Novel Hybrid Scheduling Technique for Sensor Nodes with Mixed Criticality Tasks

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Mihai-Victor Micea

2017-06-01

Full Text Available Sensor networks become increasingly a key technology for complex control applications. Their potential use in safety- and time-critical domains has raised the need for task scheduling mechanisms specially adapted to sensor node specific requirements, often materialized in predictable jitter-less execution of tasks characterized by different criticality levels. This paper offers an efficient scheduling solution, named Hybrid Hard Real-Time Scheduling (H2RTS, which combines a static, clock driven method with a dynamic, event driven scheduling technique, in order to provide high execution predictability, while keeping a high node Central Processing Unit (CPU utilization factor. From the detailed, integrated schedulability analysis of the H2RTS, a set of sufficiency tests are introduced and demonstrated based on the processor demand and linear upper bound metrics. The performance and correct behavior of the proposed hybrid scheduling technique have been extensively evaluated and validated both on a simulator and on a sensor mote equipped with ARM7 microcontroller.

Novel Hybrid Scheduling Technique for Sensor Nodes with Mixed Criticality Tasks.

Science.gov (United States)

Micea, Mihai-Victor; Stangaciu, Cristina-Sorina; Stangaciu, Valentin; Curiac, Daniel-Ioan

2017-06-26

Sensor networks become increasingly a key technology for complex control applications. Their potential use in safety- and time-critical domains has raised the need for task scheduling mechanisms specially adapted to sensor node specific requirements, often materialized in predictable jitter-less execution of tasks characterized by different criticality levels. This paper offers an efficient scheduling solution, named Hybrid Hard Real-Time Scheduling (H²RTS), which combines a static, clock driven method with a dynamic, event driven scheduling technique, in order to provide high execution predictability, while keeping a high node Central Processing Unit (CPU) utilization factor. From the detailed, integrated schedulability analysis of the H²RTS, a set of sufficiency tests are introduced and demonstrated based on the processor demand and linear upper bound metrics. The performance and correct behavior of the proposed hybrid scheduling technique have been extensively evaluated and validated both on a simulator and on a sensor mote equipped with ARM7 microcontroller.

Task-specific shell for scheduling problems, ARES[sub TM]/SCH. Scheduling mondai muke task tokka shell ARES[sub TM]/SCH

Energy Technology Data Exchange (ETDEWEB)

Kojima, S; Narimatsu, K [Toshiba Corp., Tokyo (Japan)

1994-08-01

An Expert System (ES) Shell (developed by Toshiba Corp.) which applies to the scheduling of production plan and operation plan is introduced. It describes that this tool is equipped with flowchart editor and constraint condition editor which mention the knowledge related to scheduling method, and that the former expresses scheduling procedure knowledge in the form of flowchart by combining basic tasks prepared beforehand, and the latter expresses constraint conditions which should be satisfied by the schedule, and knowledge related to the priority order which should be considered in-between in the form of IF-THEN Rule which is very close to Japanese. In addition, the knowledge is equipped with knowledge debugging system which conducts debugging while executing the knowledge. It adds that by using this tool, the manhour required for the development and maintenance of ES can be reduced considerably. 2 refs., 3 figs.

Hybrid glowworm swarm optimization for task scheduling in the cloud environment

Science.gov (United States)

Zhou, Jing; Dong, Shoubin

2018-06-01

In recent years many heuristic algorithms have been proposed to solve task scheduling problems in the cloud environment owing to their optimization capability. This article proposes a hybrid glowworm swarm optimization (HGSO) based on glowworm swarm optimization (GSO), which uses a technique of evolutionary computation, a strategy of quantum behaviour based on the principle of neighbourhood, offspring production and random walk, to achieve more efficient scheduling with reasonable scheduling costs. The proposed HGSO reduces the redundant computation and the dependence on the initialization of GSO, accelerates the convergence and more easily escapes from local optima. The conducted experiments and statistical analysis showed that in most cases the proposed HGSO algorithm outperformed previous heuristic algorithms to deal with independent tasks.

Static Scheduling of Periodic Hardware Tasks with Precedence and Deadline Constraints on Reconfigurable Hardware Devices

Directory of Open Access Journals (Sweden)

Ikbel Belaid

2011-01-01

Full Text Available Task graph scheduling for reconfigurable hardware devices can be defined as finding a schedule for a set of periodic tasks with precedence, dependence, and deadline constraints as well as their optimal allocations on the available heterogeneous hardware resources. This paper proposes a new methodology comprising three main stages. Using these three main stages, dynamic partial reconfiguration and mixed integer programming, pipelined scheduling and efficient placement are achieved and enable parallel computing of the task graph on the reconfigurable devices by optimizing placement/scheduling quality. Experiments on an application of heterogeneous hardware tasks demonstrate an improvement of resource utilization of 12.45% of the available reconfigurable resources corresponding to a resource gain of 17.3% compared to a static design. The configuration overhead is reduced to 2% of the total running time. Due to pipelined scheduling, the task graph spanning is minimized by 4% compared to sequential execution of the graph.

A Two-Level Task Scheduler on Multiple DSP System for OpenCL

Directory of Open Access Journals (Sweden)

Li Tian

2014-04-01

Full Text Available This paper addresses the problem that multiple DSP system does not support OpenCL programming. With the compiler, runtime, and the kernel scheduler proposed, an OpenCL application becomes portable not only between multiple CPU and GPU, but also between embedded multiple DSP systems. Firstly, the LLVM compiler was imported for source-to-source translation in which the translated source was supported by CCS. Secondly, two-level schedulers were proposed to support efficient OpenCL kernel execution. The DSP/BIOS is used to schedule system level tasks such as interrupts and drivers; however, the synchronization mechanism resulted in heavy overhead during task switching. So we designed an efficient second level scheduler especially for OpenCL kernel work-item scheduling. The context switch process utilizes the 8 functional units and cross path links which was superior to DSP/BIOS in the aspect of task switching. Finally, dynamic loading and software managed CACHE were redesigned for OpenCL running on multiple DSP system. We evaluated the performance using some common OpenCL kernels from NVIDIA, AMD, NAS, and Parboil benchmarks. Experimental results show that the DSP OpenCL can efficiently exploit the computing resource of multiple cores.

Scheduling technicians and tasks in a telecommunications company

DEFF Research Database (Denmark)

Cordeau, J. F.; Laporte, G.; Pasin, F.

2010-01-01

This paper proposes a construction heuristic and an adaptive large neighborhood search heuristic for the technician and task scheduling problem arising in a large telecommunications company. This problem was solved within the framework of the 2007 challenge set up by the French Operational Research...

TTSA: An Effective Scheduling Approach for Delay Bounded Tasks in Hybrid Clouds.

Science.gov (United States)

Yuan, Haitao; Bi, Jing; Tan, Wei; Zhou, MengChu; Li, Bo Hu; Li, Jianqiang

2017-11-01

The economy of scale provided by cloud attracts a growing number of organizations and industrial companies to deploy their applications in cloud data centers (CDCs) and to provide services to users around the world. The uncertainty of arriving tasks makes it a big challenge for private CDC to cost-effectively schedule delay bounded tasks without exceeding their delay bounds. Unlike previous studies, this paper takes into account the cost minimization problem for private CDC in hybrid clouds, where the energy price of private CDC and execution price of public clouds both show the temporal diversity. Then, this paper proposes a temporal task scheduling algorithm (TTSA) to effectively dispatch all arriving tasks to private CDC and public clouds. In each iteration of TTSA, the cost minimization problem is modeled as a mixed integer linear program and solved by a hybrid simulated-annealing particle-swarm-optimization. The experimental results demonstrate that compared with the existing methods, the optimal or suboptimal scheduling strategy produced by TTSA can efficiently increase the throughput and reduce the cost of private CDC while meeting the delay bounds of all the tasks.

Performance comparison of heuristic algorithms for task scheduling in IaaS cloud computing environment

Science.gov (United States)

Madni, Syed Hamid Hussain; Abd Latiff, Muhammad Shafie; Abdullahi, Mohammed; Usman, Mohammed Joda

2017-01-01

Cloud computing infrastructure is suitable for meeting computational needs of large task sizes. Optimal scheduling of tasks in cloud computing environment has been proved to be an NP-complete problem, hence the need for the application of heuristic methods. Several heuristic algorithms have been developed and used in addressing this problem, but choosing the appropriate algorithm for solving task assignment problem of a particular nature is difficult since the methods are developed under different assumptions. Therefore, six rule based heuristic algorithms are implemented and used to schedule autonomous tasks in homogeneous and heterogeneous environments with the aim of comparing their performance in terms of cost, degree of imbalance, makespan and throughput. First Come First Serve (FCFS), Minimum Completion Time (MCT), Minimum Execution Time (MET), Max-min, Min-min and Sufferage are the heuristic algorithms considered for the performance comparison and analysis of task scheduling in cloud computing. PMID:28467505

Performance comparison of heuristic algorithms for task scheduling in IaaS cloud computing environment.

Science.gov (United States)

Madni, Syed Hamid Hussain; Abd Latiff, Muhammad Shafie; Abdullahi, Mohammed; Abdulhamid, Shafi'i Muhammad; Usman, Mohammed Joda

2017-01-01

Cloud computing infrastructure is suitable for meeting computational needs of large task sizes. Optimal scheduling of tasks in cloud computing environment has been proved to be an NP-complete problem, hence the need for the application of heuristic methods. Several heuristic algorithms have been developed and used in addressing this problem, but choosing the appropriate algorithm for solving task assignment problem of a particular nature is difficult since the methods are developed under different assumptions. Therefore, six rule based heuristic algorithms are implemented and used to schedule autonomous tasks in homogeneous and heterogeneous environments with the aim of comparing their performance in terms of cost, degree of imbalance, makespan and throughput. First Come First Serve (FCFS), Minimum Completion Time (MCT), Minimum Execution Time (MET), Max-min, Min-min and Sufferage are the heuristic algorithms considered for the performance comparison and analysis of task scheduling in cloud computing.

Design issues in the semantics and scheduling of asynchronous tasks.

Energy Technology Data Exchange (ETDEWEB)

Olivier, Stephen L.

2013-07-01

The asynchronous task model serves as a useful vehicle for shared memory parallel programming, particularly on multicore and manycore processors. As adoption of model among programmers has increased, support has emerged for the integration of task parallel language constructs into mainstream programming languages, e.g., C and C++. This paper examines some of the design decisions in Cilk and OpenMP concerning semantics and scheduling of asynchronous tasks with the aim of informing the efforts of committees considering language integration, as well as developers of new task parallel languages and libraries.

A General Cross-Layer Cloud Scheduling Framework for Multiple IoT Computer Tasks.

Science.gov (United States)

Wu, Guanlin; Bao, Weidong; Zhu, Xiaomin; Zhang, Xiongtao

2018-05-23

The diversity of IoT services and applications brings enormous challenges to improving the performance of multiple computer tasks' scheduling in cross-layer cloud computing systems. Unfortunately, the commonly-employed frameworks fail to adapt to the new patterns on the cross-layer cloud. To solve this issue, we design a new computer task scheduling framework for multiple IoT services in cross-layer cloud computing systems. Specifically, we first analyze the features of the cross-layer cloud and computer tasks. Then, we design the scheduling framework based on the analysis and present detailed models to illustrate the procedures of using the framework. With the proposed framework, the IoT services deployed in cross-layer cloud computing systems can dynamically select suitable algorithms and use resources more effectively to finish computer tasks with different objectives. Finally, the algorithms are given based on the framework, and extensive experiments are also given to validate its effectiveness, as well as its superiority.

A Hybrid Task Graph Scheduler for High Performance Image Processing Workflows.

Science.gov (United States)

Blattner, Timothy; Keyrouz, Walid; Bhattacharyya, Shuvra S; Halem, Milton; Brady, Mary

2017-12-01

Designing applications for scalability is key to improving their performance in hybrid and cluster computing. Scheduling code to utilize parallelism is difficult, particularly when dealing with data dependencies, memory management, data motion, and processor occupancy. The Hybrid Task Graph Scheduler (HTGS) improves programmer productivity when implementing hybrid workflows for multi-core and multi-GPU systems. The Hybrid Task Graph Scheduler (HTGS) is an abstract execution model, framework, and API that increases programmer productivity when implementing hybrid workflows for such systems. HTGS manages dependencies between tasks, represents CPU and GPU memories independently, overlaps computations with disk I/O and memory transfers, keeps multiple GPUs occupied, and uses all available compute resources. Through these abstractions, data motion and memory are explicit; this makes data locality decisions more accessible. To demonstrate the HTGS application program interface (API), we present implementations of two example algorithms: (1) a matrix multiplication that shows how easily task graphs can be used; and (2) a hybrid implementation of microscopy image stitching that reduces code size by ≈ 43% compared to a manually coded hybrid workflow implementation and showcases the minimal overhead of task graphs in HTGS. Both of the HTGS-based implementations show good performance. In image stitching the HTGS implementation achieves similar performance to the hybrid workflow implementation. Matrix multiplication with HTGS achieves 1.3× and 1.8× speedup over the multi-threaded OpenBLAS library for 16k × 16k and 32k × 32k size matrices, respectively.

Scheduling the scheduling task : a time management perspective on scheduling

NARCIS (Netherlands)

Larco Martinelli, J.A.; Wiers, V.C.S.; Fransoo, J.C.

2013-01-01

Time is the most critical resource at the disposal of schedulers. Hence, an adequate management of time from the schedulers may impact positively on the scheduler’s productivity and responsiveness to uncertain scheduling environments. This paper presents a field study of how schedulers make use of

Hypergraph+: An Improved Hypergraph-Based Task-Scheduling Algorithm for Massive Spatial Data Processing on Master-Slave Platforms

Directory of Open Access Journals (Sweden)

Bo Cheng

2016-08-01

Full Text Available Spatial data processing often requires massive datasets, and the task/data scheduling efficiency of these applications has an impact on the overall processing performance. Among the existing scheduling strategies, hypergraph-based algorithms capture the data sharing pattern in a global way and significantly reduce total communication volume. Due to heterogeneous processing platforms, however, single hypergraph partitioning for later scheduling may be not optimal. Moreover, these scheduling algorithms neglect the overlap between task execution and data transfer that could further decrease execution time. In order to address these problems, an extended hypergraph-based task-scheduling algorithm, named Hypergraph+, is proposed for massive spatial data processing. Hypergraph+ improves upon current hypergraph scheduling algorithms in two ways: (1 It takes platform heterogeneity into consideration offering a metric function to evaluate the partitioning quality in order to derive the best task/file schedule; and (2 It can maximize the overlap between communication and computation. The GridSim toolkit was used to evaluate Hypergraph+ in an IDW spatial interpolation application on heterogeneous master-slave platforms. Experiments illustrate that the proposed Hypergraph+ algorithm achieves on average a 43% smaller makespan than the original hypergraph scheduling algorithm but still preserves high scheduling efficiency.

A Hybrid Scheduler for Many Task Computing in Big Data Systems

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Vasiliu Laura

2017-06-01

Full Text Available With the rapid evolution of the distributed computing world in the last few years, the amount of data created and processed has fast increased to petabytes or even exabytes scale. Such huge data sets need data-intensive computing applications and impose performance requirements to the infrastructures that support them, such as high scalability, storage, fault tolerance but also efficient scheduling algorithms. This paper focuses on providing a hybrid scheduling algorithm for many task computing that addresses big data environments with few penalties, taking into consideration the deadlines and satisfying a data dependent task model. The hybrid solution consists of several heuristics and algorithms (min-min, min-max and earliest deadline first combined in order to provide a scheduling algorithm that matches our problem. The experimental results are conducted by simulation and prove that the proposed hybrid algorithm behaves very well in terms of meeting deadlines.

Research on Scheduling Algorithm for Multi-satellite and Point Target Task on Swinging Mode

Science.gov (United States)

Wang, M.; Dai, G.; Peng, L.; Song, Z.; Chen, G.

2012-12-01

Nowadays, using satellite in space to observe ground is an important and major method to obtain ground information. With the development of the scientific technology in the field of space, many fields such as military and economic and other areas have more and more requirement of space technology because of the benefits of the satellite's widespread, timeliness and unlimited of area and country. And at the same time, because of the wide use of all kinds of satellites, sensors, repeater satellites and ground receiving stations, ground control system are now facing great challenge. Therefore, how to make the best value of satellite resources so as to make full use of them becomes an important problem of ground control system. Satellite scheduling is to distribute the resource to all tasks without conflict to obtain the scheduling result so as to complete as many tasks as possible to meet user's requirement under considering the condition of the requirement of satellites, sensors and ground receiving stations. Considering the size of the task, we can divide tasks into point task and area task. This paper only considers point targets. In this paper, a description of satellite scheduling problem and a chief introduction of the theory of satellite scheduling are firstly made. We also analyze the restriction of resource and task in scheduling satellites. The input and output flow of scheduling process are also chiefly described in the paper. On the basis of these analyses, we put forward a scheduling model named as multi-variable optimization model for multi-satellite and point target task on swinging mode. In the multi-variable optimization model, the scheduling problem is transformed the parametric optimization problem. The parameter we wish to optimize is the swinging angle of every time-window. In the view of the efficiency and accuracy, some important problems relating the satellite scheduling such as the angle relation between satellites and ground targets, positive

Hybrid Symbiotic Organisms Search Optimization Algorithm for Scheduling of Tasks on Cloud Computing Environment.

Science.gov (United States)

Abdullahi, Mohammed; Ngadi, Md Asri

2016-01-01

Cloud computing has attracted significant attention from research community because of rapid migration rate of Information Technology services to its domain. Advances in virtualization technology has made cloud computing very popular as a result of easier deployment of application services. Tasks are submitted to cloud datacenters to be processed on pay as you go fashion. Task scheduling is one the significant research challenges in cloud computing environment. The current formulation of task scheduling problems has been shown to be NP-complete, hence finding the exact solution especially for large problem sizes is intractable. The heterogeneous and dynamic feature of cloud resources makes optimum task scheduling non-trivial. Therefore, efficient task scheduling algorithms are required for optimum resource utilization. Symbiotic Organisms Search (SOS) has been shown to perform competitively with Particle Swarm Optimization (PSO). The aim of this study is to optimize task scheduling in cloud computing environment based on a proposed Simulated Annealing (SA) based SOS (SASOS) in order to improve the convergence rate and quality of solution of SOS. The SOS algorithm has a strong global exploration capability and uses fewer parameters. The systematic reasoning ability of SA is employed to find better solutions on local solution regions, hence, adding exploration ability to SOS. Also, a fitness function is proposed which takes into account the utilization level of virtual machines (VMs) which reduced makespan and degree of imbalance among VMs. CloudSim toolkit was used to evaluate the efficiency of the proposed method using both synthetic and standard workload. Results of simulation showed that hybrid SOS performs better than SOS in terms of convergence speed, response time, degree of imbalance, and makespan.

Hybrid Symbiotic Organisms Search Optimization Algorithm for Scheduling of Tasks on Cloud Computing Environment.

Directory of Open Access Journals (Sweden)

Mohammed Abdullahi

Full Text Available Cloud computing has attracted significant attention from research community because of rapid migration rate of Information Technology services to its domain. Advances in virtualization technology has made cloud computing very popular as a result of easier deployment of application services. Tasks are submitted to cloud datacenters to be processed on pay as you go fashion. Task scheduling is one the significant research challenges in cloud computing environment. The current formulation of task scheduling problems has been shown to be NP-complete, hence finding the exact solution especially for large problem sizes is intractable. The heterogeneous and dynamic feature of cloud resources makes optimum task scheduling non-trivial. Therefore, efficient task scheduling algorithms are required for optimum resource utilization. Symbiotic Organisms Search (SOS has been shown to perform competitively with Particle Swarm Optimization (PSO. The aim of this study is to optimize task scheduling in cloud computing environment based on a proposed Simulated Annealing (SA based SOS (SASOS in order to improve the convergence rate and quality of solution of SOS. The SOS algorithm has a strong global exploration capability and uses fewer parameters. The systematic reasoning ability of SA is employed to find better solutions on local solution regions, hence, adding exploration ability to SOS. Also, a fitness function is proposed which takes into account the utilization level of virtual machines (VMs which reduced makespan and degree of imbalance among VMs. CloudSim toolkit was used to evaluate the efficiency of the proposed method using both synthetic and standard workload. Results of simulation showed that hybrid SOS performs better than SOS in terms of convergence speed, response time, degree of imbalance, and makespan.

Time and Energy Efficient DVS Scheduling for Real-Time Pinwheel Tasks

OpenAIRE

Da-Ren, Chen; Young-Long, Chen; You-Shyang, Chen

2014-01-01

Dynamic voltage/frequency scaling (DVFS) is one of the most effective techniques for reducing energy use. In this paper, we focus on the pinwheel task model to develop a variable voltage processor with d discrete voltage/speed levels. Depending on the granularity of execution unit to which voltage scaling is applied, DVFS scheduling can be defined in two categories: (i) inter-task DVFS and (ii) intra-task DVFS. In the periodic pinwheel task model, we modified the definitions of both intra- an...

Optimization of Task Scheduling Algorithm through QoS Parameters for Cloud Computing

Directory of Open Access Journals (Sweden)

Monika

2016-01-01

Full Text Available Cloud computing is an incipient innovation which broadly spreads among analysts. It furnishes clients with foundation, stage and programming as enhancement which is easily available by means of web. A cloud is a sort of parallel and conveyed framework comprising of a gathering of virtualized PCs that are utilized to execute various tasks to accomplish good execution time, accomplish due date and usage of its assets. The scheduling issue can be seen as the finding an ideal task of assignments over the accessible arrangement of assets with the goal that we can accomplish the wanted objectives for tasks. This paper presents an optimal algorithm for scheduling tasks to get their waiting time as a QoS parameter. The algorithm is simulated using Cloudsim simulator and experiments are carried out to help clients to make sense of the bottleneck of utilizing no. of virtual machine parallely.

Underground storage tank - Integrated Demonstration Technical Task Plan master schedule

International Nuclear Information System (INIS)

Johnson, C.M.

1994-08-01

This document provides an integrated programmatic schedule (i.e., Master Schedule) for the U.S. Department of Energy (DOE) Underground Storage Tank-Integrated Demonstration (UST-ID) Program. It includes top-level schedule and related information for the DOE Office of Technology Development (EM-50) UST-ID activities. The information is based upon the fiscal year (FY) 1994 technical task plans (TTPS) and has been prepared as a baseline information resource for program participants. The Master Schedule contains Level 0 and Level 1 program schedules for the UST-ID Program. This document is one of a number of programmatic documents developed to support and manage the UST-ID activities. It is composed of the following sections: Program Overview - provides a summary background of the UST-ID Program. This summary addresses the mission, scope, and organizational structure of the program; Activity Description - provides a programmatic description of UST-ID technology development activities and lists the key milestones for the UST-ID systems. Master Schedules - contains the Level 0 and Level 1 programmatic schedules for the UST-ID systems. References - lists the UST-ID programmatic documents used as a basis for preparing the Master Schedule. The appendixes contain additional details related to site-specific technology applications

Locality-Aware Task Scheduling and Data Distribution for OpenMP Programs on NUMA Systems and Manycore Processors

Directory of Open Access Journals (Sweden)

Ananya Muddukrishna

2015-01-01

Full Text Available Performance degradation due to nonuniform data access latencies has worsened on NUMA systems and can now be felt on-chip in manycore processors. Distributing data across NUMA nodes and manycore processor caches is necessary to reduce the impact of nonuniform latencies. However, techniques for distributing data are error-prone and fragile and require low-level architectural knowledge. Existing task scheduling policies favor quick load-balancing at the expense of locality and ignore NUMA node/manycore cache access latencies while scheduling. Locality-aware scheduling, in conjunction with or as a replacement for existing scheduling, is necessary to minimize NUMA effects and sustain performance. We present a data distribution and locality-aware scheduling technique for task-based OpenMP programs executing on NUMA systems and manycore processors. Our technique relieves the programmer from thinking of NUMA system/manycore processor architecture details by delegating data distribution to the runtime system and uses task data dependence information to guide the scheduling of OpenMP tasks to reduce data stall times. We demonstrate our technique on a four-socket AMD Opteron machine with eight NUMA nodes and on the TILEPro64 processor and identify that data distribution and locality-aware task scheduling improve performance up to 69% for scientific benchmarks compared to default policies and yet provide an architecture-oblivious approach for programmers.

Cloud computing task scheduling strategy based on differential evolution and ant colony optimization

Science.gov (United States)

Ge, Junwei; Cai, Yu; Fang, Yiqiu

2018-05-01

This paper proposes a task scheduling strategy DEACO based on the combination of Differential Evolution (DE) and Ant Colony Optimization (ACO), aiming at the single problem of optimization objective in cloud computing task scheduling, this paper combines the shortest task completion time, cost and load balancing. DEACO uses the solution of the DE to initialize the initial pheromone of ACO, reduces the time of collecting the pheromone in ACO in the early, and improves the pheromone updating rule through the load factor. The proposed algorithm is simulated on cloudsim, and compared with the min-min and ACO. The experimental results show that DEACO is more superior in terms of time, cost, and load.

Economic and environmental scheduling of smart homes with microgrid: DER operation and electrical tasks

International Nuclear Information System (INIS)

Zhang, Di; Evangelisti, Sara; Lettieri, Paola; Papageorgiou, Lazaros G.

2016-01-01

Highlights: • An MILP model is formulated for energy consumption scheduling among smart homes. • Environmental and economic aspects are both addressed. • The model is implemented on an example with data profiles from the UK. • Pareto-optimal curves between cost and CO_2 emissions are obtained. • Real-time pricing and critical peak pricing schemes are investigated. - Abstract: Microgrids are promising in reducing energy consumption and carbon emissions, compared with the current centralised energy generation systems. Smart homes are becoming popular for their lower energy cost and provision of comfort. Flexible energy-consuming household tasks can be scheduled co-ordinately among multiple smart homes to reduce economic cost and CO_2. However, the electricity tariff is not always positively correlated with CO_2 intensity. In this work, a mixed integer linear programming (MILP) model is proposed to schedule the energy consumption within smart homes using a microgrid system. The daily power consumption tasks are scheduled by coupling environmental and economic sustainability in a multi-objective optimisation with ε-constraint method. The two conflicting objectives are to minimise the daily energy cost and CO_2 emissions. Distributed energy resources (DER) operation and electricity-consumption household tasks are scheduled based on electricity tariff, CO_2 intensity and electricity task time window. The proposed model is implemented on a smart building of 30 homes under three different price schemes. Electricity tariff and CO_2 intensity profiles of the UK are employed for the case study. The Pareto curves for cost and CO_2 emissions present the trade-off between the two conflicting objectives.

Investigating the Effect of Voltage-Switching on Low-Energy Task Scheduling in Hard Real-Time Systems

Science.gov (United States)

2005-01-01

We investigate the effect of voltage-switching on task execution times and energy consumption for dual-speed hard real - time systems , and present a...scheduling algorithm and apply it to two real-life task sets. Our results show that energy can be conserved in embedded real - time systems using energy...aware task scheduling. We also show that switching times have a significant effect on the energy consumed in hard real - time systems .

Degree of Schedulability of Mixed-Criticality Real-time Systems with Probabilistic Sporadic Tasks

DEFF Research Database (Denmark)

Boudjadar, Jalil; David, Alexandre; Kim, Jin Hyun

2014-01-01

We present the concept of degree of schedulability for mixed-criticality scheduling systems. This concept is given in terms of the two factors 1) Percentage of Missed Deadlines (PoMD), and 2) Degradation of the Quality of Service (DoQoS). The novel aspect is that we consider task arrival patterns...

Task path planning, scheduling and learning for free-ranging robot systems

Science.gov (United States)

Wakefield, G. Steve

1987-01-01

The development of robotics applications for space operations is often restricted by the limited movement available to guided robots. Free ranging robots can offer greater flexibility than physically guided robots in these applications. Presented here is an object oriented approach to path planning and task scheduling for free-ranging robots that allows the dynamic determination of paths based on the current environment. The system also provides task learning for repetitive jobs. This approach provides a basis for the design of free-ranging robot systems which are adaptable to various environments and tasks.

Task-FIFO co-scheduling of streaming applications on MPSoCs with predictable memory hierarchy

NARCIS (Netherlands)

Tang, Q.; Basten, A.A.; Geilen, M.C.W.; Stuijk, S.; Wei, Ji-Bo

This article studies the scheduling of real-time streaming applications on multiprocessor systems-on-chips with predictable memory hierarchy. An iteration-based task-FIFO co-scheduling framework is proposed for this problem. We obtain FIFO size distributions using Pareto space searching, based on

Task-FIFO co-scheduling of streaming applications on MPSoCs with predictable memory hierarchy

NARCIS (Netherlands)

Tang, Q.; Basten, T.; Geilen, M.; Stuijk, S.; Wei, J.B.

2017-01-01

This article studies the scheduling of real-time streaming applications on multiprocessor systems-on-chips with predictable memory hierarchy. An iteration-based task-FIFO co-scheduling framework is proposed for this problem. We obtain FIFO size distributions using Pareto space searching, based on

TaskMaster: a prototype graphical user interface to a schedule optimization model

OpenAIRE

Banham, Stephen R.

1990-01-01

Approved for public release, distribution is unlimited This thesis investigates the use of current graphical interface techniques to build more effective computer-user interfaces to Operations Research (OR) schedule optimization models. The design is directed at the scheduling decision maker who possesses limited OR experience. The feasibility and validity of building an interface for this kind of user is demonstrated in the development of a prototype graphical user interface called TaskMa...

Using Activity Schedules to Increase On-Task Behavior in Children at Risk for Attention-Deficit/Hyperactivity Disorder

Science.gov (United States)

Cirelli, Christe A.; Sidener, Tina M.; Reeve, Kenneth F.; Reeve, Sharon A.

2016-01-01

The effects of activity schedules on on-task and on-schedule behavior were assessed with two boys at risk for attention-deficit/hyperactivity disorder (ADHD) and referred by their public school teachers as having difficulty during independent work time. On-task behavior increased for both participants after two training sessions. Teachers, peers,…

A Work-Demand Analysis Compatible with Preemption-Aware Scheduling for Power-Aware Real-Time Tasks

Directory of Open Access Journals (Sweden)

Da-Ren Chen

2013-01-01

Full Text Available Due to the importance of slack time utilization for power-aware scheduling algorithms,we propose a work-demand analysis method called parareclamation algorithm (PRA to increase slack time utilization of the existing real-time DVS algorithms. PRA is an online scheduling for power-aware real-time tasks under rate-monotonic (RM policy. It can be implemented and fully compatible with preemption-aware or transition-aware scheduling algorithms without increasing their computational complexities. The key technique of the heuristics method doubles the analytical interval and turns the deferrable workload out the potential slack time. Theoretical proofs show that PRA guarantees the task deadlines in a feasible RM schedule and takes linear time and space complexities. Experimental results indicate that the proposed method combining the preemption-aware methods seamlessly reduces the energy consumption by 14% on average over their original algorithms.

A FAST AND ELITIST BI-OBJECTIVE EVOLUTIONARY ALGORITHM FOR SCHEDULING INDEPENDENT TASKS ON HETEROGENEOUS SYSTEMS

Directory of Open Access Journals (Sweden)

G.Subashini

2010-07-01

Full Text Available To meet the increasing computational demands, geographically distributed resources need to be logically coupled to make them work as a unified resource. In analyzing the performance of such distributed heterogeneous computing systems scheduling a set of tasks to the available set of resources for execution is highly important. Task scheduling being an NP-complete problem, use of metaheuristics is more appropriate in obtaining optimal solutions. Schedules thus obtained can be evaluated using several criteria that may conflict with one another which require multi objective problem formulation. This paper investigates the application of an elitist Nondominated Sorting Genetic Algorithm (NSGA-II, to efficiently schedule a set of independent tasks in a heterogeneous distributed computing system. The objectives considered in this paper include minimizing makespan and average flowtime simultaneously. The implementation of NSGA-II algorithm and Weighted-Sum Genetic Algorithm (WSGA has been tested on benchmark instances for distributed heterogeneous systems. As NSGA-II generates a set of Pareto optimal solutions, to verify the effectiveness of NSGA-II over WSGA a fuzzy based membership value assignment method is employed to choose the best compromise solution from the obtained Pareto solution set.

Hard Real-Time Task Scheduling in Cloud Computing Using an Adaptive Genetic Algorithm

Directory of Open Access Journals (Sweden)

Amjad Mahmood

2017-04-01

Full Text Available In the Infrastructure-as-a-Service cloud computing model, virtualized computing resources in the form of virtual machines are provided over the Internet. A user can rent an arbitrary number of computing resources to meet their requirements, making cloud computing an attractive choice for executing real-time tasks. Economical task allocation and scheduling on a set of leased virtual machines is an important problem in the cloud computing environment. This paper proposes a greedy and a genetic algorithm with an adaptive selection of suitable crossover and mutation operations (named as AGA to allocate and schedule real-time tasks with precedence constraint on heterogamous virtual machines. A comprehensive simulation study has been done to evaluate the performance of the proposed algorithms in terms of their solution quality and efficiency. The simulation results show that AGA outperforms the greedy algorithm and non-adaptive genetic algorithm in terms of solution quality.

Metaheuristic Based Scheduling Meta-Tasks in Distributed Heterogeneous Computing Systems

Directory of Open Access Journals (Sweden)

Hesam Izakian

2009-07-01

Full Text Available Scheduling is a key problem in distributed heterogeneous computing systems in order to benefit from the large computing capacity of such systems and is an NP-complete problem. In this paper, we present a metaheuristic technique, namely the Particle Swarm Optimization (PSO algorithm, for this problem. PSO is a population-based search algorithm based on the simulation of the social behavior of bird flocking and fish schooling. Particles fly in problem search space to find optimal or near-optimal solutions. The scheduler aims at minimizing makespan, which is the time when finishes the latest task. Experimental studies show that the proposed method is more efficient and surpasses those of reported PSO and GA approaches for this problem.

Scheduling a maintenance activity under skills constraints to minimize total weighted tardiness and late tasks

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Djalal Hedjazi

2015-04-01

Full Text Available Skill management is a key factor in improving effectiveness of industrial companies, notably their maintenance services. The problem considered in this paper concerns scheduling of maintenance tasks under resource (maintenance teams constraints. This problem is generally known as unrelated parallel machine scheduling. We consider the problem with a both objectives of minimizing total weighted tardiness (TWT and number of tardiness tasks. Our interest is focused particularly on solving this problem under skill constraints, which each resource has a skill level. So, we propose a new efficient heuristic to obtain an approximate solution for this NP-hard problem and demonstrate his effectiveness through computational experiments. This heuristic is designed for implementation in a static maintenance scheduling problem (with unequal release dates, processing times and resource skills, while minimizing objective functions aforementioned.

Investigating the Effect of Voltage-Switching on Low-Energy Task Scheduling in Hard Real-Time Systems

National Research Council Canada - National Science Library

Swaminathan, Vishnu; Chakrabarty, Krishnendu

2005-01-01

We investigate the effect of voltage-switching on task execution times and energy consumption for dual-speed hard real-time systems, and present a new approach for scheduling workloads containing periodic tasks...

Effects of practice schedule and task specificity on the adaptive process of motor learning.

Science.gov (United States)

Barros, João Augusto de Camargo; Tani, Go; Corrêa, Umberto Cesar

2017-10-01

This study investigated the effects of practice schedule and task specificity based on the perspective of adaptive process of motor learning. For this purpose, tasks with temporal and force control learning requirements were manipulated in experiments 1 and 2, respectively. Specifically, the task consisted of touching with the dominant hand the three sequential targets with specific movement time or force for each touch. Participants were children (N=120), both boys and girls, with an average age of 11.2years (SD=1.0). The design in both experiments involved four practice groups (constant, random, constant-random, and random-constant) and two phases (stabilisation and adaptation). The dependent variables included measures related to the task goal (accuracy and variability of error of the overall movement and force patterns) and movement pattern (macro- and microstructures). Results revealed a similar error of the overall patterns for all groups in both experiments and that they adapted themselves differently in terms of the macro- and microstructures of movement patterns. The study concludes that the effects of practice schedules on the adaptive process of motor learning were both general and specific to the task. That is, they were general to the task goal performance and specific regarding the movement pattern. Copyright © 2017 Elsevier B.V. All rights reserved.

Effective Task Scheduling and IP Mapping Algorithm for Heterogeneous NoC-Based MPSoC

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Peng-Fei Yang

2014-01-01

Full Text Available Quality of task scheduling is critical to define the network communication efficiency and the performance of the entire NoC- (Network-on-Chip- based MPSoC (multiprocessor System-on-Chip. In this paper, the NoC-based MPSoC design process is favorably divided into two steps, that is, scheduling subtasks to processing elements (PEs of appropriate type and quantity and then mapping these PEs onto the switching nodes of NoC topology. When the task model is improved so that it reflects better the real intertask relations, optimized particle swarm optimization (PSO is utilized to achieve the first step with expected less task running and transfer cost as well as the least task execution time. By referring to the topology of NoC and the resultant communication diagram of the first step, the second step is done with the minimal expected network transmission delay as well as less resource consumption and even power consumption. The comparative experiments have shown the preferable resource and power consumption of the algorithm when it is actually adopted in a system design.

Segment Fixed Priority Scheduling for Self Suspending Real Time Tasks

Science.gov (United States)

2016-08-11

a compute- intensive system such as a self - driving car that we have recently developed [28]. Such systems run computation-demanding algorithms...Applications. In RTSS, 2012. [12] J. Kim et al. Parallel Scheduling for Cyber-Physical Systems: Analysis and Case Study on a Self - Driving Car . In ICCPS...leveraging GPU can be modeled using a multi-segment self -suspending real-time task model. For example, a planning algorithm for autonomous driving can

A Chaotic Particle Swarm Optimization-Based Heuristic for Market-Oriented Task-Level Scheduling in Cloud Workflow Systems.

Science.gov (United States)

Li, Xuejun; Xu, Jia; Yang, Yun

2015-01-01

Cloud workflow system is a kind of platform service based on cloud computing. It facilitates the automation of workflow applications. Between cloud workflow system and its counterparts, market-oriented business model is one of the most prominent factors. The optimization of task-level scheduling in cloud workflow system is a hot topic. As the scheduling is a NP problem, Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) have been proposed to optimize the cost. However, they have the characteristic of premature convergence in optimization process and therefore cannot effectively reduce the cost. To solve these problems, Chaotic Particle Swarm Optimization (CPSO) algorithm with chaotic sequence and adaptive inertia weight factor is applied to present the task-level scheduling. Chaotic sequence with high randomness improves the diversity of solutions, and its regularity assures a good global convergence. Adaptive inertia weight factor depends on the estimate value of cost. It makes the scheduling avoid premature convergence by properly balancing between global and local exploration. The experimental simulation shows that the cost obtained by our scheduling is always lower than the other two representative counterparts.

Intelligent discrete particle swarm optimization for multiprocessor task scheduling problem

Directory of Open Access Journals (Sweden)

S Sarathambekai

2017-03-01

Full Text Available Discrete particle swarm optimization is one of the most recently developed population-based meta-heuristic optimization algorithm in swarm intelligence that can be used in any discrete optimization problems. This article presents a discrete particle swarm optimization algorithm to efficiently schedule the tasks in the heterogeneous multiprocessor systems. All the optimization algorithms share a common algorithmic step, namely population initialization. It plays a significant role because it can affect the convergence speed and also the quality of the final solution. The random initialization is the most commonly used method in majority of the evolutionary algorithms to generate solutions in the initial population. The initial good quality solutions can facilitate the algorithm to locate the optimal solution or else it may prevent the algorithm from finding the optimal solution. Intelligence should be incorporated to generate the initial population in order to avoid the premature convergence. This article presents a discrete particle swarm optimization algorithm, which incorporates opposition-based technique to generate initial population and greedy algorithm to balance the load of the processors. Make span, flow time, and reliability cost are three different measures used to evaluate the efficiency of the proposed discrete particle swarm optimization algorithm for scheduling independent tasks in distributed systems. Computational simulations are done based on a set of benchmark instances to assess the performance of the proposed algorithm.

LOAD ADAPTIVE DYNAMIC SCHEDULING OF TASKS WITH HARD DEADLINES USEFUL FOR INDUSTRIAL APPLICATIONS

NARCIS (Netherlands)

HALANG, WA

1992-01-01

All intrinsic properties of the earliest deadline task scheduling discipline are compiled and discussed in order to show that this is the most advantageous scheme at hand, characterised by efficiency and allowing predictable system behaviour. It is then pointed out how the method naturally extends

Cooperative Scheduling of Imaging Observation Tasks for High-Altitude Airships Based on Propagation Algorithm

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He Chuan

2012-01-01

Full Text Available The cooperative scheduling problem on high-altitude airships for imaging observation tasks is discussed. A constraint programming model is established by analyzing the main constraints, which takes the maximum task benefit and the minimum cruising distance as two optimization objectives. The cooperative scheduling problem of high-altitude airships is converted into a main problem and a subproblem by adopting hierarchy architecture. The solution to the main problem can construct the preliminary matching between tasks and observation resource in order to reduce the search space of the original problem. Furthermore, the solution to the sub-problem can detect the key nodes that each airship needs to fly through in sequence, so as to get the cruising path. Firstly, the task set is divided by using k-core neighborhood growth cluster algorithm (K-NGCA. Then, a novel swarm intelligence algorithm named propagation algorithm (PA is combined with the key node search algorithm (KNSA to optimize the cruising path of each airship and determine the execution time interval of each task. Meanwhile, this paper also provides the realization approach of the above algorithm and especially makes a detailed introduction on the encoding rules, search models, and propagation mechanism of the PA. Finally, the application results and comparison analysis show the proposed models and algorithms are effective and feasible.

A Chaotic Particle Swarm Optimization-Based Heuristic for Market-Oriented Task-Level Scheduling in Cloud Workflow Systems

Directory of Open Access Journals (Sweden)

Xuejun Li

2015-01-01

Full Text Available Cloud workflow system is a kind of platform service based on cloud computing. It facilitates the automation of workflow applications. Between cloud workflow system and its counterparts, market-oriented business model is one of the most prominent factors. The optimization of task-level scheduling in cloud workflow system is a hot topic. As the scheduling is a NP problem, Ant Colony Optimization (ACO and Particle Swarm Optimization (PSO have been proposed to optimize the cost. However, they have the characteristic of premature convergence in optimization process and therefore cannot effectively reduce the cost. To solve these problems, Chaotic Particle Swarm Optimization (CPSO algorithm with chaotic sequence and adaptive inertia weight factor is applied to present the task-level scheduling. Chaotic sequence with high randomness improves the diversity of solutions, and its regularity assures a good global convergence. Adaptive inertia weight factor depends on the estimate value of cost. It makes the scheduling avoid premature convergence by properly balancing between global and local exploration. The experimental simulation shows that the cost obtained by our scheduling is always lower than the other two representative counterparts.

MULTISHAPE TASK SCHEDULING ALGORITHM FOR REAL TIME MICRO-CONTROLLER BASED APPLICATION

OpenAIRE

Ankur Jain

2017-01-01

Embedded Systems are usually microcontroller-based systems that represent a class of reliable and dependable dedicated computer systems designed for specific purposes. Micro-controllers are used in most electronic devices in an endless variety of ways. Some micro-controller-based embedded systems are required to respond to external events in the shortest possible time and such systems are known as realtime embedded systems. So in multitasking system there is a need of task Scheduling, there a...

Scheduling techniques in the Request Oriented Scheduling Engine (ROSE)

Science.gov (United States)

Zoch, David R.

1991-01-01

Scheduling techniques in the ROSE are presented in the form of the viewgraphs. The following subject areas are covered: agenda; ROSE summary and history; NCC-ROSE task goals; accomplishments; ROSE timeline manager; scheduling concerns; current and ROSE approaches; initial scheduling; BFSSE overview and example; and summary.

Analyzing the effect of gain time on soft task scheduling policies in real-time systems

OpenAIRE

Búrdalo Rapa, Luis Antonio; Terrasa Barrena, Andrés Martín; Espinosa Minguet, Agustín Rafael; García Fornes, Ana María

2012-01-01

In hard real-time systems, gain time is defined as the difference between the Worst Case Execution Time (WCET) of a hard task and its actual processor consumption at runtime. This paper presents the results of an empirical study about how the presence of a significant amount of gain time in a hard real-time system questions the advantages of using the most representative scheduling algorithms or policies for aperiodic or soft tasks in fixed-priority preemptive systems. The work presented here...

Project Schedule Simulation

DEFF Research Database (Denmark)

Mizouni, Rabeb; Lazarova-Molnar, Sanja

2015-01-01

overrun both their budget and time. To improve the quality of initial project plans, we show in this paper the importance of (1) reflecting features’ priorities/risk in task schedules and (2) considering uncertainties related to human factors in plan schedules. To make simulation tasks reflect features......’ priority as well as multimodal team allocation, enhanced project schedules (EPS), where remedial actions scenarios (RAS) are added, were introduced. They reflect potential schedule modifications in case of uncertainties and promote a dynamic sequencing of involved tasks rather than the static conventional...... this document as an instruction set. The electronic file of your paper will be formatted further at Journal of Software. Define all symbols used in the abstract. Do not cite references in the abstract. Do not delete the blank line immediately above the abstract; it sets the footnote at the bottom of this column....

Task Balanced Workflow Scheduling Technique considering Task Processing Rate in Spot Market

Directory of Open Access Journals (Sweden)

Daeyong Jung

2014-01-01

Full Text Available Recently, the cloud computing is a computing paradigm that constitutes an advanced computing environment that evolved from the distributed computing. And the cloud computing provides acquired computing resources in a pay-as-you-go manner. For example, Amazon EC2 offers the Infrastructure-as-a-Service (IaaS instances in three different ways with different price, reliability, and various performances of instances. Our study is based on the environment using spot instances. Spot instances can significantly decrease costs compared to reserved and on-demand instances. However, spot instances give a more unreliable environment than other instances. In this paper, we propose the workflow scheduling scheme that reduces the out-of-bid situation. Consequently, the total task completion time is decreased. The simulation results reveal that, compared to various instance types, our scheme achieves performance improvements in terms of an average combined metric of 12.76% over workflow scheme without considering the processing rate. However, the cost in our scheme is higher than an instance with low performance and is lower than an instance with high performance.

Optimal Temporal Decoupling in Task Scheduling with Preferences

NARCIS (Netherlands)

Endhoven, L.; Klos, T.B.; Witteveen, C.

2011-01-01

Multi-agent planning and scheduling concerns finding a joint plan to achieve some set of common goals with several independent agents each aiming to find a plan or schedule for their part of the goals. To avoid conflicts in these individual plans or schedules decoupling is used. Such a decoupling

Cloud Service Scheduling Algorithm Research and Optimization

Directory of Open Access Journals (Sweden)

Hongyan Cui

2017-01-01

Full Text Available We propose a cloud service scheduling model that is referred to as the Task Scheduling System (TSS. In the user module, the process time of each task is in accordance with a general distribution. In the task scheduling module, we take a weighted sum of makespan and flowtime as the objective function and use an Ant Colony Optimization (ACO and a Genetic Algorithm (GA to solve the problem of cloud task scheduling. Simulation results show that the convergence speed and output performance of our Genetic Algorithm-Chaos Ant Colony Optimization (GA-CACO are optimal.

Towards best-case response times of real-time tasks under fixed-priority scheduling with deferred preemption

NARCIS (Netherlands)

Bril, R.J.; Verhaegh, W.F.J.; Puaut, I.

2005-01-01

In this paper, we present lower bounds for best-case response times of periodic tasks under fixed-priority scheduling with deferred preemption (FPDS) and arbitrary phasing. Our analysis is based on a dedicated conjecture for a ¿-optimal instant, and uses the notion of best-case occupied time. We

An Adaptive Procedure for Task Scheduling Optimization in Mobile Cloud Computing

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Pham Phuoc Hung

2015-01-01

Full Text Available Nowadays, mobile cloud computing (MCC has emerged as a new paradigm which enables offloading computation-intensive, resource-consuming tasks up to a powerful computing platform in cloud, leaving only simple jobs to the capacity-limited thin client devices such as smartphones, tablets, Apple’s iWatch, and Google Glass. However, it still faces many challenges due to inherent problems of thin clients, especially the slow processing and low network connectivity. So far, a number of research studies have been carried out, trying to eliminate these problems, yet few have been found efficient. In this paper, we present an enhanced architecture, taking advantage of collaboration of thin clients and conventional desktop or laptop computers, known as thick clients, particularly aiming at improving cloud access. Additionally, we introduce an innovative genetic approach for task scheduling such that the processing time is minimized, while considering network contention and cloud cost. Our simulation shows that the proposed approach is more cost-effective and achieves better performance compared with others.

Mechanisms for scheduling games with selfish players

NARCIS (Netherlands)

Hoeksma, R.P.

2015-01-01

Many challenges in operations research involve optimization. In particular, scheduling treats the optimal planning of tasks. This thesis focuses on machine scheduling models, where a number of tasks, called jobs, need to be scheduled on one or more machines. The outcome is determined by which job is

Best Speed Fit EDF Scheduling for Performance Asymmetric Multiprocessors

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Peng Wu

2017-01-01

Full Text Available In order to improve the performance of a real-time system, asymmetric multiprocessors have been proposed. The benefits of improved system performance and reduced power consumption from such architectures cannot be fully exploited unless suitable task scheduling and task allocation approaches are implemented at the operating system level. Unfortunately, most of the previous research on scheduling algorithms for performance asymmetric multiprocessors is focused on task priority assignment. They simply assign the highest priority task to the fastest processor. In this paper, we propose BSF-EDF (best speed fit for earliest deadline first for performance asymmetric multiprocessor scheduling. This approach chooses a suitable processor rather than the fastest one, when allocating tasks. With this proposed BSF-EDF scheduling, we also derive an effective schedulability test.

Distributing Flexibility to Enhance Robustness in Task Scheduling Problems

NARCIS (Netherlands)

Wilmer, D.; Klos, T.B.; Wilson, M.

2013-01-01

Temporal scheduling problems occur naturally in many diverse application domains such as manufacturing, transportation, health and education. A scheduling problem arises if we have a set of temporal events (or variables) and some constraints on those events, and we have to find a schedule, which is

Designing a fuzzy scheduler for hard real-time systems

Science.gov (United States)

Yen, John; Lee, Jonathan; Pfluger, Nathan; Natarajan, Swami

1992-01-01

In hard real-time systems, tasks have to be performed not only correctly, but also in a timely fashion. If timing constraints are not met, there might be severe consequences. Task scheduling is the most important problem in designing a hard real-time system, because the scheduling algorithm ensures that tasks meet their deadlines. However, the inherent nature of uncertainty in dynamic hard real-time systems increases the problems inherent in scheduling. In an effort to alleviate these problems, we have developed a fuzzy scheduler to facilitate searching for a feasible schedule. A set of fuzzy rules are proposed to guide the search. The situation we are trying to address is the performance of the system when no feasible solution can be found, and therefore, certain tasks will not be executed. We wish to limit the number of important tasks that are not scheduled.

ALGORITHMIC CONSTRUCTION SCHEDULES IN CONDITIONS OF TIMING CONSTRAINTS

Directory of Open Access Journals (Sweden)

Alexey S. Dobrynin

2014-01-01

Full Text Available Tasks of time-schedule construction (JSSP in various fields of human activities have an important theoretical and practical significance. The main feature of these tasks is a timing requirement, describing allowed planning time periods and periods of downtime. This article describes implementation variations of the work scheduling algorithm under timing requirements for the tasks of industrial time-schedules construction, and service activities.

GPScheDVS: A New Paradigm of the Autonomous CPU Speed Control for Commodity-OS-based General-Purpose Mobile Computers with a DVS-friendly Task Scheduling

OpenAIRE

Kim, Sookyoung

2008-01-01

This dissertation studies the problem of increasing battery life-time and reducing CPU heat dissipation without degrading system performance in commodity-OS-based general-purpose (GP) mobile computers using the dynamic voltage scaling (DVS) function of modern CPUs. The dissertation especially focuses on the impact of task scheduling on the effectiveness of DVS in achieving this goal. The task scheduling mechanism used in most contemporary general-purpose operating systems (GPOS) prioritizes t...

Analyzing scheduling in the food-processing industry

DEFF Research Database (Denmark)

Akkerman, Renzo; van Donk, Dirk Pieter

2009-01-01

Production scheduling has been widely studied in several research areas, resulting in a large number of methods, prescriptions, and approaches. However, the impact on scheduling practice seems relatively low. This is also the case in the food-processing industry, where industry......-specific characteristics induce specific and complex scheduling problems. Based on ideas about decomposition of the scheduling task and the production process, we develop an analysis methodology for scheduling problems in food processing. This combines an analysis of structural (technological) elements of the production...... process with an analysis of the tasks of the scheduler. This helps to understand, describe, and structure scheduling problems in food processing, and forms a basis for improving scheduling and applying methods developed in literature. It also helps in evaluating the organisational structures...

Energy-Efficient Scheduling for Hybrid Tasks in Control Devices for the Internet of Things

Science.gov (United States)

Gao, Zhigang; Wu, Yifan; Dai, Guojun; Xia, Haixia

2012-01-01

In control devices for the Internet of Things (IoT), energy is one of the critical restriction factors. Dynamic voltage scaling (DVS) has been proved to be an effective method for reducing the energy consumption of processors. This paper proposes an energy-efficient scheduling algorithm for IoT control devices with hard real-time control tasks (HRCTs) and soft real-time tasks (SRTs). The main contribution of this paper includes two parts. First, it builds the Hybrid tasks with multi-subtasks of different function Weight (HoW) task model for IoT control devices. HoW describes the structure of HRCTs and SRTs, and their properties, e.g., deadlines, execution time, preemption properties, and energy-saving goals, etc. Second, it presents the Hybrid Tasks' Dynamic Voltage Scaling (HTDVS) algorithm. HTDVS first sets the slowdown factors of subtasks while meeting the different real-time requirements of HRCTs and SRTs, and then dynamically reclaims, reserves, and reuses the slack time of the subtasks to meet their ideal energy-saving goals. Experimental results show HTDVS can reduce energy consumption about 10%–80% while meeting the real-time requirements of HRCTs, HRCTs help to reduce the deadline miss ratio (DMR) of systems, and HTDVS has comparable performance with the greedy algorithm and is more favorable to keep the subtasks' ideal speeds. PMID:23112659

A master surgical scheduling approach for cyclic scheduling in operating room departments

NARCIS (Netherlands)

van Oostrum, Jeroen M.; van Houdenhoven, M.; Hurink, Johann L.; Hans, Elias W.; Wullink, Gerhard; Kazemier, G.

This paper addresses the problem of operating room (OR) scheduling at the tactical level of hospital planning and control. Hospitals repetitively construct operating room schedules, which is a time-consuming, tedious, and complex task. The stochasticity of the durations of surgical procedures

Automated Scheduling Via Artificial Intelligence

Science.gov (United States)

Biefeld, Eric W.; Cooper, Lynne P.

1991-01-01

Artificial-intelligence software that automates scheduling developed in Operations Mission Planner (OMP) research project. Software used in both generation of new schedules and modification of existing schedules in view of changes in tasks and/or available resources. Approach based on iterative refinement. Although project focused upon scheduling of operations of scientific instruments and other equipment aboard spacecraft, also applicable to such terrestrial problems as scheduling production in factory.

It Is Not Just about the Schedule: Key Factors in Effective Reference Desk Scheduling and Management

Science.gov (United States)

Sciammarella, Susan; Fernandes, Maria Isabel; McKay, Devin

2008-01-01

Reference desk scheduling is one of the most challenging tasks in the organizational structure of an academic library. The ability to turn this challenge into a workable and effective function lies with the scheduler and indirectly the cooperation of all librarians scheduled for reference desk service. It is the scheduler's sensitivity to such…

Optimization of Hierarchically Scheduled Heterogeneous Embedded Systems

DEFF Research Database (Denmark)

Pop, Traian; Pop, Paul; Eles, Petru

2005-01-01

We present an approach to the analysis and optimization of heterogeneous distributed embedded systems. The systems are heterogeneous not only in terms of hardware components, but also in terms of communication protocols and scheduling policies. When several scheduling policies share a resource......, they are organized in a hierarchy. In this paper, we address design problems that are characteristic to such hierarchically scheduled systems: assignment of scheduling policies to tasks, mapping of tasks to hardware components, and the scheduling of the activities. We present algorithms for solving these problems....... Our heuristics are able to find schedulable implementations under limited resources, achieving an efficient utilization of the system. The developed algorithms are evaluated using extensive experiments and a real-life example....

Range Scheduling Aid (RSA)

Science.gov (United States)

Logan, J. R.; Pulvermacher, M. K.

1991-01-01

Range Scheduling Aid (RSA) is presented in the form of the viewgraphs. The following subject areas are covered: satellite control network; current and new approaches to range scheduling; MITRE tasking; RSA features; RSA display; constraint based analytic capability; RSA architecture; and RSA benefits.

Real-Time Scheduling for Preventing Information Leakage with Preemption Overheads

Directory of Open Access Journals (Sweden)

BAEK, H.

2017-05-01

Full Text Available Real-time systems (RTS are characterized by tasks executing in a timely manner to meet its deadlines as a real-time constraint. Most studies of RTS have focused on these criteria as primary design points. However, recent increases in security threats to various real-time systems have shown that enhanced security support must be included as an important design point, retro-fitting such support to existing systems as necessary. In this paper, we propose a new pre-flush technique referred to as flush task reservation for FP scheduling (FTR-FP to conditionally sanitize the state of resources shared by real-time tasks by invoking a flush task (FT in order to mitigate information leakage/corruption of real-time systems. FTR-FP extends existing works exploiting FTs to be applicable more general scheduling algorithms and security model. We also propose modifications to existing real-time scheduling algorithms to implement a pre-flush technique as a security constraint, and analysis technique to verify schedulability of the real-time scheduling. For better analytic capability, our analysis technique provides a count of the precise number of preemptions that a task experiences offline. Our evaluation results demonstrate that our proposed schedulability analysis improves the performance of existing scheduling algorithms in terms of schedulability and preemption cost.

Energy-Efficient Scheduling for Hybrid Tasks in Control Devices for the Internet of Things

Directory of Open Access Journals (Sweden)

Guojun Dai

2012-08-01

Full Text Available In control devices for the Internet of Things (IoT, energy is one of the critical restriction factors. Dynamic voltage scaling (DVS has been proved to be an effective method for reducing the energy consumption of processors. This paper proposes an energy-efficient scheduling algorithm for IoT control devices with hard real-time control tasks (HRCTs and soft real-time tasks (SRTs. The main contribution of this paper includes two parts. First, it builds the Hybrid tasks with multi-subtasks of different function Weight (HoW task model for IoT control devices. HoW describes the structure of HRCTs and SRTs, and their properties, e.g., deadlines, execution time, preemption properties, and energy-saving goals, etc. Second, it presents the Hybrid Tasks’ Dynamic Voltage Scaling (HTDVS algorithm. HTDVS first sets the slowdown factors of subtasks while meeting the different real-time requirements of HRCTs and SRTs, and then dynamically reclaims, reserves, and reuses the slack time of the subtasks to meet their ideal energy-saving goals. Experimental results show HTDVS can reduce energy consumption about 10%–80% while meeting the real-time requirements of HRCTs, HRCTs help to reduce the deadline miss ratio (DMR of systems, and HTDVS has comparable performance with the greedy algorithm and is more favorable to keep the subtasks’ ideal speeds.

Schedulability of Herschel revisited using statistical model checking

DEFF Research Database (Denmark)

David, Alexandre; Larsen, Kim Guldstrand; Legay, Axel

2015-01-01

-approximation technique. We can safely conclude that the system is schedulable for varying values of BCET. For the cases where deadlines are violated, we use polyhedra to try to confirm the witnesses. Our alternative method to confirm non-schedulability uses statistical model-checking (SMC) to generate counter...... and blocking times of tasks. Consequently, the method may falsely declare deadline violations that will never occur during execution. This paper is a continuation of previous work of the authors in applying extended timed automata model checking (using the tool UPPAAL) to obtain more exact schedulability...... analysis, here in the presence of non-deterministic computation times of tasks given by intervals [BCET,WCET]. Computation intervals with preemptive schedulers make the schedulability analysis of the resulting task model undecidable. Our contribution is to propose a combination of model checking techniques...

Optimizing the Steel Plate Storage Yard Crane Scheduling Problem Using a Two Stage Planning/Scheduling Approach

DEFF Research Database (Denmark)

Hansen, Anders Dohn; Clausen, Jens

This paper presents the Steel Plate Storage Yard Crane Scheduling Problem. The task is to generate a schedule for two gantry cranes sharing tracks. The schedule must comply with a number of constraints and at the same time be cost efficient. We propose some ideas for a two stage planning...

Designing of Vague Logic Based 2-Layered Framework for CPU Scheduler

Directory of Open Access Journals (Sweden)

Supriya Raheja

2016-01-01

Full Text Available Fuzzy based CPU scheduler has become of great interest by operating system because of its ability to handle imprecise information associated with task. This paper introduces an extension to the fuzzy based round robin scheduler to a Vague Logic Based Round Robin (VBRR scheduler. VBRR scheduler works on 2-layered framework. At the first layer, scheduler has a vague inference system which has the ability to handle the impreciseness of task using vague logic. At the second layer, Vague Logic Based Round Robin (VBRR scheduling algorithm works to schedule the tasks. VBRR scheduler has the learning capability based on which scheduler adapts intelligently an optimum length for time quantum. An optimum time quantum reduces the overhead on scheduler by reducing the unnecessary context switches which lead to improve the overall performance of system. The work is simulated using MATLAB and compared with the conventional round robin scheduler and the other two fuzzy based approaches to CPU scheduler. Given simulation analysis and results prove the effectiveness and efficiency of VBRR scheduler.

Analysis and Optimisation of Hierarchically Scheduled Multiprocessor Embedded Systems

DEFF Research Database (Denmark)

Pop, Traian; Pop, Paul; Eles, Petru

2008-01-01

We present an approach to the analysis and optimisation of heterogeneous multiprocessor embedded systems. The systems are heterogeneous not only in terms of hardware components, but also in terms of communication protocols and scheduling policies. When several scheduling policies share a resource......, they are organised in a hierarchy. In this paper, we first develop a holistic scheduling and schedulability analysis that determines the timing properties of a hierarchically scheduled system. Second, we address design problems that are characteristic to such hierarchically scheduled systems: assignment...... of scheduling policies to tasks, mapping of tasks to hardware components, and the scheduling of the activities. We also present several algorithms for solving these problems. Our heuristics are able to find schedulable implementations under limited resources, achieving an efficient utilisation of the system...

Alternative Work Schedules: Definitions

Science.gov (United States)

Journal of the College and University Personnel Association, 1977

1977-01-01

The term "alternative work schedules" encompasses any variation of the requirement that all permanent employees in an organization or one shift of employees adhere to the same five-day, seven-to-eight-hour schedule. This article defines staggered hours, flexible working hours (flexitour and gliding time), compressed work week, the task system, and…

Independent tasks scheduling in cloud computing via improved estimation of distribution algorithm

Science.gov (United States)

Sun, Haisheng; Xu, Rui; Chen, Huaping

2018-04-01

To minimize makespan for scheduling independent tasks in cloud computing, an improved estimation of distribution algorithm (IEDA) is proposed to tackle the investigated problem in this paper. Considering that the problem is concerned with multi-dimensional discrete problems, an improved population-based incremental learning (PBIL) algorithm is applied, which the parameter for each component is independent with other components in PBIL. In order to improve the performance of PBIL, on the one hand, the integer encoding scheme is used and the method of probability calculation of PBIL is improved by using the task average processing time; on the other hand, an effective adaptive learning rate function that related to the number of iterations is constructed to trade off the exploration and exploitation of IEDA. In addition, both enhanced Max-Min and Min-Min algorithms are properly introduced to form two initial individuals. In the proposed IEDA, an improved genetic algorithm (IGA) is applied to generate partial initial population by evolving two initial individuals and the rest of initial individuals are generated at random. Finally, the sampling process is divided into two parts including sampling by probabilistic model and IGA respectively. The experiment results show that the proposed IEDA not only gets better solution, but also has faster convergence speed.

An Integrated Approach to Locality-Conscious Processor Allocation and Scheduling of Mixed-Parallel Applications

Energy Technology Data Exchange (ETDEWEB)

Vydyanathan, Naga; Krishnamoorthy, Sriram; Sabin, Gerald M.; Catalyurek, Umit V.; Kurc, Tahsin; Sadayappan, Ponnuswamy; Saltz, Joel H.

2009-08-01

Complex parallel applications can often be modeled as directed acyclic graphs of coarse-grained application-tasks with dependences. These applications exhibit both task- and data-parallelism, and combining these two (also called mixedparallelism), has been shown to be an effective model for their execution. In this paper, we present an algorithm to compute the appropriate mix of task- and data-parallelism required to minimize the parallel completion time (makespan) of these applications. In other words, our algorithm determines the set of tasks that should be run concurrently and the number of processors to be allocated to each task. The processor allocation and scheduling decisions are made in an integrated manner and are based on several factors such as the structure of the taskgraph, the runtime estimates and scalability characteristics of the tasks and the inter-task data communication volumes. A locality conscious scheduling strategy is used to improve inter-task data reuse. Evaluation through simulations and actual executions of task graphs derived from real applications as well as synthetic graphs shows that our algorithm consistently generates schedules with lower makespan as compared to CPR and CPA, two previously proposed scheduling algorithms. Our algorithm also produces schedules that have lower makespan than pure taskand data-parallel schedules. For task graphs with known optimal schedules or lower bounds on the makespan, our algorithm generates schedules that are closer to the optima than other scheduling approaches.

A Scheduling Algorithm for Cloud Computing System Based on the Driver of Dynamic Essential Path.

Science.gov (United States)

Xie, Zhiqiang; Shao, Xia; Xin, Yu

2016-01-01

To solve the problem of task scheduling in the cloud computing system, this paper proposes a scheduling algorithm for cloud computing based on the driver of dynamic essential path (DDEP). This algorithm applies a predecessor-task layer priority strategy to solve the problem of constraint relations among task nodes. The strategy assigns different priority values to every task node based on the scheduling order of task node as affected by the constraint relations among task nodes, and the task node list is generated by the different priority value. To address the scheduling order problem in which task nodes have the same priority value, the dynamic essential long path strategy is proposed. This strategy computes the dynamic essential path of the pre-scheduling task nodes based on the actual computation cost and communication cost of task node in the scheduling process. The task node that has the longest dynamic essential path is scheduled first as the completion time of task graph is indirectly influenced by the finishing time of task nodes in the longest dynamic essential path. Finally, we demonstrate the proposed algorithm via simulation experiments using Matlab tools. The experimental results indicate that the proposed algorithm can effectively reduce the task Makespan in most cases and meet a high quality performance objective.

A hybrid online scheduling mechanism with revision and progressive techniques for autonomous Earth observation satellite

Science.gov (United States)

Li, Guoliang; Xing, Lining; Chen, Yingwu

2017-11-01

The autonomicity of self-scheduling on Earth observation satellite and the increasing scale of satellite network attract much attention from researchers in the last decades. In reality, the limited onboard computational resource presents challenge for the online scheduling algorithm. This study considered online scheduling problem for a single autonomous Earth observation satellite within satellite network environment. It especially addressed that the urgent tasks arrive stochastically during the scheduling horizon. We described the problem and proposed a hybrid online scheduling mechanism with revision and progressive techniques to solve this problem. The mechanism includes two decision policies, a when-to-schedule policy combining periodic scheduling and critical cumulative number-based event-driven rescheduling, and a how-to-schedule policy combining progressive and revision approaches to accommodate two categories of task: normal tasks and urgent tasks. Thus, we developed two heuristic (re)scheduling algorithms and compared them with other generally used techniques. Computational experiments indicated that the into-scheduling percentage of urgent tasks in the proposed mechanism is much higher than that in periodic scheduling mechanism, and the specific performance is highly dependent on some mechanism-relevant and task-relevant factors. For the online scheduling, the modified weighted shortest imaging time first and dynamic profit system benefit heuristics outperformed the others on total profit and the percentage of successfully scheduled urgent tasks.

A model for generating master surgical schedules to allow cyclic scheduling in operating room departments

NARCIS (Netherlands)

van Oostrum, J.M.; van Houdenhoven, M.; Hurink, Johann L.; Hans, Elias W.; Wullink, Gerhard; Kazemier, G.

2005-01-01

This paper addresses the problem of operating room scheduling at the tactical level of hospital planning and control. Hospitals repetitively construct operating room schedules, which is a time consuming tedious and complex task. The stochasticity of the durations of surgical procedures complicates

Integrated test schedule for buried waste integrated demonstration

International Nuclear Information System (INIS)

Brown, J.T.; McDonald, J.K.

1992-05-01

The Integrated Test Schedule incorporates the various schedules the Buried Waste Integrated Demonstration (BWID) supports into one document. This document contains the Federal Facilities Agreement and Consent Order schedules for the Idaho National Engineering Laboratory, Hanford Reservation, Oak Ridge Reservation, and Fernald Environmental Materials Center. Included in the Integrated Test Schedule is the Buried Waste Integrated Demonstration ''windows of opportunity'' schedule. The ''windows of opportunity'' schedule shows periods of time in which Buried Waste Integrated Demonstration Program-sponsored technology demonstrations could support key decisions in the Federal Facilities Agreement and Consent Order. Schedules for the Buried Waste Integrated Demonstration-sponsored technology task plans are categorized by technology area and divided by current fiscal year and out-year. Total estimated costs for Buried Waste Integrated Demonstration-sponsored Technology Task Plans for FY-92 through FY-97 are $74.756M

An introduction to optimal satellite range scheduling

CERN Document Server

Vázquez Álvarez, Antonio José

2015-01-01

The satellite range scheduling (SRS) problem, an important operations research problem in the aerospace industry consisting of allocating tasks among satellites and Earth-bound objects, is examined in this book. SRS principles and solutions are applicable to many areas, including: Satellite communications, where tasks are communication intervals between sets of satellites and ground stations Earth observation, where tasks are observations of spots on the Earth by satellites Sensor scheduling, where tasks are observations of satellites by sensors on the Earth. This self-contained monograph begins with a structured compendium of the problem and moves on to explain the optimal approach to the solution, which includes aspects from graph theory, set theory, game theory and belief networks. This book is accessible to students, professionals and researchers in a variety of fields, including: operations research, optimization, scheduling theory, dynamic programming and game theory. Taking account of the distributed, ...

Heimdall System for MSSS Sensor Tasking

Science.gov (United States)

Herz, A.; Jones, B.; Herz, E.; George, D.; Axelrad, P.; Gehly, S.

In Norse Mythology, Heimdall uses his foreknowledge and keen eyesight to keep watch for disaster from his home near the Rainbow Bridge. Orbit Logic and the Colorado Center for Astrodynamics Research (CCAR) at the University of Colorado (CU) have developed the Heimdall System to schedule observations of known and uncharacterized objects and search for new objects from the Maui Space Surveillance Site. Heimdall addresses the current need for automated and optimized SSA sensor tasking driven by factors associated with improved space object catalog maintenance. Orbit Logic and CU developed an initial baseline prototype SSA sensor tasking capability for select sensors at the Maui Space Surveillance Site (MSSS) using STK and STK Scheduler, and then added a new Track Prioritization Component for FiSST-inspired computations for predicted Information Gain and Probability of Detection, and a new SSA-specific Figure-of-Merit (FOM) for optimized SSA sensor tasking. While the baseline prototype addresses automation and some of the multi-sensor tasking optimization, the SSA-improved prototype addresses all of the key elements required for improved tasking leading to enhanced object catalog maintenance. The Heimdall proof-of-concept was demonstrated for MSSS SSA sensor tasking for a 24 hour period to attempt observations of all operational satellites in the unclassified NORAD catalog, observe a small set of high priority GEO targets every 30 minutes, make a sky survey of the GEO belt region accessible to MSSS sensors, and observe particular GEO regions that have a high probability of finding new objects with any excess sensor time. This Heimdall prototype software paves the way for further R&D that will integrate this technology into the MSSS systems for operational scheduling, improve the software's scalability, and further tune and enhance schedule optimization. The Heimdall software for SSA sensor tasking provides greatly improved performance over manual tasking, improved

Hierarchical Scheduling Framework Based on Compositional Analysis Using Uppaal

DEFF Research Database (Denmark)

Boudjadar, Jalil; David, Alexandre; Kim, Jin Hyun

2014-01-01

This paper introduces a reconfigurable compositional scheduling framework, in which the hierarchical structure, the scheduling policies, the concrete task behavior and the shared resources can all be reconfigured. The behavior of each periodic preemptive task is given as a list of timed actions, ...

Scheduling with time-dependent execution times

NARCIS (Netherlands)

Woeginger, G.J.

1995-01-01

We consider systems of tasks where the task execution times are time-dependent and where all tasks have some common deadline. We describe how to compute in polynomial time a schedule that minimizes the number of late tasks. This answers a question raised in a recent paper by Ho, Leung and Wei.

Artificial intelligence for the CTA Observatory scheduler

Science.gov (United States)

Colomé, Josep; Colomer, Pau; Campreciós, Jordi; Coiffard, Thierry; de Oña, Emma; Pedaletti, Giovanna; Torres, Diego F.; Garcia-Piquer, Alvaro

2014-08-01

The Cherenkov Telescope Array (CTA) project will be the next generation ground-based very high energy gamma-ray instrument. The success of the precursor projects (i.e., HESS, MAGIC, VERITAS) motivated the construction of this large infrastructure that is included in the roadmap of the ESFRI projects since 2008. CTA is planned to start the construction phase in 2015 and will consist of two arrays of Cherenkov telescopes operated as a proposal-driven open observatory. Two sites are foreseen at the southern and northern hemispheres. The CTA observatory will handle several observation modes and will have to operate tens of telescopes with a highly efficient and reliable control. Thus, the CTA planning tool is a key element in the control layer for the optimization of the observatory time. The main purpose of the scheduler for CTA is the allocation of multiple tasks to one single array or to multiple sub-arrays of telescopes, while maximizing the scientific return of the facility and minimizing the operational costs. The scheduler considers long- and short-term varying conditions to optimize the prioritization of tasks. A short-term scheduler provides the system with the capability to adapt, in almost real-time, the selected task to the varying execution constraints (i.e., Targets of Opportunity, health or status of the system components, environment conditions). The scheduling procedure ensures that long-term planning decisions are correctly transferred to the short-term prioritization process for a suitable selection of the next task to execute on the array. In this contribution we present the constraints to CTA task scheduling that helped classifying it as a Flexible Job-Shop Problem case and finding its optimal solution based on Artificial Intelligence techniques. We describe the scheduler prototype that uses a Guarded Discrete Stochastic Neural Network (GDSN), for an easy representation of the possible long- and short-term planning solutions, and Constraint

Analysis of Issues for Project Scheduling by Multiple, Dispersed Schedulers (distributed Scheduling) and Requirements for Manual Protocols and Computer-based Support

Science.gov (United States)

Richards, Stephen F.

1991-01-01

Although computerized operations have significant gains realized in many areas, one area, scheduling, has enjoyed few benefits from automation. The traditional methods of industrial engineering and operations research have not proven robust enough to handle the complexities associated with the scheduling of realistic problems. To address this need, NASA has developed the computer-aided scheduling system (COMPASS), a sophisticated, interactive scheduling tool that is in wide-spread use within NASA and the contractor community. Therefore, COMPASS provides no explicit support for the large class of problems in which several people, perhaps at various locations, build separate schedules that share a common pool of resources. This research examines the issue of distributing scheduling, as applied to application domains characterized by the partial ordering of tasks, limited resources, and time restrictions. The focus of this research is on identifying issues related to distributed scheduling, locating applicable problem domains within NASA, and suggesting areas for ongoing research. The issues that this research identifies are goals, rescheduling requirements, database support, the need for communication and coordination among individual schedulers, the potential for expert system support for scheduling, and the possibility of integrating artificially intelligent schedulers into a network of human schedulers.

OPTIMIZED PARTICLE SWARM OPTIMIZATION BASED DEADLINE CONSTRAINED TASK SCHEDULING IN HYBRID CLOUD

Directory of Open Access Journals (Sweden)

Dhananjay Kumar

2016-01-01

Full Text Available Cloud Computing is a dominant way of sharing of computing resources that can be configured and provisioned easily. Task scheduling in Hybrid cloud is a challenge as it suffers from producing the best QoS (Quality of Service when there is a high demand. In this paper a new resource allocation algorithm, to find the best External Cloud provider when the intermediate provider’s resources aren’t enough to satisfy the customer’s demand is proposed. The proposed algorithm called Optimized Particle Swarm Optimization (OPSO combines the two metaheuristic algorithms namely Particle Swarm Optimization and Ant Colony Optimization (ACO. These metaheuristic algorithms are used for the purpose of optimization in the search space of the required solution, to find the best resource from the pool of resources and to obtain maximum profit even when the number of tasks submitted for execution is very high. This optimization is performed to allocate job requests to internal and external cloud providers to obtain maximum profit. It helps to improve the system performance by improving the CPU utilization, and handle multiple requests at the same time. The simulation result shows that an OPSO yields 0.1% - 5% profit to the intermediate cloud provider compared with standard PSO and ACO algorithms and it also increases the CPU utilization by 0.1%.

Multiresource allocation and scheduling for periodic soft real-time applications

Science.gov (United States)

Gopalan, Kartik; Chiueh, Tzi-cker

2001-12-01

Real-time applications that utilize multiple system resources, such as CPU, disks, and network links, require coordinated scheduling of these resources in order to meet their end-to-end performance requirements. Most state-of-the-art operating systems support independent resource allocation and deadline-driven scheduling but lack coordination among multiple heterogeneous resources. This paper describes the design and implementation of an Integrated Real-time Resource Scheduler (IRS) that performs coordinated allocation and scheduling of multiple heterogeneous resources on the same machine for periodic soft real-time application. The principal feature of IRS is a heuristic multi-resource allocation algorithm that reserves multiple resources for real-time applications in a manner that can maximize the number of applications admitted into the system in the long run. At run-time, a global scheduler dispatches the tasks of the soft real-time application to individual resource schedulers according to the precedence constraints between tasks. The individual resource schedulers, which could be any deadline based schedulers, can make scheduling decisions locally and yet collectively satisfy a real-time application's performance requirements. The tightness of overall timing guarantees is ultimately determined by the properties of individual resource schedulers. However, IRS maximizes overall system resource utilization efficiency by coordinating deadline assignment across multiple tasks in a soft real-time application.

Limited Preemptive Scheduling in Real-time Systems

OpenAIRE

Thekkilakattil, Abhilash

2016-01-01

Preemptive and non-preemptive scheduling paradigms typically introduce undesirable side effects when scheduling real-time tasks, mainly in the form of preemption overheads and blocking, that potentially compromise timeliness guarantees. The high preemption overheads in preemptive real-time scheduling may imply high resource utilization, often requiring significant over-provisioning, e.g., pessimistic Worst Case Execution Time (WCET) approximations. Non-preemptive scheduling, on the other hand...

Designing of vague logic based multilevel feedback queue scheduler

Directory of Open Access Journals (Sweden)

Supriya Raheja

2016-03-01

Full Text Available Multilevel feedback queue scheduler suffers from major issues of scheduling such as starvation for long tasks, fixed number of queues, and static length of time quantum in each queue. These factors directly affect the performance of the scheduler. At many times impreciseness exists in attributes of tasks which make the performance even worse. In this paper, our intent is to improve the performance by providing a solution to these issues. We design a multilevel feedback queue scheduler using a vague set which we call as VMLFQ scheduler. VMLFQ scheduler intelligently handles the impreciseness and defines the optimum number of queues as well as the optimal size of time quantum for each queue. It also resolves the problem of starvation. This paper simulates and analyzes the performance of VMLFQ scheduler with the other multilevel feedback queue techniques using MatLab.

Constraint-based scheduling

Science.gov (United States)

Zweben, Monte

1993-01-01

The GERRY scheduling system developed by NASA Ames with assistance from the Lockheed Space Operations Company, and the Lockheed Artificial Intelligence Center, uses a method called constraint-based iterative repair. Using this technique, one encodes both hard rules and preference criteria into data structures called constraints. GERRY repeatedly attempts to improve schedules by seeking repairs for violated constraints. The system provides a general scheduling framework which is being tested on two NASA applications. The larger of the two is the Space Shuttle Ground Processing problem which entails the scheduling of all the inspection, repair, and maintenance tasks required to prepare the orbiter for flight. The other application involves power allocation for the NASA Ames wind tunnels. Here the system will be used to schedule wind tunnel tests with the goal of minimizing power costs. In this paper, we describe the GERRY system and its application to the Space Shuttle problem. We also speculate as to how the system would be used for manufacturing, transportation, and military problems.

A General State-Space Formulation for Online Scheduling

Directory of Open Access Journals (Sweden)

Dhruv Gupta

2017-11-01

Full Text Available We present a generalized state-space model formulation particularly motivated by an online scheduling perspective, which allows modeling (1 task-delays and unit breakdowns; (2 fractional delays and unit downtimes, when using discrete-time grid; (3 variable batch-sizes; (4 robust scheduling through the use of conservative yield estimates and processing times; (5 feedback on task-yield estimates before the task finishes; (6 task termination during its execution; (7 post-production storage of material in unit; and (8 unit capacity degradation and maintenance. Through these proposed generalizations, we enable a natural way to handle routinely encountered disturbances and a rich set of corresponding counter-decisions. Thereby, greatly simplifying and extending the possible application of mathematical programming based online scheduling solutions to diverse application settings. Finally, we demonstrate the effectiveness of this model on a case study from the field of bio-manufacturing.

Energy-Aware Real-Time Task Scheduling for Heterogeneous Multiprocessors with Particle Swarm Optimization Algorithm

Directory of Open Access Journals (Sweden)

Weizhe Zhang

2014-01-01

Full Text Available Energy consumption in computer systems has become a more and more important issue. High energy consumption has already damaged the environment to some extent, especially in heterogeneous multiprocessors. In this paper, we first formulate and describe the energy-aware real-time task scheduling problem in heterogeneous multiprocessors. Then we propose a particle swarm optimization (PSO based algorithm, which can successfully reduce the energy cost and the time for searching feasible solutions. Experimental results show that the PSO-based energy-aware metaheuristic uses 40%–50% less energy than the GA-based and SFLA-based algorithms and spends 10% less time than the SFLA-based algorithm in finding the solutions. Besides, it can also find 19% more feasible solutions than the SFLA-based algorithm.

Multi-objective Mobile Robot Scheduling Problem with Dynamic Time Windows

DEFF Research Database (Denmark)

Dang, Vinh Quang; Nielsen, Izabela Ewa; Steger-Jensen, Kenn

2012-01-01

This paper deals with the problem of scheduling feeding tasks of a single mobile robot which has capability of supplying parts to feeders on pro-duction lines. The performance criterion is to minimize the total traveling time of the robot and the total tardiness of the feeding tasks being scheduled...

Kokkos' Task DAG Capabilities.

Energy Technology Data Exchange (ETDEWEB)

Edwards, Harold C. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Ibanez, Daniel Alejandro [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-09-01

This report documents the ASC/ATDM Kokkos deliverable "Production Portable Dy- namic Task DAG Capability." This capability enables applications to create and execute a dynamic task DAG ; a collection of heterogeneous computational tasks with a directed acyclic graph (DAG) of "execute after" dependencies where tasks and their dependencies are dynamically created and destroyed as tasks execute. The Kokkos task scheduler executes the dynamic task DAG on the target execution resource; e.g. a multicore CPU, a manycore CPU such as Intel's Knights Landing (KNL), or an NVIDIA GPU. Several major technical challenges had to be addressed during development of Kokkos' Task DAG capability: (1) portability to a GPU with it's simplified hardware and micro- runtime, (2) thread-scalable memory allocation and deallocation from a bounded pool of memory, (3) thread-scalable scheduler for dynamic task DAG, (4) usability by applications.

Resource allocation in IT projects: using schedule optimization

Directory of Open Access Journals (Sweden)

Michael Chilton

2014-01-01

Full Text Available Resource allocation is the process of assigning resources to tasks throughout the life of a project. Despite sophisticated software packages devoted to keeping track of tasks, resources and resource assignments, it is often the case that project managers find some resources over-allocated and therefore unable to complete the assigned work in the allotted amount of time. Most scheduling software has provisions for leveling resources, but the techniques for doing so simply add time to the schedule and may cause delays in tasks that are critical to the project in meeting deadlines. This paper presents a software application that ensures that resources are properly balanced at the beginning of the project and eliminates the situation in which resources become over-allocated. It can be used in a multi-project environment and reused throughout the project as tasks, resource assignments and availability, and the project scope change. The application utilizes the bounded enumeration technique to formulate an optimal schedule for which both the task sequence and resource availability are taken into account. It is run on a database server to reduce the running time and make it a viable application for practitioners.

Utilization Bound of Non-preemptive Fixed Priority Schedulers

Science.gov (United States)

Park, Moonju; Chae, Jinseok

It is known that the schedulability of a non-preemptive task set with fixed priority can be determined in pseudo-polynomial time. However, since Rate Monotonic scheduling is not optimal for non-preemptive scheduling, the applicability of existing polynomial time tests that provide sufficient schedulability conditions, such as Liu and Layland's bound, is limited. This letter proposes a new sufficient condition for non-preemptive fixed priority scheduling that can be used for any fixed priority assignment scheme. It is also shown that the proposed schedulability test has a tighter utilization bound than existing test methods.

Toward an Autonomous Telescope Network: the TBT Scheduler

Science.gov (United States)

Racero, E.; Ibarra, A.; Ocaña, F.; de Lis, S. B.; Ponz, J. D.; Castillo, M.; Sánchez-Portal, M.

2015-09-01

Within the ESA SSA program, it is foreseen to deploy several robotic telescopes to provide surveillance and tracking services for hazardous objects. The TBT project will procure a validation platform for an autonomous optical observing system in a realistic scenario, consisting of two telescopes located in Spain and Australia, to collect representative test data for precursor SSA services. In this context, the planning and scheduling of the night consists of two software modules, the TBT Scheduler, that will allow the manual and autonomous planning of the night, and the control of the real-time response of the system, done by the RTS2 internal scheduler. The TBT Scheduler allocates tasks for both telescopes without human intervention. Every night it takes all the inputs needed and prepares the schedule following some predefined rules. The main purpose of the scheduler is the distribution of the time for follow-up of recently discovered targets and surveys. The TBT Scheduler considers the overall performance of the system, and combine follow-up with a priori survey strategies for both kind of objects. The strategy is defined according to the expected combined performance for both systems the upcoming night (weather, sky brightness, object accessibility and priority). Therefore, TBT Scheduler defines the global approach for the network and relies on the RTS2 internal scheduler for the final detailed distribution of tasks at each sensor.

WCET Analysis for Preemptive Scheduling

OpenAIRE

Altmeyer, Sebastian; Gebhard, Gernot

2008-01-01

Hard real-time systems induce strict constraints on the timing of the task set. Validation of these timing constraints is thus a major challenge during the design of such a system. Whereas the derivation of timing guarantees must already be considered complex if tasks are running to completion, it gets even more complex if tasks are scheduled preemptively -- especially due to caches, deployed to improve the average performance. In this paper we propose a new method to compu...

Improved SIRAP analysis for synchronization in hierarchical scheduled real-time systems

NARCIS (Netherlands)

Behnam, M.; Bril, R.J.; Nolte, T.

2009-01-01

We present our ongoing work on synchronization in hierarchical scheduled real-time systems, where tasks are scheduled using fixed-priority pre-emptive scheduling. In this paper, we show that the original local schedulability analysis of the synchronization protocol SIRAP [4] is very pessimistic when

Time-critical multirate scheduling using contemporary real-time operating system services

Science.gov (United States)

Eckhardt, D. E., Jr.

1983-01-01

Although real-time operating systems provide many of the task control services necessary to process time-critical applications (i.e., applications with fixed, invariant deadlines), it may still be necessary to provide a scheduling algorithm at a level above the operating system in order to coordinate a set of synchronized, time-critical tasks executing at different cyclic rates. The scheduling requirements for such applications and develops scheduling algorithms using services provided by contemporary real-time operating systems.

Energy-driven scheduling algorithm for nanosatellite energy harvesting maximization

Science.gov (United States)

Slongo, L. K.; Martínez, S. V.; Eiterer, B. V. B.; Pereira, T. G.; Bezerra, E. A.; Paiva, K. V.

2018-06-01

The number of tasks that a satellite may execute in orbit is strongly related to the amount of energy its Electrical Power System (EPS) is able to harvest and to store. The manner the stored energy is distributed within the satellite has also a great impact on the CubeSat's overall efficiency. Most CubeSat's EPS do not prioritize energy constraints in their formulation. Unlike that, this work proposes an innovative energy-driven scheduling algorithm based on energy harvesting maximization policy. The energy harvesting circuit is mathematically modeled and the solar panel I-V curves are presented for different temperature and irradiance levels. Considering the models and simulations, the scheduling algorithm is designed to keep solar panels working close to their maximum power point by triggering tasks in the appropriate form. Tasks execution affects battery voltage, which is coupled to the solar panels through a protection circuit. A software based Perturb and Observe strategy allows defining the tasks to be triggered. The scheduling algorithm is tested in FloripaSat, which is an 1U CubeSat. A test apparatus is proposed to emulate solar irradiance variation, considering the satellite movement around the Earth. Tests have been conducted to show that the scheduling algorithm improves the CubeSat energy harvesting capability by 4.48% in a three orbit experiment and up to 8.46% in a single orbit cycle in comparison with the CubeSat operating without the scheduling algorithm.

Influence of a scheduled-waiting task on EMG reactivity and oral habits among facial pain patients and no-pain controls.

Science.gov (United States)

Nicholson, R A; Townsend, D R; Gramling, S E

2000-12-01

Recent research has strongly implicated the role of psychological stress in the development of temporomandibular disorders (TMD). It is widely reported that oral habits (e.g., teeth grinding) probably provide a behavioral link between stress and the development of TMD symptomatology. Extrapolation of research in the field of adjunctive behavior to the TMD disorders suggests that oral behaviors may develop conjointly with fixed-time (FT) stimulus presentation. The current experiment extended previous research examining this possibility by assessing the influence of experimental stress on masseter EMG and oral habits among persons who met broadband criteria for TMD and no-pain controls. Oral habit activity was assessed via self-report questionnaire whereas masseter muscle activity was measured continuously via electromyography across four phases (Adaptation, Free-Play, Scheduled-Play, Recovery). The Scheduled-Play phase was designed as a stress-reactivity task that included an FT schedule. Results indicated that, consistent with the stress-reactivity model, the Scheduled-Play phase resulted in a significant increase in masseter EMG levels relative to Free-Play and Adaptation, and that this effect was significantly larger for the TMD group relative to controls. The results suggest an adjunctive behavior effect although the effect was not specific to those with facial pain. Oral habit data showed a significant phase effect with oral habits that was significantly higher during the Scheduled-Play phase relative to Adaptation. The findings are the impetus for further study regarding the mechanisms whereby oral habits are developed and maintained despite their painful consequences.

Crane Scheduling on a Plate Storage

DEFF Research Database (Denmark)

Hansen, Jesper

2002-01-01

OSS produces the worlds largest container ships. The first process of producing the steel ships is handling arrival and storage of steel plates until they are needed in production. Two gantry cranes carry out this task. The planning task is now to create a schedule of movements for the 2 cranes...

Fixed-Time Schedule Effects in Combination with Response-Dependent Schedules

Science.gov (United States)

Borrero, John C.; Bartels-Meints, Jamie A.; Sy, Jolene R.; Francisco, Monica T.

2011-01-01

We evaluated the effects of fixed-interval (FI), fixed-time (FT), and conjoint (combined) FI FT reinforcement schedules on the responding of 3 adults who had been diagnosed with schizophrenia. Responding on vocational tasks decreased for 2 of 3 participants under FT alone relative to FI alone. Responding under FI FT resulted in response…

An Experimental Evaluation of Real-Time DVFS Scheduling Algorithms

OpenAIRE

Saha, Sonal

2011-01-01

Dynamic voltage and frequency scaling (DVFS) is an extensively studied energy manage- ment technique, which aims to reduce the energy consumption of computing platforms by dynamically scaling the CPU frequency. Real-Time DVFS (RT-DVFS) is a branch of DVFS, which reduces CPU energy consumption through DVFS, while at the same time ensures that task time constraints are satisfied by constructing appropriate real-time task schedules. The literature presents numerous RT-DVFS schedul...

A Review Of Fault Tolerant Scheduling In Multicore Systems

Directory of Open Access Journals (Sweden)

Shefali Malhotra

2015-05-01

Full Text Available Abstract In this paper we have discussed about various fault tolerant task scheduling algorithm for multi core system based on hardware and software. Hardware based algorithm which is blend of Triple Modulo Redundancy and Double Modulo Redundancy in which Agricultural Vulnerability Factor is considered while deciding the scheduling other than EDF and LLF scheduling algorithms. In most of the real time system the dominant part is shared memory.Low overhead software based fault tolerance approach can be implemented at user-space level so that it does not require any changes at application level. Here redundant multi-threaded processes are used. Using those processes we can detect soft errors and recover from them. This method gives low overhead fast error detection and recovery mechanism. The overhead incurred by this method ranges from 0 to 18 for selected benchmarks. Hybrid Scheduling Method is another scheduling approach for real time systems. Dynamic fault tolerant scheduling gives high feasibility rate whereas task criticality is used to select the type of fault recovery method in order to tolerate the maximum number of faults.

A Novel Algorithm of Quantum Random Walk in Server Traffic Control and Task Scheduling

Directory of Open Access Journals (Sweden)

Dong Yumin

2014-01-01

Full Text Available A quantum random walk optimization model and algorithm in network cluster server traffic control and task scheduling is proposed. In order to solve the problem of server load balancing, we research and discuss the distribution theory of energy field in quantum mechanics and apply it to data clustering. We introduce the method of random walk and illuminate what the quantum random walk is. Here, we mainly research the standard model of one-dimensional quantum random walk. For the data clustering problem of high dimensional space, we can decompose one m-dimensional quantum random walk into m one-dimensional quantum random walk. In the end of the paper, we compare the quantum random walk optimization method with GA (genetic algorithm, ACO (ant colony optimization, and SAA (simulated annealing algorithm. In the same time, we prove its validity and rationality by the experiment of analog and simulation.

CellSs: Scheduling Techniques to Better Exploit Memory Hierarchy

Directory of Open Access Journals (Sweden)

Pieter Bellens

2009-01-01

Full Text Available Cell Superscalar's (CellSs main goal is to provide a simple, flexible and easy programming approach for the Cell Broadband Engine (Cell/B.E. that automatically exploits the inherent concurrency of the applications at a task level. The CellSs environment is based on a source-to-source compiler that translates annotated C or Fortran code and a runtime library tailored for the Cell/B.E. that takes care of the concurrent execution of the application. The first efforts for task scheduling in CellSs derived from very simple heuristics. This paper presents new scheduling techniques that have been developed for CellSs for the purpose of improving an application's performance. Additionally, the design of a new scheduling algorithm is detailed and the algorithm evaluated. The CellSs scheduler takes an extension of the memory hierarchy for Cell/B.E. into account, with a cache memory shared between the SPEs. All new scheduling practices have been evaluated showing better behavior of our system.

Individual differences in strategic flight management and scheduling

Science.gov (United States)

Wickens, Christopher D.; Raby, Mireille

1991-01-01

A group of 30 instrument-rated pilots was made to fly simulator approaches to three airports under conditions of low, medium, and high workload conditions. An analysis is presently conducted of the difference in discrete task scheduling between the group of 10 highest and 10 lowest performing pilots in the sample; this categorization was based on the mean of various flight-profile measures. The two groups were found to differ from each other only in terms of the time when specific events were conducted, and of the optimality of scheduling for certain high-priority tasks. These results are assessed in view of the relative independence of task-management skills from aircraft-control skills.

A Comparison between Fixed Priority and EDF Scheduling accounting for Cache Related Pre-emption Delays

Directory of Open Access Journals (Sweden)

Will Lunniss

2014-04-01

Full Text Available In multitasking real-time systems, the choice of scheduling algorithm is an important factor to ensure that response time requirements are met while maximising limited system resources. Two popular scheduling algorithms include fixed priority (FP and earliest deadline first (EDF. While they have been studied in great detail before, they have not been compared when taking into account cache related pre-emption delays (CRPD. Memory and cache are split into a number of blocks containing instructions and data. During a pre-emption, cache blocks from the pre-empting task can evict those of the pre-empted task. When the pre-empted task is resumed, if it then has to re-load the evicted blocks, CRPD are introduced which then affect the schedulability of the task. In this paper we compare FP and EDF scheduling algorithms in the presence of CRPD using the state-of-the-art CRPD analysis. We find that when CRPD is accounted for, the performance gains offered by EDF over FP, while still notable, are diminished. Furthermore, we find that under scenarios that cause relatively high CRPD, task layout optimisation techniques can be applied to allow FP to schedule tasksets at a similar processor utilisation to EDF. Thus making the choice of the task layout in memory as important as the choice of scheduling algorithm. This is very relevant for industry, as it is much cheaper and simpler to adjust the task layout through the linker than it is to switch the scheduling algorithm.

Application Of The Work Breakdown Structure In Determining Cost Buffers In Construction Schedules

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Połoński M.

2015-03-01

Full Text Available The paper presents methods of determining the location of cost buffers and corresponding contingency costs in the CPM schedule based on its work breakdown structure. Application of correctly located cost buffers with appropriately established reserve costs is justified by the common overrunning of scheduled costs in construction projects. Interpolated cost buffers (CB as separate tasks have been combined with relevant summary tasks by the start–to–start (SS relationship, whereas the time of their execution has been dynamically connected with the time of accomplishment of particular summary tasks using the “paste connection” option. Besides cost buffers linked with the group of tasks assigned to summary tasks, a definition of the cost buffer for the entire project (PCB has been proposed, i.e. as one initial task of the entire project. Contingency costs corresponding to these buffers, depending on the data that the planner has at his disposal, can be determined using different methods, but always depend on the costs of all tasks protected by each buffer. The paper presents an exemplary schedule for a facility and the method of determining locations and cost for buffers CB and PCB, as well as their influence on the course of the curve illustrating the budgeted cost of work scheduled (BCWS. The proposed solution has been adjusted and presented with consideration of the possibilities created by the scheduling software MS Project, though its general assumptions may be implemented with application of other similar specialist tools.

Chaotic Multiobjective Evolutionary Algorithm Based on Decomposition for Test Task Scheduling Problem

Directory of Open Access Journals (Sweden)

Hui Lu

2014-01-01

Full Text Available Test task scheduling problem (TTSP is a complex optimization problem and has many local optima. In this paper, a hybrid chaotic multiobjective evolutionary algorithm based on decomposition (CMOEA/D is presented to avoid becoming trapped in local optima and to obtain high quality solutions. First, we propose an improving integrated encoding scheme (IES to increase the efficiency. Then ten chaotic maps are applied into the multiobjective evolutionary algorithm based on decomposition (MOEA/D in three phases, that is, initial population and crossover and mutation operators. To identify a good approach for hybrid MOEA/D and chaos and indicate the effectiveness of the improving IES several experiments are performed. The Pareto front and the statistical results demonstrate that different chaotic maps in different phases have different effects for solving the TTSP especially the circle map and ICMIC map. The similarity degree of distribution between chaotic maps and the problem is a very essential factor for the application of chaotic maps. In addition, the experiments of comparisons of CMOEA/D and variable neighborhood MOEA/D (VNM indicate that our algorithm has the best performance in solving the TTSP.

Dynamic Scheduling for Cloud Reliability using Transportation Problem

OpenAIRE

P. Balasubramanie; S. K. Senthil Kumar

2012-01-01

Problem statement: Cloud is purely a dynamic environment and the existing task scheduling algorithms are mostly static and considered various parameters like time, cost, make span, speed, scalability, throughput, resource utilization, scheduling success rate and so on. Available scheduling algorithms are mostly heuristic in nature and more complex, time consuming and does not consider reliability and availability of the cloud computing environment. Therefore there is a need to implement a sch...

Neural Feedback Scheduling of Real-Time Control Tasks

OpenAIRE

Xia, Feng; Tian, Yu-Chu; Sun, Youxian; Dong, Jinxiang

2008-01-01

Many embedded real-time control systems suffer from resource constraints and dynamic workload variations. Although optimal feedback scheduling schemes are in principle capable of maximizing the overall control performance of multitasking control systems, most of them induce excessively large computational overheads associated with the mathematical optimization routines involved and hence are not directly applicable to practical systems. To optimize the overall control performance while minimi...

Schedulability using native non-preemptive groups on an AUTOSAR/OSEK platform

NARCIS (Netherlands)

Hatvani, L.; Bril, R.J.

To combine the relative strengths of fully preemptive and non-preemptive fixed priority scheduling, we can use limited preemptive scheduling methods. One such method is fixed-priority threshold scheduling (FPTS). This approach defines dual priorities for every task, a priority assigned to the

Elastic Scheduling of Scientific Workflows under Deadline Constraints in Cloud Computing Environments

Directory of Open Access Journals (Sweden)

Nazia Anwar

2018-01-01

Full Text Available Scientific workflow applications are collections of several structured activities and fine-grained computational tasks. Scientific workflow scheduling in cloud computing is a challenging research topic due to its distinctive features. In cloud environments, it has become critical to perform efficient task scheduling resulting in reduced scheduling overhead, minimized cost and maximized resource utilization while still meeting the user-specified overall deadline. This paper proposes a strategy, Dynamic Scheduling of Bag of Tasks based workflows (DSB, for scheduling scientific workflows with the aim to minimize financial cost of leasing Virtual Machines (VMs under a user-defined deadline constraint. The proposed model groups the workflow into Bag of Tasks (BoTs based on data dependency and priority constraints and thereafter optimizes the allocation and scheduling of BoTs on elastic, heterogeneous and dynamically provisioned cloud resources called VMs in order to attain the proposed method’s objectives. The proposed approach considers pay-as-you-go Infrastructure as a Service (IaaS clouds having inherent features such as elasticity, abundance, heterogeneity and VM provisioning delays. A trace-based simulation using benchmark scientific workflows representing real world applications, demonstrates a significant reduction in workflow computation cost while the workflow deadline is met. The results validate that the proposed model produces better success rates to meet deadlines and cost efficiencies in comparison to adapted state-of-the-art algorithms for similar problems.

Schedule-Aware Workflow Management Systems

Science.gov (United States)

Mans, Ronny S.; Russell, Nick C.; van der Aalst, Wil M. P.; Moleman, Arnold J.; Bakker, Piet J. M.

Contemporary workflow management systems offer work-items to users through specific work-lists. Users select the work-items they will perform without having a specific schedule in mind. However, in many environments work needs to be scheduled and performed at particular times. For example, in hospitals many work-items are linked to appointments, e.g., a doctor cannot perform surgery without reserving an operating theater and making sure that the patient is present. One of the problems when applying workflow technology in such domains is the lack of calendar-based scheduling support. In this paper, we present an approach that supports the seamless integration of unscheduled (flow) and scheduled (schedule) tasks. Using CPN Tools we have developed a specification and simulation model for schedule-aware workflow management systems. Based on this a system has been realized that uses YAWL, Microsoft Exchange Server 2007, Outlook, and a dedicated scheduling service. The approach is illustrated using a real-life case study at the AMC hospital in the Netherlands. In addition, we elaborate on the experiences obtained when developing and implementing a system of this scale using formal techniques.

Low-Energy Real-Time OS Using Voltage Scheduling Algorithm for Variable Voltage Processors

OpenAIRE

Okuma, Takanori; Yasuura, Hiroto

2001-01-01

This paper presents a real-time OS based on $ mu $ITRON using proposed voltage scheduling algorithm for variable voltage processors which can vary supply voltage dynamically. The proposed voltage scheduling algorithms assign voltage level for each task dynamically in order to minimize energy consumption under timing constraints. Using the presented real-time OS, running tasks with low supply voltage leads to drastic energy reduction. In addition, the presented voltage scheduling algorithm is ...

A meta-heuristic method for solving scheduling problem: crow search algorithm

Science.gov (United States)

Adhi, Antono; Santosa, Budi; Siswanto, Nurhadi

2018-04-01

Scheduling is one of the most important processes in an industry both in manufacturingand services. The scheduling process is the process of selecting resources to perform an operation on tasks. Resources can be machines, peoples, tasks, jobs or operations.. The selection of optimum sequence of jobs from a permutation is an essential issue in every research in scheduling problem. Optimum sequence becomes optimum solution to resolve scheduling problem. Scheduling problem becomes NP-hard problem since the number of job in the sequence is more than normal number can be processed by exact algorithm. In order to obtain optimum results, it needs a method with capability to solve complex scheduling problems in an acceptable time. Meta-heuristic is a method usually used to solve scheduling problem. The recently published method called Crow Search Algorithm (CSA) is adopted in this research to solve scheduling problem. CSA is an evolutionary meta-heuristic method which is based on the behavior in flocks of crow. The calculation result of CSA for solving scheduling problem is compared with other algorithms. From the comparison, it is found that CSA has better performance in term of optimum solution and time calculation than other algorithms.

Multiprocessor Real-Time Scheduling with Hierarchical Processor Affinities

OpenAIRE

Bonifaci , Vincenzo; Brandenburg , Björn; D'Angelo , Gianlorenzo; Marchetti-Spaccamela , Alberto

2016-01-01

International audience; Many multiprocessor real-time operating systems offer the possibility to restrict the migrations of any task to a specified subset of processors by setting affinity masks. A notion of " strong arbitrary processor affinity scheduling " (strong APA scheduling) has been proposed; this notion avoids schedulability losses due to overly simple implementations of processor affinities. Due to potential overheads, strong APA has not been implemented so far in a real-time operat...

KASS v.2.2. scheduling software for construction

OpenAIRE

Krzemiński Michał

2016-01-01

The paper presents fourth version of specialist useful software in scheduling KASS v.2.2 (Algorithm Scheduling Krzeminski System). KASS software is designed for construction scheduling, specially form flow shop models. The program is being dedicated closely for the purposes of the construction. In distinguishing to other used programs in tasks of this type operational research criteria were designed closely with the thought about construction works and about the specificity of the building pr...

A comparative critical analysis of modern task-parallel runtimes.

Energy Technology Data Exchange (ETDEWEB)

Wheeler, Kyle Bruce; Stark, Dylan; Murphy, Richard C.

2012-12-01

The rise in node-level parallelism has increased interest in task-based parallel runtimes for a wide array of application areas. Applications have a wide variety of task spawning patterns which frequently change during the course of application execution, based on the algorithm or solver kernel in use. Task scheduling and load balance regimes, however, are often highly optimized for specific patterns. This paper uses four basic task spawning patterns to quantify the impact of specific scheduling policy decisions on execution time. We compare the behavior of six publicly available tasking runtimes: Intel Cilk, Intel Threading Building Blocks (TBB), Intel OpenMP, GCC OpenMP, Qthreads, and High Performance ParalleX (HPX). With the exception of Qthreads, the runtimes prove to have schedulers that are highly sensitive to application structure. No runtime is able to provide the best performance in all cases, and those that do provide the best performance in some cases, unfortunately, provide extremely poor performance when application structure does not match the schedulers assumptions.

DLTAP: A Network-efficient Scheduling Method for Distributed Deep Learning Workload in Containerized Cluster Environment

Directory of Open Access Journals (Sweden)

Qiao Wei

2017-01-01

Full Text Available Deep neural networks (DNNs have recently yielded strong results on a range of applications. Training these DNNs using a cluster of commodity machines is a promising approach since training is time consuming and compute-intensive. Furthermore, putting DNN tasks into containers of clusters would enable broader and easier deployment of DNN-based algorithms. Toward this end, this paper addresses the problem of scheduling DNN tasks in the containerized cluster environment. Efficiently scheduling data-parallel computation jobs like DNN over containerized clusters is critical for job performance, system throughput, and resource utilization. It becomes even more challenging with the complex workloads. We propose a scheduling method called Deep Learning Task Allocation Priority (DLTAP which performs scheduling decisions in a distributed manner, and each of scheduling decisions takes aggregation degree of parameter sever task and worker task into account, in particularly, to reduce cross-node network transmission traffic and, correspondingly, decrease the DNN training time. We evaluate the DLTAP scheduling method using a state-of-the-art distributed DNN training framework on 3 benchmarks. The results show that the proposed method can averagely reduce 12% cross-node network traffic, and decrease the DNN training time even with the cluster of low-end servers.

Integrated project scheduling and staff assignment with controllable processing times.

Science.gov (United States)

Fernandez-Viagas, Victor; Framinan, Jose M

2014-01-01

This paper addresses a decision problem related to simultaneously scheduling the tasks in a project and assigning the staff to these tasks, taking into account that a task can be performed only by employees with certain skills, and that the length of each task depends on the number of employees assigned. This type of problems usually appears in service companies, where both tasks scheduling and staff assignment are closely related. An integer programming model for the problem is proposed, together with some extensions to cope with different situations. Additionally, the advantages of the controllable processing times approach are compared with the fixed processing times. Due to the complexity of the integrated model, a simple GRASP algorithm is implemented in order to obtain good, approximate solutions in short computation times.

Integrated Project Scheduling and Staff Assignment with Controllable Processing Times

Directory of Open Access Journals (Sweden)

Victor Fernandez-Viagas

2014-01-01

Full Text Available This paper addresses a decision problem related to simultaneously scheduling the tasks in a project and assigning the staff to these tasks, taking into account that a task can be performed only by employees with certain skills, and that the length of each task depends on the number of employees assigned. This type of problems usually appears in service companies, where both tasks scheduling and staff assignment are closely related. An integer programming model for the problem is proposed, together with some extensions to cope with different situations. Additionally, the advantages of the controllable processing times approach are compared with the fixed processing times. Due to the complexity of the integrated model, a simple GRASP algorithm is implemented in order to obtain good, approximate solutions in short computation times.

Developing optimal nurses work schedule using integer programming

Science.gov (United States)

Shahidin, Ainon Mardhiyah; Said, Mohd Syazwan Md; Said, Noor Hizwan Mohamad; Sazali, Noor Izatie Amaliena

2017-08-01

Time management is the art of arranging, organizing and scheduling one's time for the purpose of generating more effective work and productivity. Scheduling is the process of deciding how to commit resources between varieties of possible tasks. Thus, it is crucial for every organization to have a good work schedule for their staffs. The job of Ward nurses at hospitals runs for 24 hours every day. Therefore, nurses will be working using shift scheduling. This study is aimed to solve the nurse scheduling problem at an emergency ward of a private hospital. A 7-day work schedule for 7 consecutive weeks satisfying all the constraints set by the hospital will be developed using Integer Programming. The work schedule for the nurses obtained gives an optimal solution where all the constraints are being satisfied successfully.

A combinatorial approach to multi-skill workforce scheduling

NARCIS (Netherlands)

Firat, M.; Hurkens, C.A.J.

2010-01-01

This paper deals with scheduling complex tasks with an inhomogeneous set of resources. The problem is to assign technicians to tasks with multi-level skill requirements. Here the requirements are merely the presence of a set of technicians that possess the necessary capabilities. An additional

Use of Perceive, Recall, Plan, Perform Stage Two Cognitive Task Analysis for Students with Autism and Intellectual Disability: The Impact of a Sensory Activity Schedule

Science.gov (United States)

Mills, Caroline; Chapparo, Christine

2017-01-01

The aim of this study was to determine the impact of a classroom sensory activity schedule (SAS) on cognitive strategy use during task performance. This work studies a single-system AB research design with seven students with autism and intellectual disability. Repeated measures using the Perceive, Recall, Plan and Perform (PRPP) Cognitive Task…

Modeling the violation of reward maximization and invariance in reinforcement schedules.

Directory of Open Access Journals (Sweden)

Giancarlo La Camera

2008-08-01

Full Text Available It is often assumed that animals and people adjust their behavior to maximize reward acquisition. In visually cued reinforcement schedules, monkeys make errors in trials that are not immediately rewarded, despite having to repeat error trials. Here we show that error rates are typically smaller in trials equally distant from reward but belonging to longer schedules (referred to as "schedule length effect". This violates the principles of reward maximization and invariance and cannot be predicted by the standard methods of Reinforcement Learning, such as the method of temporal differences. We develop a heuristic model that accounts for all of the properties of the behavior in the reinforcement schedule task but whose predictions are not different from those of the standard temporal difference model in choice tasks. In the modification of temporal difference learning introduced here, the effect of schedule length emerges spontaneously from the sensitivity to the immediately preceding trial. We also introduce a policy for general Markov Decision Processes, where the decision made at each node is conditioned on the motivation to perform an instrumental action, and show that the application of our model to the reinforcement schedule task and the choice task are special cases of this general theoretical framework. Within this framework, Reinforcement Learning can approach contextual learning with the mixture of empirical findings and principled assumptions that seem to coexist in the best descriptions of animal behavior. As examples, we discuss two phenomena observed in humans that often derive from the violation of the principle of invariance: "framing," wherein equivalent options are treated differently depending on the context in which they are presented, and the "sunk cost" effect, the greater tendency to continue an endeavor once an investment in money, effort, or time has been made. The schedule length effect might be a manifestation of these

ENHANCED HYBRID PSO – ACO ALGORITHM FOR GRID SCHEDULING

Directory of Open Access Journals (Sweden)

P. Mathiyalagan

2010-07-01

Full Text Available Grid computing is a high performance computing environment to solve larger scale computational demands. Grid computing contains resource management, task scheduling, security problems, information management and so on. Task scheduling is a fundamental issue in achieving high performance in grid computing systems. A computational GRID is typically heterogeneous in the sense that it combines clusters of varying sizes, and different clusters typically contains processing elements with different level of performance. In this, heuristic approaches based on particle swarm optimization and ant colony optimization algorithms are adopted for solving task scheduling problems in grid environment. Particle Swarm Optimization (PSO is one of the latest evolutionary optimization techniques by nature. It has the better ability of global searching and has been successfully applied to many areas such as, neural network training etc. Due to the linear decreasing of inertia weight in PSO the convergence rate becomes faster, which leads to the minimal makespan time when used for scheduling. To make the convergence rate faster, the PSO algorithm is improved by modifying the inertia parameter, such that it produces better performance and gives an optimized result. The ACO algorithm is improved by modifying the pheromone updating rule. ACO algorithm is hybridized with PSO algorithm for efficient result and better convergence in PSO algorithm.

A transportation-scheduling system for managing silvicultural projects

Science.gov (United States)

Jorge F. Valenzuela; H. Hakan Balci; Timothy McDonald

2005-01-01

A silvicultural project encompasses tasks such as sitelevel planning, regeneration, harvestin, and stand-tending treatments. an essential problem in managing silvicultural projects is to efficiently schedule the operations while considering project task due dates and costs of moving scarce resources to specific job locations. Transportation costs represent a...

Flow-shop scheduling problem under uncertainties: Review and trends

OpenAIRE

Eliana María González-Neira; Jairo R. Montoya-Torres; David Barrera

2017-01-01

Among the different tasks in production logistics, job scheduling is one of the most important at the operational decision-making level to enable organizations to achieve competiveness. Scheduling consists in the allocation of limited resources to activities over time in order to achieve one or more optimization objectives. Flow-shop (FS) scheduling problems encompass the sequencing processes in environments in which the activities or operations are performed in a serial flow. This type of co...

Microprocessor multi-task monitor

International Nuclear Information System (INIS)

Ludemann, C.A.

1983-01-01

This paper describes a multi-task monitor program for microprocessors. Although written for the Intel 8085, it incorporates features that would be beneficial for implementation in other microprocessors used in controlling and monitoring experiments and accelerators. The monitor places permanent programs (tasks) arbitrarily located throughout ROM in a priority ordered queue. The programmer is provided with the flexibility to add new tasks or modified versions of existing tasks, without having to comply with previously defined task boundaries or having to reprogram all of ROM. Scheduling of tasks is triggered by timers, outside stimuli (interrupts), or inter-task communications. Context switching time is of the order of tenths of a milllisecond

Technology for planning and scheduling under complex constraints

Science.gov (United States)

Alguire, Karen M.; Pedro Gomes, Carla O.

1997-02-01

Within the context of law enforcement, several problems fall into the category of planning and scheduling under constraints. Examples include resource and personnel scheduling, and court scheduling. In the case of court scheduling, a schedule must be generated considering available resources, e.g., court rooms and personnel. Additionally, there are constraints on individual court cases, e.g., temporal and spatial, and between different cases, e.g., precedence. Finally, there are overall objectives that the schedule should satisfy such as timely processing of cases and optimal use of court facilities. Manually generating a schedule that satisfies all of the constraints is a very time consuming task. As the number of court cases and constraints increases, this becomes increasingly harder to handle without the assistance of automatic scheduling techniques. This paper describes artificial intelligence (AI) technology that has been used to develop several high performance scheduling applications including a military transportation scheduler, a military in-theater airlift scheduler, and a nuclear power plant outage scheduler. We discuss possible law enforcement applications where we feel the same technology could provide long-term benefits to law enforcement agencies and their operations personnel.

NASA Schedule Management Handbook

Science.gov (United States)

2011-01-01

The purpose of schedule management is to provide the framework for time-phasing, resource planning, coordination, and communicating the necessary tasks within a work effort. The intent is to improve schedule management by providing recommended concepts, processes, and techniques used within the Agency and private industry. The intended function of this handbook is two-fold: first, to provide guidance for meeting the scheduling requirements contained in NPR 7120.5, NASA Space Flight Program and Project Management Requirements, NPR 7120.7, NASA Information Technology and Institutional Infrastructure Program and Project Requirements, NPR 7120.8, NASA Research and Technology Program and Project Management Requirements, and NPD 1000.5, Policy for NASA Acquisition. The second function is to describe the schedule management approach and the recommended best practices for carrying out this project control function. With regards to the above project management requirements documents, it should be noted that those space flight projects previously established and approved under the guidance of prior versions of NPR 7120.5 will continue to comply with those requirements until project completion has been achieved. This handbook will be updated as needed, to enhance efficient and effective schedule management across the Agency. It is acknowledged that most, if not all, external organizations participating in NASA programs/projects will have their own internal schedule management documents. Issues that arise from conflicting schedule guidance will be resolved on a case by case basis as contracts and partnering relationships are established. It is also acknowledged and understood that all projects are not the same and may require different levels of schedule visibility, scrutiny and control. Project type, value, and complexity are factors that typically dictate which schedule management practices should be employed.

Comparison of multi-objective evolutionary approaches for task ...

Indian Academy of Sciences (India)

evaluated using standard metrics. Experimental results and performance measures infer that NSGA-II produces quality schedules compared to NSPSO. ...... J 2005 Framework for task scheduling in heterogeneous distributed computing using.

Adapting planning and scheduling concepts to an engineering perspective: Key issues and successful techniques

International Nuclear Information System (INIS)

Finnegan, J.M.

1986-01-01

Traditional approaches to engineering planning are slanted toward the formats and interests of downstream implementation, and do not always consider the form and criticality of the front-end engineering development process. These processes and scopes are less defined and more subjective than most construction and operations tasks, and require flexible scheduling methods. This paper discusses the characteristics and requirement of engineering schedules, presents concepts for approaching planning in this field, and illustrates simple methods for developing and analyzing engineering plans, and evaluating schedule performance. Engineering plans are structured into a schedule hierarchy which delineates appropriate control and responsibilities, and is governed by key evaluation and decision milestones. Schedule risk analysis considers the uncertainty of engineering tasks, and critical resource constraints. Methods to evaluate schedule performance recognize that engineers and managers are responsible for adequate planning and forecasting, and quality decisions, even if they cannot control all factors influencing schedule results

Timing analysis for embedded systems using non-preemptive EDF scheduling under bounded error arrivals

Directory of Open Access Journals (Sweden)

Michael Short

2017-07-01

Full Text Available Embedded systems consist of one or more processing units which are completely encapsulated by the devices under their control, and they often have stringent timing constraints associated with their functional specification. Previous research has considered the performance of different types of task scheduling algorithm and developed associated timing analysis techniques for such systems. Although preemptive scheduling techniques have traditionally been favored, rapid increases in processor speeds combined with improved insights into the behavior of non-preemptive scheduling techniques have seen an increased interest in their use for real-time applications such as multimedia, automation and control. However when non-preemptive scheduling techniques are employed there is a potential lack of error confinement should any timing errors occur in individual software tasks. In this paper, the focus is upon adding fault tolerance in systems using non-preemptive deadline-driven scheduling. Schedulability conditions are derived for fault-tolerant periodic and sporadic task sets experiencing bounded error arrivals under non-preemptive deadline scheduling. A timing analysis algorithm is presented based upon these conditions and its run-time properties are studied. Computational experiments show it to be highly efficient in terms of run-time complexity and competitive ratio when compared to previous approaches.

Job shop scheduling problem with late work criterion

Science.gov (United States)

Piroozfard, Hamed; Wong, Kuan Yew

2015-05-01

Scheduling is considered as a key task in many industries, such as project based scheduling, crew scheduling, flight scheduling, machine scheduling, etc. In the machine scheduling area, the job shop scheduling problems are considered to be important and highly complex, in which they are characterized as NP-hard. The job shop scheduling problems with late work criterion and non-preemptive jobs are addressed in this paper. Late work criterion is a fairly new objective function. It is a qualitative measure and concerns with late parts of the jobs, unlike classical objective functions that are quantitative measures. In this work, simulated annealing was presented to solve the scheduling problem. In addition, operation based representation was used to encode the solution, and a neighbourhood search structure was employed to search for the new solutions. The case studies are Lawrence instances that were taken from the Operations Research Library. Computational results of this probabilistic meta-heuristic algorithm were compared with a conventional genetic algorithm, and a conclusion was made based on the algorithm and problem.

Teaching Task Sequencing via Verbal Mediation.

Science.gov (United States)

Rusch, Frank R.; And Others

1987-01-01

Verbal sequence training was used to teach a moderately mentally retarded woman to sequence job-related tasks. Learning to say the tasks in the proper sequence resulted in the employee performing her tasks in that sequence, and the employee was capable of mediating her own work behavior when scheduled changes occurred. (Author/JDD)

Different MK-801 administration schedules induce mild to severe learning impairments in an operant conditioning task: role of buspirone and risperidone in ameliorating these cognitive deficits.

Science.gov (United States)

Rapanelli, Maximiliano; Frick, Luciana Romina; Bernardez-Vidal, Micaela; Zanutto, Bonifacio Silvano

2013-11-15

Blockade of N-methyl-d-aspartate receptor (NMDA) by the noncompetitive NMDA receptor (NMDAR) antagonist MK-801 produces behavioral abnormalities and alterations in prefrontal cortex (PFC) functioning. Due to the critical role of the PFC in operant conditioning task learning, we evaluated the effects of acute, repeated postnatal injections of MK-801 (0.1mg/kg) on learning performance. We injected Long-Evans rats i.p. with MK-801 (0.1mg/kg) using three different administration schedules: injection 40 min before beginning the task (during) (n=12); injection twice daily for six consecutive days prior to beginning the experimental procedures (prior) (n=12); or twice daily subcutaneous injections from postnatal day 7 to 11 (postnatal) (n=12). Next, we orally administered risperidone (serotonin receptor 2A and dopamine receptor 2 antagonist, 1mg/kg) or buspirone (serotonin receptor 1A partial agonist, 10mg/kg) to animals treated with the MK-801 schedule described above. The postnatal and prior administration schedules produced severe learning deficits, whereas injection of MK-801 just before training sessions had only mild effects on acquisition of an operant conditioning. Risperidone was able to reverse the detrimental effect of MK-801 in the animals that were treated with MK-801 during and prior training sessions. In contrast, buspirone was only effective at mitigating the cognitive deficits induced by MK-801 when administered during the training procedures. The data demonstrates that NMDA antagonism disrupts basic mechanisms of learning in a simple PFC-mediated operant conditioning task, and that buspirone and risperidone failed to attenuate the learning deficits when NMDA neurotransmission was blocked in the early stages of the postnatal period. Copyright © 2013 Elsevier B.V. All rights reserved.

Characterizing and Mitigating Work Time Inflation in Task Parallel Programs

Directory of Open Access Journals (Sweden)

Stephen L. Olivier

2013-01-01

Full Text Available Task parallelism raises the level of abstraction in shared memory parallel programming to simplify the development of complex applications. However, task parallel applications can exhibit poor performance due to thread idleness, scheduling overheads, and work time inflation – additional time spent by threads in a multithreaded computation beyond the time required to perform the same work in a sequential computation. We identify the contributions of each factor to lost efficiency in various task parallel OpenMP applications and diagnose the causes of work time inflation in those applications. Increased data access latency can cause significant work time inflation in NUMA systems. Our locality framework for task parallel OpenMP programs mitigates this cause of work time inflation. Our extensions to the Qthreads library demonstrate that locality-aware scheduling can improve performance up to 3X compared to the Intel OpenMP task scheduler.

Optimizing Manpower Allocation for Ground Handling Tasks in Airports using Column Generation

DEFF Research Database (Denmark)

Hansen, Anders Dohn; Kolind, Esben

2008-01-01

individual teams to cooperate. Cooperating teams have to be synchronized with each other. Due to the limited number of teams, some tasks may have to be left unassigned. The objective is to maximize the number of assigned tasks. The problem arises in various crew scheduling contexts where cooperation between......The Manpower Allocation Problem with Time Windows, Job-Teaming Constraints and a limited number of teams (m-MAPTWTC) is the problem of assigning m teams to a number of tasks, where both teams and tasks are restricted by time windows outside which operation is not possible. Tasks may require several...... teams/workers, possibly with different skills, is required. This study focuses on the scheduling of ground handling tasks in some of Europe's major airports. Any daily schedule must comply with the time windows and skill requirements of tasks, transportation time between locations, the working hours...

A derived heuristics based multi-objective optimization procedure for micro-grid scheduling

Science.gov (United States)

Li, Xin; Deb, Kalyanmoy; Fang, Yanjun

2017-06-01

With the availability of different types of power generators to be used in an electric micro-grid system, their operation scheduling as the load demand changes with time becomes an important task. Besides satisfying load balance constraints and the generator's rated power, several other practicalities, such as limited availability of grid power and restricted ramping of power output from generators, must all be considered during the operation scheduling process, which makes it difficult to decide whether the optimization results are accurate and satisfactory. In solving such complex practical problems, heuristics-based customized optimization algorithms are suggested. However, due to nonlinear and complex interactions of variables, it is difficult to come up with heuristics in such problems off-hand. In this article, a two-step strategy is proposed in which the first task deciphers important heuristics about the problem and the second task utilizes the derived heuristics to solve the original problem in a computationally fast manner. Specifically, the specific operation scheduling is considered from a two-objective (cost and emission) point of view. The first task develops basic and advanced level knowledge bases offline from a series of prior demand-wise optimization runs and then the second task utilizes them to modify optimized solutions in an application scenario. Results on island and grid connected modes and several pragmatic formulations of the micro-grid operation scheduling problem clearly indicate the merit of the proposed two-step procedure.

Apprenticeship Learning: Learning to Schedule from Human Experts

Science.gov (United States)

2016-06-09

identified by the heuristic . A spectrum of problems (i.e. traveling salesman, job-shop scheduling, multi-vehicle routing) was represented , as task locations...caus- ing the codification of this knowledge to become labori- ous. We propose a new approach for capturing domain- expert heuristics through a...demonstrate that this approach accu- rately learns multi-faceted heuristics on both a synthetic data set incorporating job-shop scheduling and vehicle

Multiprocessor Global Scheduling on Frame-Based DVFS Systems

OpenAIRE

Berten, Vandy; Goossens, Joël

2008-01-01

International audience; In this work, we are interested in multiprocessor energy efficient systems where task durations are not known in advance but are known stochastically. More precisely we consider global scheduling algorithms for frame-based multiprocessor stochastic DVFS (Dynamic Voltage and Frequency Scaling) systems. Moreover we consider processors with a discrete set of available frequencies. We provide a global scheduling algorithm, and formally show that no deadline will ever be mi...

ComprehensiveBench: a Benchmark for the Extensive Evaluation of Global Scheduling Algorithms

Science.gov (United States)

Pilla, Laércio L.; Bozzetti, Tiago C.; Castro, Márcio; Navaux, Philippe O. A.; Méhaut, Jean-François

2015-10-01

Parallel applications that present tasks with imbalanced loads or complex communication behavior usually do not exploit the underlying resources of parallel platforms to their full potential. In order to mitigate this issue, global scheduling algorithms are employed. As finding the optimal task distribution is an NP-Hard problem, identifying the most suitable algorithm for a specific scenario and comparing algorithms are not trivial tasks. In this context, this paper presents ComprehensiveBench, a benchmark for global scheduling algorithms that enables the variation of a vast range of parameters that affect performance. ComprehensiveBench can be used to assist in the development and evaluation of new scheduling algorithms, to help choose a specific algorithm for an arbitrary application, to emulate other applications, and to enable statistical tests. We illustrate its use in this paper with an evaluation of Charm++ periodic load balancers that stresses their characteristics.

Updating Linear Schedules with Lowest Cost: a Linear Programming Model

Science.gov (United States)

Biruk, Sławomir; Jaśkowski, Piotr; Czarnigowska, Agata

2017-10-01

Many civil engineering projects involve sets of tasks repeated in a predefined sequence in a number of work areas along a particular route. A useful graphical representation of schedules of such projects is time-distance diagrams that clearly show what process is conducted at a particular point of time and in particular location. With repetitive tasks, the quality of project performance is conditioned by the ability of the planner to optimize workflow by synchronizing the works and resources, which usually means that resources are planned to be continuously utilized. However, construction processes are prone to risks, and a fully synchronized schedule may expire if a disturbance (bad weather, machine failure etc.) affects even one task. In such cases, works need to be rescheduled, and another optimal schedule should be built for the changed circumstances. This typically means that, to meet the fixed completion date, durations of operations have to be reduced. A number of measures are possible to achieve such reduction: working overtime, employing more resources or relocating resources from less to more critical tasks, but they all come at a considerable cost and affect the whole project. The paper investigates the problem of selecting the measures that reduce durations of tasks of a linear project so that the cost of these measures is kept to the minimum and proposes an algorithm that could be applied to find optimal solutions as the need to reschedule arises. Considering that civil engineering projects, such as road building, usually involve less process types than construction projects, the complexity of scheduling problems is lower, and precise optimization algorithms can be applied. Therefore, the authors put forward a linear programming model of the problem and illustrate its principle of operation with an example.

Investigation of implementing a synchronization protocol under multiprocessors hierarchical scheduling

NARCIS (Netherlands)

Nemati, F.; Behnam, M.; Bril, R.J.

2009-01-01

In the multi-core and multiprocessor domain, there has been considerable work done on scheduling techniques assuming that real-time tasks are independent. In practice a typical real-time system usually share logical resources among tasks. However, synchronization in the multiprocessor area has not

Scheduling and control of programs in the CICADA computer system for TFTR

International Nuclear Information System (INIS)

Christianson, G.B.; Sherrick, M.; Stark, W.

1983-01-01

The CICADA computer system is a network of super minicomputers for data acquisition, reduction, display and device control on the TFTR experiment. Human interaction with the CICADA system is accomplished by consoles offering color displays with a high degree of operator interaction with the computer system, and by interactive terminals offering a limited degree of operator interaction. The authors describe the software packages and data bases used to control the consoles and provide communication to an application program attached to a console. The console control program in its turn schedules the execution of control programs that furnish operating system interfaces to applications programs executing at a console or terminal (in response to human activation), or upon activation by scheduling tasks. The control programs handle functions such as applications task activation. They discuss the implementation of the control programs in the multi-computer CICADA environment, and describe the control program data bases. In a TFTR shot cycle, applications programs must be scheduled for activation at operator-defined stages, in order to accomplish the arming of hardware devices, acquisition of summary waveform data, and the acquisition and archiving of raw data. The authors describe the software tasks and data bases of the CICADA event system, which accomplishes this scheduling of applications task activation in conjunction with the control programs. Future enhancements planned for the console control, program control, and event systems are outlined

Adaptive Scheduling Applied to Non-Deterministic Networks of Heterogeneous Tasks for Peak Throughput in Concurrent Gaudi

CERN Document Server

AUTHOR|(CDS)2070032; Clemencic, Marco

As much the e-Science revolutionizes the scientific method in its empirical research and scientific theory, as it does pose the ever growing challenge of accelerating data deluge. The high energy physics (HEP) is a prominent representative of the data intensive science and requires scalable high-throughput software to be able to cope with associated computational endeavors. One such striking example is $\\text G\\rm \\small{AUDI}$ -- an experiment independent software framework, used in several frontier HEP experiments. Among them stand ATLAS and LHCb -- two of four mainstream experiments at the Large Hadron Collider (LHC) at CERN, the European Laboratory for Particle Physics. The framework is currently undergoing an architectural revolution aiming at massively concurrent and adaptive data processing. In this work I explore new dimensions of performance improvement for the next generation $\\text G\\rm \\small{AUDI}$. I then propose a complex of generic task scheduling solutions for adaptive and non-intrusive throu...

Automatic scheduling of maintenance work in nuclear power plants

International Nuclear Information System (INIS)

Kasahara, T.; Nishizawa, Y.; Kato, K.; Kiguchi, T.

1987-01-01

An automatic scheduling method for maintenance work in nuclear power plants has been developed using an AI technique. The purpose of this method is to help plant operators by adjusting the time schedule of various kinds of maintenance work so that incorrect ordering or timing of plant manipulations does not cause undersirable results, such as a plant trip. The functions of the method were tested by off-line simulations. The results show that the method can produce a satisfactory schedule of plant component manipulations without interference between the tasks and plant conditions

Aplikasi Penjadwalan Tugas Berbasis Mobile Device Didukung Google Task Dan Google Drive

OpenAIRE

Anggraini, Elisa Yuni; Wibowo, Adi; Dewi, Lily Puspa

2017-01-01

As the increased of work productivity, many task scheduling applications are emerging. Each of Task scheduling applications has its own advantages to similar competitors. The applications helps the user to remember if one of task was approaching deadline, and to store activities' data. However, to fulfil the task, we need a container to store important files in a safe place. In recent years, the use of Cloud Computing is growing because the data is safely stored. In the applications mention...

Trial-to-trial reoptimization of motor behavior due to changes in task demands is limited.

Directory of Open Access Journals (Sweden)

Orban de Xivry J-J

Full Text Available Each task requires a specific motor behavior that is tuned to task demands. For instance, writing requires a lot of accuracy while clapping does not. It is known that the brain adjusts the motor behavior to different task demands as predicted by optimal control theory. In this study, the mechanism of this reoptimization process is investigated by varying the accuracy demands of a reaching task. In this task, the width of the reaching target (0.5 or 8 cm was varied either on a trial-to-trial basis (random schedule or in blocks (blocked schedule. On some trials, the hand of the subjects was clamped to a rectilinear trajectory that ended 2 cm on the left or right of the target center. The rejection of this perturbation largely varied with target width in the blocked schedule but not in the random schedule. That is, subjects exhibited different motor behavior in the different schedules despite identical accuracy demands. Therefore, while reoptimization has been considered immediate and automatic, the differences in motor behavior observed across schedules suggest that the reoptimization of the motor behavior is neither happening on a trial-by-trial basis nor obligatory. The absence of trial-to-trial mechanisms, the inability of the brain to adapt to two conflicting task demands and the existence of a switching cost are discussed as possible sources of the non-optimality of motor behavior during the random schedule.

Planning and Scheduling for Fleets of Earth Observing Satellites

Science.gov (United States)

Frank, Jeremy; Jonsson, Ari; Morris, Robert; Smith, David E.; Norvig, Peter (Technical Monitor)

2001-01-01

We address the problem of scheduling observations for a collection of earth observing satellites. This scheduling task is a difficult optimization problem, potentially involving many satellites, hundreds of requests, constraints on when and how to service each request, and resources such as instruments, recording devices, transmitters, and ground stations. High-fidelity models are required to ensure the validity of schedules; at the same time, the size and complexity of the problem makes it unlikely that systematic optimization search methods will be able to solve them in a reasonable time. This paper presents a constraint-based approach to solving the Earth Observing Satellites (EOS) scheduling problem, and proposes a stochastic heuristic search method for solving it.

Voltage scheduling for low power/energy

Science.gov (United States)

Manzak, Ali

2001-07-01

Power considerations have become an increasingly dominant factor in the design of both portable and desk-top systems. An effective way to reduce power consumption is to lower the supply voltage since voltage is quadratically related to power. This dissertation considers the problem of lowering the supply voltage at (i) the system level and at (ii) the behavioral level. At the system level, the voltage of the variable voltage processor is dynamically changed with the work load. Processors with limited sized buffers as well as those with very large buffers are considered. Given the task arrival times, deadline times, execution times, periods and switching activities, task scheduling algorithms that minimize energy or peak power are developed for the processors equipped with very large buffers. A relation between the operating voltages of the tasks for minimum energy/power is determined using the Lagrange multiplier method, and an iterative algorithm that utilizes this relation is developed. Experimental results show that the voltage assignment obtained by the proposed algorithm is very close (0.1% error) to that of the optimal energy assignment and the optimal peak power (1% error) assignment. Next, on-line and off-fine minimum energy task scheduling algorithms are developed for processors with limited sized buffers. These algorithms have polynomial time complexity and present optimal (off-line) and close-to-optimal (on-line) solutions. A procedure to calculate the minimum buffer size given information about the size of the task (maximum, minimum), execution time (best case, worst case) and deadlines is also presented. At the behavioral level, resources operating at multiple voltages are used to minimize power while maintaining the throughput. Such a scheme has the advantage of allowing modules on the critical paths to be assigned to the highest voltage levels (thus meeting the required timing constraints) while allowing modules on non-critical paths to be assigned

Microcomputer-based workforce scheduling for hospital porters.

Science.gov (United States)

Lin, C K

1999-01-01

This paper focuses on labour scheduling for hospital porters who are the major workforce providing routine cleansing of wards, transportation and messenger services. Generating an equitable monthly roster for porters while meeting the daily minimum demand is a tedious task scheduled manually by a supervisor. In considering a variety of constraints and goals, a manual schedule was usually produced in seven to ten days. To be in line with the strategic goal of scientific management of an acute care regional hospital in Hong Kong, a microcomputer-based algorithm was developed to schedule the monthly roster. The algorithm, coded in Digital Visual Fortran 5.0 Professional, could generate a monthly roster in seconds. Implementation has been carried out since September 1998 and the results proved to be useful to hospital administrators and porters. This paper discusses both the technical and human issues involved during the computerization process.

VM Capacity-Aware Scheduling within Budget Constraints in IaaS Clouds.

Directory of Open Access Journals (Sweden)

Vasileios Thanasias

Full Text Available Recently, cloud computing has drawn significant attention from both industry and academia, bringing unprecedented changes to computing and information technology. The infrastructure-as-a-Service (IaaS model offers new abilities such as the elastic provisioning and relinquishing of computing resources in response to workload fluctuations. However, because the demand for resources dynamically changes over time, the provisioning of resources in a way that a given budget is efficiently utilized while maintaining a sufficing performance remains a key challenge. This paper addresses the problem of task scheduling and resource provisioning for a set of tasks running on IaaS clouds; it presents novel provisioning and scheduling algorithms capable of executing tasks within a given budget, while minimizing the slowdown due to the budget constraint. Our simulation study demonstrates a substantial reduction up to 70% in the overall task slowdown rate by the proposed algorithms.

VM Capacity-Aware Scheduling within Budget Constraints in IaaS Clouds.

Science.gov (United States)

Thanasias, Vasileios; Lee, Choonhwa; Hanif, Muhammad; Kim, Eunsam; Helal, Sumi

2016-01-01

Recently, cloud computing has drawn significant attention from both industry and academia, bringing unprecedented changes to computing and information technology. The infrastructure-as-a-Service (IaaS) model offers new abilities such as the elastic provisioning and relinquishing of computing resources in response to workload fluctuations. However, because the demand for resources dynamically changes over time, the provisioning of resources in a way that a given budget is efficiently utilized while maintaining a sufficing performance remains a key challenge. This paper addresses the problem of task scheduling and resource provisioning for a set of tasks running on IaaS clouds; it presents novel provisioning and scheduling algorithms capable of executing tasks within a given budget, while minimizing the slowdown due to the budget constraint. Our simulation study demonstrates a substantial reduction up to 70% in the overall task slowdown rate by the proposed algorithms.

A multitasking general executive for compound continuous tasks.

Science.gov (United States)

Salvucci, Dario D

2005-05-06

As cognitive architectures move to account for increasingly complex real-world tasks, one of the most pressing challenges involves understanding and modeling human multitasking. Although a number of existing models now perform multitasking in real-world scenarios, these models typically employ customized executives that schedule tasks for the particular domain but do not generalize easily to other domains. This article outlines a general executive for the Adaptive Control of Thought-Rational (ACT-R) cognitive architecture that, given independent models of individual tasks, schedules and interleaves the models' behavior into integrated multitasking behavior. To demonstrate the power of the proposed approach, the article describes an application to the domain of driving, showing how the general executive can interleave component subtasks of the driving task (namely, control and monitoring) and interleave driving with in-vehicle secondary tasks (radio tuning and phone dialing). 2005 Lawrence Erlbaum Associates, Inc.

Adaptive resource allocation for efficient patient scheduling

NARCIS (Netherlands)

Vermeulen, Ivan B.; Bohte, Sander M.; Elkhuizen, Sylvia G.; Lameris, Han; Bakker, Piet J. M.; La Poutré, Han

2009-01-01

Efficient scheduling of patient appointments on expensive resources is a complex and dynamic task. A resource is typically used by several patient groups. To service these groups, resource capacity is often allocated per group, explicitly or implicitly. Importantly, due to fluctuations in demand,

Intelligence amplification framework for enhancing scheduling processes

NARCIS (Netherlands)

Dobrkovic, Andrej; Liu, Luyao; Iacob, Maria Eugenia; van Hillegersberg, Jos

2016-01-01

The scheduling process in a typical business environment consists of predominantly repetitive tasks that have to be completed in limited time and often containing some form of uncertainty. The intelligence amplification is a symbiotic relationship between a human and an intelligent agent. This

Components installation. Scheduling techniques applied at Framatome for the French nuclear program

International Nuclear Information System (INIS)

Cremese, G.

1982-09-01

The first scheduling objective is a timely delivery of heavy components manufactured by FRAMATOME factories: reactor vessel, steam generators and pressurizer. The second scheduling function is the preparation and updating of overall and detailed schedules for the coordination and follow-up of: design activities, progress at equipment suppliers, construction and erection activities of sub-contractors, test and start-up tasks by FRAMATOME and customer teams, and maintenance operations by FRAMATOME teams. I shall first describe the schedules for the contract first unit then show how the following units of the contract are scheduled in their turn

Work schedule manager gap analysis : assessing the future training needs of work schedule managers using a strategic job analysis approach

Science.gov (United States)

2010-05-01

This report documents the results of a strategic job analysis that examined the job tasks and knowledge, skills, abilities, and other characteristics (KSAOs) needed to perform the job of a work schedule manager. The strategic job analysis compared in...

Job schedulers for Big data processing in Hadoop environment: testing real-life schedulers using benchmark programs

Directory of Open Access Journals (Sweden)

Mohd Usama

2017-11-01

Full Text Available At present, big data is very popular, because it has proved to be much successful in many fields such as social media, E-commerce transactions, etc. Big data describes the tools and technologies needed to capture, manage, store, distribute, and analyze petabyte or larger-sized datasets having different structures with high speed. Big data can be structured, unstructured, or semi structured. Hadoop is an open source framework that is used to process large amounts of data in an inexpensive and efficient way, and job scheduling is a key factor for achieving high performance in big data processing. This paper gives an overview of big data and highlights the problems and challenges in big data. It then highlights Hadoop Distributed File System (HDFS, Hadoop MapReduce, and various parameters that affect the performance of job scheduling algorithms in big data such as Job Tracker, Task Tracker, Name Node, Data Node, etc. The primary purpose of this paper is to present a comparative study of job scheduling algorithms along with their experimental results in Hadoop environment. In addition, this paper describes the advantages, disadvantages, features, and drawbacks of various Hadoop job schedulers such as FIFO, Fair, capacity, Deadline Constraints, Delay, LATE, Resource Aware, etc, and provides a comparative study among these schedulers.

Load Balancing in Cloud Computing Environment Using Improved Weighted Round Robin Algorithm for Nonpreemptive Dependent Tasks.

Science.gov (United States)

Devi, D Chitra; Uthariaraj, V Rhymend

2016-01-01

Cloud computing uses the concepts of scheduling and load balancing to migrate tasks to underutilized VMs for effectively sharing the resources. The scheduling of the nonpreemptive tasks in the cloud computing environment is an irrecoverable restraint and hence it has to be assigned to the most appropriate VMs at the initial placement itself. Practically, the arrived jobs consist of multiple interdependent tasks and they may execute the independent tasks in multiple VMs or in the same VM's multiple cores. Also, the jobs arrive during the run time of the server in varying random intervals under various load conditions. The participating heterogeneous resources are managed by allocating the tasks to appropriate resources by static or dynamic scheduling to make the cloud computing more efficient and thus it improves the user satisfaction. Objective of this work is to introduce and evaluate the proposed scheduling and load balancing algorithm by considering the capabilities of each virtual machine (VM), the task length of each requested job, and the interdependency of multiple tasks. Performance of the proposed algorithm is studied by comparing with the existing methods.

Applying genetic algorithms for programming manufactoring cell tasks

Directory of Open Access Journals (Sweden)

Efredy Delgado

2005-05-01

Full Text Available This work was aimed for developing computational intelligence for scheduling a manufacturing cell's tasks, based manily on genetic algorithms. The manufacturing cell was modelled as beign a production-line; the makespan was calculated by using heuristics adapted from several libraries for genetic algorithms computed in C++ builder. Several problems dealing with small, medium and large list of jobs and machinery were resolved. The results were compared with other heuristics. The approach developed here would seem to be promising for future research concerning scheduling manufacturing cell tasks involving mixed batches.

Proposing New Heuristic Approaches for Preventive Maintenance Scheduling

Directory of Open Access Journals (Sweden)

majid Esmailian

2013-08-01

Full Text Available The purpose of preventive maintenance management is to perform a series of tasks that prevent or minimize production breakdowns and improve reliability of production facilities. An important objective of preventive maintenance management is to minimize downtime of production facilities. In order to accomplish this objective, personnel should efficiently allocate resources and determine an effective maintenance schedule. Gopalakrishnan (1997 developed a mathematical model and four heuristic approaches to solve the preventive maintenance scheduling problem of assigning skilled personnel to work with tasks that require a set of corresponding skills. However, there are several limitations in the prior work in this area of research. The craft combination problem has not been solved because the craft combination is assumed as given. The craft combination problem concerns the computation of all combinations of assigning multi skilled workers to accomplishment of a particular task. In fact, determining craft combinations is difficult because of the exponential number of craft combinations that are possible. This research provides a heuristic approach for determining the craft combination and four new heuristic approach solution for the preventive maintenance scheduling problem with multi skilled workforce constraints. In order to examine the new heuristic approach and to compare the new heuristic approach with heuristic approach of Gopalakrishnan (1997, 81 standard problems have been generated based on the criterion suggested by from Gopalakrishnan (1997. The average solution quality (SQ of the new heuristic approaches is 1.86% and in old heuristic approaches is 8.32%. The solution time of new heuristic approaches are shorter than old heuristic approaches. The solution time of new heuristic approaches is 0.78 second and old heuristic approaches is 6.43 second, but the solution time of mathematical model provided by Gopalakrishnan (1997 is 152 second. �

Secure Scientific Applications Scheduling Technique for Cloud Computing Environment Using Global League Championship Algorithm.

Science.gov (United States)

Abdulhamid, Shafi'i Muhammad; Abd Latiff, Muhammad Shafie; Abdul-Salaam, Gaddafi; Hussain Madni, Syed Hamid

2016-01-01

Cloud computing system is a huge cluster of interconnected servers residing in a datacenter and dynamically provisioned to clients on-demand via a front-end interface. Scientific applications scheduling in the cloud computing environment is identified as NP-hard problem due to the dynamic nature of heterogeneous resources. Recently, a number of metaheuristics optimization schemes have been applied to address the challenges of applications scheduling in the cloud system, without much emphasis on the issue of secure global scheduling. In this paper, scientific applications scheduling techniques using the Global League Championship Algorithm (GBLCA) optimization technique is first presented for global task scheduling in the cloud environment. The experiment is carried out using CloudSim simulator. The experimental results show that, the proposed GBLCA technique produced remarkable performance improvement rate on the makespan that ranges between 14.44% to 46.41%. It also shows significant reduction in the time taken to securely schedule applications as parametrically measured in terms of the response time. In view of the experimental results, the proposed technique provides better-quality scheduling solution that is suitable for scientific applications task execution in the Cloud Computing environment than the MinMin, MaxMin, Genetic Algorithm (GA) and Ant Colony Optimization (ACO) scheduling techniques.

Secure Scientific Applications Scheduling Technique for Cloud Computing Environment Using Global League Championship Algorithm

Science.gov (United States)

Abdulhamid, Shafi’i Muhammad; Abd Latiff, Muhammad Shafie; Abdul-Salaam, Gaddafi; Hussain Madni, Syed Hamid

2016-01-01

Cloud computing system is a huge cluster of interconnected servers residing in a datacenter and dynamically provisioned to clients on-demand via a front-end interface. Scientific applications scheduling in the cloud computing environment is identified as NP-hard problem due to the dynamic nature of heterogeneous resources. Recently, a number of metaheuristics optimization schemes have been applied to address the challenges of applications scheduling in the cloud system, without much emphasis on the issue of secure global scheduling. In this paper, scientific applications scheduling techniques using the Global League Championship Algorithm (GBLCA) optimization technique is first presented for global task scheduling in the cloud environment. The experiment is carried out using CloudSim simulator. The experimental results show that, the proposed GBLCA technique produced remarkable performance improvement rate on the makespan that ranges between 14.44% to 46.41%. It also shows significant reduction in the time taken to securely schedule applications as parametrically measured in terms of the response time. In view of the experimental results, the proposed technique provides better-quality scheduling solution that is suitable for scientific applications task execution in the Cloud Computing environment than the MinMin, MaxMin, Genetic Algorithm (GA) and Ant Colony Optimization (ACO) scheduling techniques. PMID:27384239

Comparing Book- and Tablet-Based Picture Activity Schedules: Acquisition and Preference.

Science.gov (United States)

Giles, Aimee; Markham, Victoria

2017-09-01

Picture activity schedules consist of a sequence of images representing the order of tasks for a person to complete. Although, picture activity schedules have traditionally been presented in a book format, recently picture activity schedules have been evaluated on technological devices such as an iPod™ touch. The present study compared the efficiency of picture activity schedule acquisition on book- and tablet-based modalities. In addition, participant preference for each modality was assessed. Three boys aged below 5 years with a diagnosis of autism participated. Participants were taught to follow the schedules using both modalities. Following mastery of each modality of picture activity schedule, a concurrent-chains preference assessment was conducted to evaluate participant preference for each modality. Differences in acquisition rates across the two modalities were marginal. Preference for book- or tablet-based schedules was idiosyncratic across participants.

An extended Intelligent Water Drops algorithm for workflow scheduling in cloud computing environment

Directory of Open Access Journals (Sweden)

Shaymaa Elsherbiny

2018-03-01

Full Text Available Cloud computing is emerging as a high performance computing environment with a large scale, heterogeneous collection of autonomous systems and flexible computational architecture. Many resource management methods may enhance the efficiency of the whole cloud computing system. The key part of cloud computing resource management is resource scheduling. Optimized scheduling of tasks on the cloud virtual machines is an NP-hard problem and many algorithms have been presented to solve it. The variations among these schedulers are due to the fact that the scheduling strategies of the schedulers are adapted to the changing environment and the types of tasks. The focus of this paper is on workflows scheduling in cloud computing, which is gaining a lot of attention recently because workflows have emerged as a paradigm to represent complex computing problems. We proposed a novel algorithm extending the natural-based Intelligent Water Drops (IWD algorithm that optimizes the scheduling of workflows on the cloud. The proposed algorithm is implemented and embedded within the workflows simulation toolkit and tested in different simulated cloud environments with different cost models. Our algorithm showed noticeable enhancements over the classical workflow scheduling algorithms. We made a comparison between the proposed IWD-based algorithm with other well-known scheduling algorithms, including MIN-MIN, MAX-MIN, Round Robin, FCFS, and MCT, PSO and C-PSO, where the proposed algorithm presented noticeable enhancements in the performance and cost in most situations.

Optimizing Music Learning: Exploring How Blocked and Interleaved Practice Schedules Affect Advanced Performance.

Science.gov (United States)

Carter, Christine E; Grahn, Jessica A

2016-01-01

Repetition is the most commonly used practice strategy by musicians. Although blocks of repetition continue to be suggested in the pedagogical literature, work in the field of cognitive psychology suggests that repeated events receive less processing, thereby reducing the potential for long-term learning. Motor skill learning and sport psychology research offer an alternative. Instead of using a blocked practice schedule, with practice completed on one task before moving on to the next task, an interleaved schedule can be used, in which practice is frequently alternated between tasks. This frequent alternation involves more effortful processing, resulting in increased long-term learning. The finding that practicing in an interleaved schedule leads to better retention than practicing in a blocked schedule has been labeled the "contextual interference effect." While the effect has been observed across a wide variety of fields, few studies have researched this phenomenon in a music-learning context, despite the broad potential for application to music practice. This study compared the effects of blocked and interleaved practice schedules on advanced clarinet performance in an ecologically valid context. Ten clarinetists were given one concerto exposition and one technical excerpt to practice in a blocked schedule (12 min per piece) and a second concerto exposition and technical excerpt to practice in an interleaved schedule (3 min per piece, alternating until a total of 12 min of practice were completed on each piece). Participants sight-read the four pieces prior to practice and performed them at the end of practice and again one day later. The sight-reading and two performance run-throughs of each piece were recorded and given to three professional clarinetists to rate using a percentage scale. Overall, whenever there was a ratings difference between the conditions, pieces practiced in the interleaved schedule were rated better than those in the blocked schedule

Optimizing Music Learning: Exploring How Blocked and Interleaved Practice Schedules Affect Advanced Performance

Science.gov (United States)

Carter, Christine E.; Grahn, Jessica A.

2016-01-01

Repetition is the most commonly used practice strategy by musicians. Although blocks of repetition continue to be suggested in the pedagogical literature, work in the field of cognitive psychology suggests that repeated events receive less processing, thereby reducing the potential for long-term learning. Motor skill learning and sport psychology research offer an alternative. Instead of using a blocked practice schedule, with practice completed on one task before moving on to the next task, an interleaved schedule can be used, in which practice is frequently alternated between tasks. This frequent alternation involves more effortful processing, resulting in increased long-term learning. The finding that practicing in an interleaved schedule leads to better retention than practicing in a blocked schedule has been labeled the “contextual interference effect.” While the effect has been observed across a wide variety of fields, few studies have researched this phenomenon in a music-learning context, despite the broad potential for application to music practice. This study compared the effects of blocked and interleaved practice schedules on advanced clarinet performance in an ecologically valid context. Ten clarinetists were given one concerto exposition and one technical excerpt to practice in a blocked schedule (12 min per piece) and a second concerto exposition and technical excerpt to practice in an interleaved schedule (3 min per piece, alternating until a total of 12 min of practice were completed on each piece). Participants sight-read the four pieces prior to practice and performed them at the end of practice and again one day later. The sight-reading and two performance run-throughs of each piece were recorded and given to three professional clarinetists to rate using a percentage scale. Overall, whenever there was a ratings difference between the conditions, pieces practiced in the interleaved schedule were rated better than those in the blocked schedule

Optimizing music learning: Exploring how blocked and interleaved practice schedules affect advanced performance

Directory of Open Access Journals (Sweden)

Christine E Carter

2016-08-01

Full Text Available Repetition is the most commonly used practice strategy by musicians. Although blocks of repetition continue to be suggested in the pedagogical literature, work in the field of cognitive psychology suggests that repeated events receive less processing, thereby reducing the potential for long-term learning. Motor skill learning and sport psychology research offer an alternative. Instead of using a blocked practice schedule, with practice completed on one task before moving on to the next task, an interleaved schedule can be used, in which practice is frequently alternated between tasks. This frequent alternation involves more effortful processing, resulting in increased long-term learning. The finding that practicing in an interleaved schedule leads to better retention than practicing in a blocked schedule has been labeled the contextual interference effect. While the effect has been observed across a wide variety of fields, few studies have researched this phenomenon in a music-learning context, despite the broad potential for application to music practice. This study compared the effects of blocked and interleaved practice schedules on advanced clarinet performance in an ecologically valid context. Ten clarinetists were given one concerto exposition and one technical excerpt to practice in a blocked schedule (twelve minutes per piece and a second concerto exposition and technical excerpt to practice in an interleaved schedule (three minutes per piece, alternating until a total of twelve minutes of practice were completed on each piece. Participants sight-read the four pieces prior to practice and performed them at the end of practice and again one day later. The sight-reading and two performance run-throughs of each piece were recorded and given to three professional clarinetists to rate using a percentage scale. Overall, whenever there was a ratings difference between the conditions, pieces practiced in the interleaved schedule were rated

The R-Shell approach - Using scheduling agents in complex distributed real-time systems

Science.gov (United States)

Natarajan, Swaminathan; Zhao, Wei; Goforth, Andre

1993-01-01

Large, complex real-time systems such as space and avionics systems are extremely demanding in their scheduling requirements. The current OS design approaches are quite limited in the capabilities they provide for task scheduling. Typically, they simply implement a particular uniprocessor scheduling strategy and do not provide any special support for network scheduling, overload handling, fault tolerance, distributed processing, etc. Our design of the R-Shell real-time environment fcilitates the implementation of a variety of sophisticated but efficient scheduling strategies, including incorporation of all these capabilities. This is accomplished by the use of scheduling agents which reside in the application run-time environment and are responsible for coordinating the scheduling of the application.

Performing Task Integration

DEFF Research Database (Denmark)

Elkjaer, Bente; Nickelsen, Niels Christian Mossfeldt

by shared goals and knowledge as well as mutual respect and frequent, timely, accurate and problem-solving ways of communication with the purpose of dealing with the tasks at hand in an integrated way. We introduce and discuss relational coordination theory through a case-study within public healthcare....... Here cross-professional coordination of work was done by scheduled communication twice a day. When we proposed a way for further integration of tasks through an all-inclusive team organization, we were met with resistance. We use the study to discuss whether relational coordination theory is able to do...... away with differences regarding task definitions and working conditions as well as professional knowledge hierarchies and responsibilities for parts and wholes....

DEVELOPMENT OF GENETIC ALGORITHM-BASED METHODOLOGY FOR SCHEDULING OF MOBILE ROBOTS

DEFF Research Database (Denmark)

Dang, Vinh Quang

problem is to minimize the total traveling time of the single mobile robot and thereby increase its availability. For the second scheduling problem, a fleet of mobile robots is considered together with a set of machines to carry out different types of tasks, e.g. pre-assembly or quality inspection. Some...... problem and finding optimal solutions for each one. However, the formulated mathematical models could only be applicable to small-scale problems in practice due to the significant increase of computation time as the problem size grows. Note that making schedules of mobile robots is part of real-time....... For the first scheduling problem, a single mobile robot is considered to collect and transport container of parts and empty them into machine feeders where needed. A limit on carrying capacity of the single mobile robot and hard time windows of part-feeding tasks are considered. The objective of the first...

A distributed scheduling algorithm for heterogeneous real-time systems

Science.gov (United States)

Zeineldine, Osman; El-Toweissy, Mohamed; Mukkamala, Ravi

1991-01-01

Much of the previous work on load balancing and scheduling in distributed environments was concerned with homogeneous systems and homogeneous loads. Several of the results indicated that random policies are as effective as other more complex load allocation policies. The effects of heterogeneity on scheduling algorithms for hard real time systems is examined. A distributed scheduler specifically to handle heterogeneities in both nodes and node traffic is proposed. The performance of the algorithm is measured in terms of the percentage of jobs discarded. While a random task allocation is very sensitive to heterogeneities, the algorithm is shown to be robust to such non-uniformities in system components and load.

DLTAP: A Network-efficient Scheduling Method for Distributed Deep Learning Workload in Containerized Cluster Environment

OpenAIRE

Qiao Wei; Li Ying; Wu Zhong-Hai

2017-01-01

Deep neural networks (DNNs) have recently yielded strong results on a range of applications. Training these DNNs using a cluster of commodity machines is a promising approach since training is time consuming and compute-intensive. Furthermore, putting DNN tasks into containers of clusters would enable broader and easier deployment of DNN-based algorithms. Toward this end, this paper addresses the problem of scheduling DNN tasks in the containerized cluster environment. Efficiently scheduling ...

Development of Milestone Schedules for Selected Logistics Support Directorate Programs. Appendix A. Part 2. Task Summaries.

Science.gov (United States)

1987-09-15

LOGISTIC SUPPORT (ILS) COST ESTIMATE SCODE NUMBER: NONE -ESPONSIBILITY: ROY & ILS ’,!,RATION: 22.00 WORK DAYS A-221 * .9 ..- 9 * PAGE: .LSMTEST SCHEDULE: CE...0/ TIPO SCHEDULE: DV CONDUCT A PERFORMANCE DEMONSTRATION PRIOR TO TECHNICAL TEST CODE NUMBER: NONE (TT) I AND USER TEST (UT) I. RESPONSIBILITY...RESPONSIBILITY: BELVOIR LAB DURATION: 20.00 WORK DAYS ENG DE I SCHEDULE: DV ENGINEERING DESIGN INITIATED. CODE NUMBER: NONE RESPONSIBILITY: BELVOIR LAB

A Framework for Simplifying the Development of Kernel Schedulers: Design and Performance Evaluation

DEFF Research Database (Denmark)

Muller, Gilles; Lawall, Julia Laetitia; Duschene, Hervé

2005-01-01

Writing a new scheduler and integrating it into an existing OS is a daunting task, requiring the understanding of multiple low-level kernel mechanisms. Indeed, implementing a new scheduler is outside the expertise of application programmers, even though they are the ones who understand best the s...

Load Balancing in Cloud Computing Environment Using Improved Weighted Round Robin Algorithm for Nonpreemptive Dependent Tasks

Directory of Open Access Journals (Sweden)

D. Chitra Devi

2016-01-01

Full Text Available Cloud computing uses the concepts of scheduling and load balancing to migrate tasks to underutilized VMs for effectively sharing the resources. The scheduling of the nonpreemptive tasks in the cloud computing environment is an irrecoverable restraint and hence it has to be assigned to the most appropriate VMs at the initial placement itself. Practically, the arrived jobs consist of multiple interdependent tasks and they may execute the independent tasks in multiple VMs or in the same VM’s multiple cores. Also, the jobs arrive during the run time of the server in varying random intervals under various load conditions. The participating heterogeneous resources are managed by allocating the tasks to appropriate resources by static or dynamic scheduling to make the cloud computing more efficient and thus it improves the user satisfaction. Objective of this work is to introduce and evaluate the proposed scheduling and load balancing algorithm by considering the capabilities of each virtual machine (VM, the task length of each requested job, and the interdependency of multiple tasks. Performance of the proposed algorithm is studied by comparing with the existing methods.

A hybrid electromagnetism-like algorithm for a multi-mode resource-constrained project scheduling problem

Directory of Open Access Journals (Sweden)

Mohammad Hossein Sadeghi

2013-08-01

Full Text Available In this paper, two different sub-problems are considered to solve a resource constrained project scheduling problem (RCPSP, namely i assignment of modes to tasks and ii scheduling of these tasks in order to minimize the makespan of the project. The modified electromagnetism-like algorithm deals with the first problem to create an assignment of modes to activities. This list is used to generate a project schedule. When a new assignment is made, it is necessary to fix all mode dependent requirements of the project activities and to generate a random schedule with the serial SGS method. A local search will optimize the sequence of the activities. Also in this paper, a new penalty function has been proposed for solutions which are infeasible with respect to non-renewable resources. Performance of the proposed algorithm has been compared with the best algorithms published so far on the basis of CPU time and number of generated schedules stopping criteria. Reported results indicate excellent performance of the algorithm.

MaGate Simulator: A Simulation Environment for a Decentralized Grid Scheduler

Science.gov (United States)

Huang, Ye; Brocco, Amos; Courant, Michele; Hirsbrunner, Beat; Kuonen, Pierre

This paper presents a simulator for of a decentralized modular grid scheduler named MaGate. MaGate’s design emphasizes scheduler interoperability by providing intelligent scheduling serving the grid community as a whole. Each MaGate scheduler instance is able to deal with dynamic scheduling conditions, with continuously arriving grid jobs. Received jobs are either allocated on local resources, or delegated to other MaGates for remote execution. The proposed MaGate simulator is based on GridSim toolkit and Alea simulator, and abstracts the features and behaviors of complex fundamental grid elements, such as grid jobs, grid resources, and grid users. Simulation of scheduling tasks is supported by a grid network overlay simulator executing distributed ant-based swarm intelligence algorithms to provide services such as group communication and resource discovery. For evaluation, a comparison of behaviors of different collaborative policies among a community of MaGates is provided. Results support the use of the proposed approach as a functional ready grid scheduler simulator.

Efficient Feasibility Analysis for Real-Time Systems with EDF Scheduling

OpenAIRE

Albers , Karsten; Slomka , Frank

2005-01-01

Submitted on behalf of EDAA (http://www.edaa.com/); International audience; This paper presents new fast exact feasibility tests for uniprocessor real-time systems using preemptive EDF scheduling. Task sets which are accepted by previously described sufficient tests will be evaluated in nearly the same time as with the old tests by the new algorithms. Many task sets are not accepted by the earlier tests despite them beeing feasible. These task sets will be evaluated by the new algorithms a lo...

A Multitasking General Executive for Compound Continuous Tasks

Science.gov (United States)

Salvucci, Dario D.

2005-01-01

As cognitive architectures move to account for increasingly complex real-world tasks, one of the most pressing challenges involves understanding and modeling human multitasking. Although a number of existing models now perform multitasking in real-world scenarios, these models typically employ customized executives that schedule tasks for the…

Load Balancing in Cloud Computing Environment Using Improved Weighted Round Robin Algorithm for Nonpreemptive Dependent Tasks

OpenAIRE

Devi, D. Chitra; Uthariaraj, V. Rhymend

2016-01-01

Cloud computing uses the concepts of scheduling and load balancing to migrate tasks to underutilized VMs for effectively sharing the resources. The scheduling of the nonpreemptive tasks in the cloud computing environment is an irrecoverable restraint and hence it has to be assigned to the most appropriate VMs at the initial placement itself. Practically, the arrived jobs consist of multiple interdependent tasks and they may execute the independent tasks in multiple VMs or in the same VM’s mul...

Software Schedules Missions, Aids Project Management

Science.gov (United States)

2008-01-01

NASA missions require advanced planning, scheduling, and management, and the Space Agency has worked extensively to develop the programs and software suites necessary to facilitate these complex missions. These enormously intricate undertakings have hundreds of active components that need constant management and monitoring. It is no surprise, then, that the software developed for these tasks is often applicable in other high-stress, complex environments, like in government or industrial settings. NASA work over the past few years has resulted in a handful of new scheduling, knowledge-management, and research tools developed under contract with one of NASA s partners. These tools have the unique responsibility of supporting NASA missions, but they are also finding uses outside of the Space Program.

A fuzzy-based particle swarm optimisation approach for task assignment in home healthcare

Directory of Open Access Journals (Sweden)

Mutingi, Michael

2014-11-01

Full Text Available Home healthcare (HHC organisations provide coordinated healthcare services to patients at their homes. Motivated by the ever-increasing need for home-based care, the assignment of tasks to available healthcare staff is a common and complex problem in homecare organisations. Designing high quality task schedules is critical for improving worker morale, job satisfaction, service efficiency, service quality, and competitiveness over the long term. The desire is to provide high quality task assignment schedules that satisfy the patient, the care worker, and the management. This translates to maximising schedule fairness in terms of workload assignments, avoiding task time window violation, and meeting management goals as much as possible. However, in practice, these desires are often subjective as they involve imprecise human perceptions. This paper develops a fuzzy multi-criteria particle swarm optimisation (FPSO approach for task assignment in a home healthcare setting in a fuzzy environment. The proposed approach uses a fuzzy evaluation method from a multi-criteria point of view. Results from illustrative computational experiments show that the approach is promising.

The complexity of scheduling trees with communication delays

NARCIS (Netherlands)

Lenstra, J.K.; Veldhorst, M.; Veltman, B.

1996-01-01

We consider the problem of finding a minimum-length schedule onmmachines for a set ofnunit-length tasks with a forest of intrees as precedence relation, and with unit interprocessor communication delays. First, we prove that this problem is NP-complete; second, we derive a linear time algorithm for

Evaluation of Selected Resource Allocation and Scheduling Methods in Heterogeneous Many-Core Processors and Graphics Processing Units

Directory of Open Access Journals (Sweden)

Ciznicki Milosz

2014-12-01

Full Text Available Heterogeneous many-core computing resources are increasingly popular among users due to their improved performance over homogeneous systems. Many developers have realized that heterogeneous systems, e.g. a combination of a shared memory multi-core CPU machine with massively parallel Graphics Processing Units (GPUs, can provide significant performance opportunities to a wide range of applications. However, the best overall performance can only be achieved if application tasks are efficiently assigned to different types of processor units in time taking into account their specific resource requirements. Additionally, one should note that available heterogeneous resources have been designed as general purpose units, however, with many built-in features accelerating specific application operations. In other words, the same algorithm or application functionality can be implemented as a different task for CPU or GPU. Nevertheless, from the perspective of various evaluation criteria, e.g. the total execution time or energy consumption, we may observe completely different results. Therefore, as tasks can be scheduled and managed in many alternative ways on both many-core CPUs or GPUs and consequently have a huge impact on the overall computing resources performance, there are needs for new and improved resource management techniques. In this paper we discuss results achieved during experimental performance studies of selected task scheduling methods in heterogeneous computing systems. Additionally, we present a new architecture for resource allocation and task scheduling library which provides a generic application programming interface at the operating system level for improving scheduling polices taking into account a diversity of tasks and heterogeneous computing resources characteristics.

Self-powered information measuring wireless networks using the distribution of tasks within multicore processors

Science.gov (United States)

Zhuravska, Iryna M.; Koretska, Oleksandra O.; Musiyenko, Maksym P.; Surtel, Wojciech; Assembay, Azat; Kovalev, Vladimir; Tleshova, Akmaral

2017-08-01

The article contains basic approaches to develop the self-powered information measuring wireless networks (SPIM-WN) using the distribution of tasks within multicore processors critical applying based on the interaction of movable components - as in the direction of data transmission as wireless transfer of energy coming from polymetric sensors. Base mathematic model of scheduling tasks within multiprocessor systems was modernized to schedule and allocate tasks between cores of one-crystal computer (SoC) to increase energy efficiency SPIM-WN objects.

Allocating time to future tasks: the effect of task segmentation on planning fallacy bias.

Science.gov (United States)

Forsyth, Darryl K; Burt, Christopher D B

2008-06-01

The scheduling component of the time management process was used as a "paradigm" to investigate the allocation of time to future tasks. In three experiments, we compared task time allocation for a single task with the summed time allocations given for each subtask that made up the single task. In all three, we found that allocated time for a single task was significantly smaller than the summed time allocated to the individual subtasks. We refer to this as the segmentation effect. In Experiment 3, we asked participants to give estimates by placing a mark on a time line, and found that giving time allocations in the form of rounded close approximations probably does not account for the segmentation effect. We discuss the results in relation to the basic processes used to allocate time to future tasks and the means by which planning fallacy bias might be reduced.

Coordinating space telescope operations in an integrated planning and scheduling architecture

Science.gov (United States)

Muscettola, Nicola; Smith, Stephen F.; Cesta, Amedeo; D'Aloisi, Daniela

1992-01-01

The Heuristic Scheduling Testbed System (HSTS), a software architecture for integrated planning and scheduling, is discussed. The architecture has been applied to the problem of generating observation schedules for the Hubble Space Telescope. This problem is representative of the class of problems that can be addressed: their complexity lies in the interaction of resource allocation and auxiliary task expansion. The architecture deals with this interaction by viewing planning and scheduling as two complementary aspects of the more general process of constructing behaviors of a dynamical system. The principal components of the software architecture are described, indicating how to model the structure and dynamics of a system, how to represent schedules at multiple levels of abstraction in the temporal database, and how the problem solving machinery operates. A scheduler for the detailed management of Hubble Space Telescope operations that has been developed within HSTS is described. Experimental performance results are given that indicate the utility and practicality of the approach.

Multi-Satellite Observation Scheduling for Large Area Disaster Emergency Response

Science.gov (United States)

Niu, X. N.; Tang, H.; Wu, L. X.

2018-04-01

an optimal imaging plan, plays a key role in coordinating multiple satellites to monitor the disaster area. In the paper, to generate imaging plan dynamically according to the disaster relief, we propose a dynamic satellite task scheduling method for large area disaster response. First, an initial robust scheduling scheme is generated by a robust satellite scheduling model in which both the profit and the robustness of the schedule are simultaneously maximized. Then, we use a multi-objective optimization model to obtain a series of decomposing schemes. Based on the initial imaging plan, we propose a mixed optimizing algorithm named HA_NSGA-II to allocate the decomposing results thus to obtain an adjusted imaging schedule. A real disaster scenario, i.e., 2008 Wenchuan earthquake, is revisited in terms of rapid response using satellite resources and used to evaluate the performance of the proposed method with state-of-the-art approaches. We conclude that our satellite scheduling model can optimize the usage of satellite resources so as to obtain images in disaster response in a more timely and efficient manner.

An Improved Task Scheduling Algorithm for Intelligent Control in Tiny Mechanical System

Directory of Open Access Journals (Sweden)

Jialiang Wang

2014-01-01

Full Text Available Wireless sensor network (WSN has been already widely used in many fields in terms of industry, agriculture, and military, and so forth. The basic composition is WSN nodes that are capable of performing processing, gathering information, and communicating with other connected nodes in the network. The main components of a WSN node are microcontroller, transceiver, and some sensors. Undoubtedly, it also can be added with some actuators to form a tiny mechanical system. Under this case, the existence of task preemption while executing operating system will not only cost more energy for WSN nodes themselves, but also bring unacceptable system states caused by vibrations. However for these nodes, task I/O delays are inevitable due to the existence of task preemption, which will bring extra overhead for the whole system, and even bring unacceptable system states caused by vibrations. This paper mainly considers the earliest deadline first (EDF task preemption algorithm executed in WSN OS and proposes an improved task preemption algorithm so as to lower the preemption overhead and I/O delay and then improve the system performance. The experimental results show that the improved task preemption algorithm can reduce the I/O delay effectively, so the real-time processing ability of the system is enhanced.

Supporting Real-Time Operations and Execution through Timeline and Scheduling Aids

Science.gov (United States)

Marquez, Jessica J.; Pyrzak, Guy; Hashemi, Sam; Ahmed, Samia; McMillin, Kevin Edward; Medwid, Joseph Daniel; Chen, Diana; Hurtle, Esten

2013-01-01

Since 2003, the NASA Ames Research Center has been actively involved in researching and advancing the state-of-the-art of planning and scheduling tools for NASA mission operations. Our planning toolkit SPIFe (Scheduling and Planning Interface for Exploration) has supported a variety of missions and field tests, scheduling activities for Mars rovers as well as crew on-board International Space Station and NASA earth analogs. The scheduled plan is the integration of all the activities for the day/s. In turn, the agents (rovers, landers, spaceships, crew) execute from this schedule while the mission support team members (e.g., flight controllers) follow the schedule during execution. Over the last couple of years, our team has begun to research and validate methods that will better support users during realtime operations and execution of scheduled activities. Our team utilizes human-computer interaction principles to research user needs, identify workflow processes, prototype software aids, and user test these. This paper discusses three specific prototypes developed and user tested to support real-time operations: Score Mobile, Playbook, and Mobile Assistant for Task Execution (MATE).

Problem specific heuristics for group scheduling problems in cellular manufacturing

OpenAIRE

Neufeld, Janis Sebastian

2016-01-01

The group scheduling problem commonly arises in cellular manufacturing systems, where parts are grouped into part families. It is characterized by a sequencing task on two levels: on the one hand, a sequence of jobs within each part family has to be identified while, on the other hand, a family sequence has to be determined. In order to solve this NP-hard problem usually heuristic solution approaches are used. In this thesis different aspects of group scheduling are discussed and problem spec...

Constraint based scheduling for the Goddard Space Flight Center distributed Active Archive Center's data archive and distribution system

Science.gov (United States)

Short, Nick, Jr.; Bedet, Jean-Jacques; Bodden, Lee; Boddy, Mark; White, Jim; Beane, John

1994-01-01

The Goddard Space Flight Center (GSFC) Distributed Active Archive Center (DAAC) has been operational since October 1, 1993. Its mission is to support the Earth Observing System (EOS) by providing rapid access to EOS data and analysis products, and to test Earth Observing System Data and Information System (EOSDIS) design concepts. One of the challenges is to ensure quick and easy retrieval of any data archived within the DAAC's Data Archive and Distributed System (DADS). Over the 15-year life of EOS project, an estimated several Petabytes (10(exp 15)) of data will be permanently stored. Accessing that amount of information is a formidable task that will require innovative approaches. As a precursor of the full EOS system, the GSFC DAAC with a few Terabits of storage, has implemented a prototype of a constraint-based task and resource scheduler to improve the performance of the DADS. This Honeywell Task and Resource Scheduler (HTRS), developed by Honeywell Technology Center in cooperation the Information Science and Technology Branch/935, the Code X Operations Technology Program, and the GSFC DAAC, makes better use of limited resources, prevents backlog of data, provides information about resources bottlenecks and performance characteristics. The prototype which is developed concurrently with the GSFC Version 0 (V0) DADS, models DADS activities such as ingestion and distribution with priority, precedence, resource requirements (disk and network bandwidth) and temporal constraints. HTRS supports schedule updates, insertions, and retrieval of task information via an Application Program Interface (API). The prototype has demonstrated with a few examples, the substantial advantages of using HTRS over scheduling algorithms such as a First In First Out (FIFO) queue. The kernel scheduling engine for HTRS, called Kronos, has been successfully applied to several other domains such as space shuttle mission scheduling, demand flow manufacturing, and avionics communications

Improved Space Surveillance Network (SSN) Scheduling using Artificial Intelligence Techniques

Science.gov (United States)

Stottler, D.

There are close to 20,000 cataloged manmade objects in space, the large majority of which are not active, functioning satellites. These are tracked by phased array and mechanical radars and ground and space-based optical telescopes, collectively known as the Space Surveillance Network (SSN). A better SSN schedule of observations could, using exactly the same legacy sensor resources, improve space catalog accuracy through more complementary tracking, provide better responsiveness to real-time changes, better track small debris in low earth orbit (LEO) through efficient use of applicable sensors, efficiently track deep space (DS) frequent revisit objects, handle increased numbers of objects and new types of sensors, and take advantage of future improved communication and control to globally optimize the SSN schedule. We have developed a scheduling algorithm that takes as input the space catalog and the associated covariance matrices and produces a globally optimized schedule for each sensor site as to what objects to observe and when. This algorithm is able to schedule more observations with the same sensor resources and have those observations be more complementary, in terms of the precision with which each orbit metric is known, to produce a satellite observation schedule that, when executed, minimizes the covariances across the entire space object catalog. If used operationally, the results would be significantly increased accuracy of the space catalog with fewer lost objects with the same set of sensor resources. This approach inherently can also trade-off fewer high priority tasks against more lower-priority tasks, when there is benefit in doing so. Currently the project has completed a prototyping and feasibility study, using open source data on the SSN's sensors, that showed significant reduction in orbit metric covariances. The algorithm techniques and results will be discussed along with future directions for the research.

Staff Scheduling within the Retail Business in Denmark

DEFF Research Database (Denmark)

Leedgaard, Jesper; Mortensen, Kim H.; Larsen, Allan

2002-01-01

Staff Scheduling within the retail business deals with the assignment of employees such as shop assistants to work tasks so that the right number of employees are available at any given times and the total staff costs are minimized. In this paper the retail staff scheduling problem is formulated...... as a Mixed Integer Problem. The retail staff scheduling problem is solved using the metaheuristic {\\$\\backslash\\$it Simulated Annealing}. The heuristic is implemented by modifying the original MIP model. Some of the constraints defined in the MIP are relaxed, entered into the objective function and weighted...... according to their relative importance. The problem is then formulated as minimizing the overall constraint violation. A thorough parameter test has been applied to the developed heuristics. The developed system has successfully been implemented in a number of shops and stores in Denmark....

An Optimal Scheduling Algorithm with a Competitive Factor for Real-Time Systems

Science.gov (United States)

1991-07-29

real - time systems in which the value of a task is proportional to its computation time. The system obtains the value of a given task if the task completes by its deadline. Otherwise, the system obtains no value for the task. When such a system is underloaded (i.e. there exists a schedule for which all tasks meet their deadlines), Dertouzos [6] showed that the earliest deadline first algorithm will achieve 100% of the possible value. We consider the case of a possibly overloaded system and present an algorithm which: 1. behaves like the earliest deadline first

Compositional schedulability analysis of real-time actor-based systems.

Science.gov (United States)

Jaghoori, Mohammad Mahdi; de Boer, Frank; Longuet, Delphine; Chothia, Tom; Sirjani, Marjan

2017-01-01

We present an extension of the actor model with real-time, including deadlines associated with messages, and explicit application-level scheduling policies, e.g.,"earliest deadline first" which can be associated with individual actors. Schedulability analysis in this setting amounts to checking whether, given a scheduling policy for each actor, every task is processed within its designated deadline. To check schedulability, we introduce a compositional automata-theoretic approach, based on maximal use of model checking combined with testing. Behavioral interfaces define what an actor expects from the environment, and the deadlines for messages given these assumptions. We use model checking to verify that actors match their behavioral interfaces. We extend timed automata refinement with the notion of deadlines and use it to define compatibility of actor environments with the behavioral interfaces. Model checking of compatibility is computationally hard, so we propose a special testing process. We show that the analyses are decidable and automate the process using the Uppaal model checker.

Multiprocessor scheduling for real-time systems

CERN Document Server

Baruah, Sanjoy; Buttazzo, Giorgio

2015-01-01

This book provides a comprehensive overview of both theoretical and pragmatic aspects of resource-allocation and scheduling in multiprocessor and multicore hard-real-time systems.  The authors derive new, abstract models of real-time tasks that capture accurately the salient features of real application systems that are to be implemented on multiprocessor platforms, and identify rules for mapping application systems onto the most appropriate models.  New run-time multiprocessor scheduling algorithms are presented, which are demonstrably better than those currently used, both in terms of run-time efficiency and tractability of off-line analysis.  Readers will benefit from a new design and analysis framework for multiprocessor real-time systems, which will translate into a significantly enhanced ability to provide formally verified, safety-critical real-time systems at a significantly lower cost.

Scheduling of resource-constrained projects

CERN Document Server

Klein, Robert

2000-01-01

Project management has become a widespread instrument enabling organizations to efficiently master the challenges of steadily shortening product life cycles, global markets and decreasing profit margins. With projects increasing in size and complexity, their planning and control represents one of the most crucial management tasks. This is especially true for scheduling, which is concerned with establishing execution dates for the sub-activities to be performed in order to complete the project. The ability to manage projects where resources must be allocated between concurrent projects or even sub-activities of a single project requires the use of commercial project management software packages. However, the results yielded by the solution procedures included are often rather unsatisfactory. Scheduling of Resource-Constrained Projects develops more efficient procedures, which can easily be integrated into software packages by incorporated programming languages, and thus should be of great interest for practiti...

tms-sim - Timing Models Scheduling Simulation Framework: Release 2014-12

OpenAIRE

Kluge, Florian

2015-01-01

tms-sim is a framework for the simulation and evaluation of scheduling algorithms. It is being developed to support our work on real-time task scheduling based on time-utility and history-cognisant utility functions. We publish tms-sim under the conditions of the GNU GPL to make our results reproducible and in the hope that it may be useful for others. This report describes the usage of the TMS framework libraries and how they can be used to build further simulation environments. It is not in...

Scheduling algorithms for automatic control systems for technological processes

Science.gov (United States)

Chernigovskiy, A. S.; Tsarev, R. Yu; Kapulin, D. V.

2017-01-01

Wide use of automatic process control systems and the usage of high-performance systems containing a number of computers (processors) give opportunities for creation of high-quality and fast production that increases competitiveness of an enterprise. Exact and fast calculations, control computation, and processing of the big data arrays - all of this requires the high level of productivity and, at the same time, minimum time of data handling and result receiving. In order to reach the best time, it is necessary not only to use computing resources optimally, but also to design and develop the software so that time gain will be maximal. For this purpose task (jobs or operations), scheduling techniques for the multi-machine/multiprocessor systems are applied. Some of basic task scheduling methods for the multi-machine process control systems are considered in this paper, their advantages and disadvantages come to light, and also some usage considerations, in case of the software for automatic process control systems developing, are made.

GLOA: A New Job Scheduling Algorithm for Grid Computing

Directory of Open Access Journals (Sweden)

Zahra Pooranian

2013-03-01

Full Text Available The purpose of grid computing is to produce a virtual supercomputer by using free resources available through widespread networks such as the Internet. This resource distribution, changes in resource availability, and an unreliable communication infrastructure pose a major challenge for efficient resource allocation. Because of the geographical spread of resources and their distributed management, grid scheduling is considered to be a NP-complete problem. It has been shown that evolutionary algorithms offer good performance for grid scheduling. This article uses a new evaluation (distributed algorithm inspired by the effect of leaders in social groups, the group leaders' optimization algorithm (GLOA, to solve the problem of scheduling independent tasks in a grid computing system. Simulation results comparing GLOA with several other evaluation algorithms show that GLOA produces shorter makespans.

Flow-shop scheduling problem under uncertainties: Review and trends

Directory of Open Access Journals (Sweden)

Eliana María González-Neira

2017-03-01

Full Text Available Among the different tasks in production logistics, job scheduling is one of the most important at the operational decision-making level to enable organizations to achieve competiveness. Scheduling consists in the allocation of limited resources to activities over time in order to achieve one or more optimization objectives. Flow-shop (FS scheduling problems encompass the sequencing processes in environments in which the activities or operations are performed in a serial flow. This type of configuration includes assembly lines and the chemical, electronic, food, and metallurgical industries, among others. Scheduling has been mostly investigated for the deterministic cases, in which all parameters are known in advance and do not vary over time. Nevertheless, in real-world situations, events are frequently subject to uncertainties that can affect the decision-making process. Thus, it is important to study scheduling and sequencing activities under uncertainties since they can cause infeasibilities and disturbances. The purpose of this paper is to provide a general overview of the FS scheduling problem under uncertainties and its role in production logistics and to draw up opportunities for further research. To this end, 100 papers about FS and flexible flow-shop scheduling problems published from 2001 to October 2016 were analyzed and classified. Trends in the reviewed literature are presented and finally some research opportunities in the field are proposed.

Routing Cooperating Vehicles to Perform Precedence-Linked Tasks

National Research Council Canada - National Science Library

Vakhutinsky, Andrew; Wu, Cynara

2005-01-01

The problem of scheduling cooperating vehicles is a generalization of the classical vehicle routing problem where certain tasks are linked by precedence constraints and vehicles have varying constrained resources...

Streaming system scheduling for Xeon Phi

OpenAIRE

Faltín, Tomáš

2017-01-01

Task scheduling in operating system area is a well-known problem on traditional system architectures (NUMA, SMP). Unfortunately, it does not perform well on emerging many-core architectures, especially on Intel Xeon Phi. We collected all publicly available information about the architecture of Xeon Phi. After that, we benchmarked the Xeon Phi in order to find the missing information about its architecture. We focused especially on the information about cores and memory controllers. These are ...

A new distributed systems scheduling algorithm: a swarm intelligence approach

Science.gov (United States)

Haghi Kashani, Mostafa; Sarvizadeh, Raheleh; Jameii, Mahdi

2011-12-01

The scheduling problem in distributed systems is known as an NP-complete problem, and methods based on heuristic or metaheuristic search have been proposed to obtain optimal and suboptimal solutions. The task scheduling is a key factor for distributed systems to gain better performance. In this paper, an efficient method based on memetic algorithm is developed to solve the problem of distributed systems scheduling. With regard to load balancing efficiently, Artificial Bee Colony (ABC) has been applied as local search in the proposed memetic algorithm. The proposed method has been compared to existing memetic-Based approach in which Learning Automata method has been used as local search. The results demonstrated that the proposed method outperform the above mentioned method in terms of communication cost.

Auditory Training for Adults Who Have Hearing Loss: A Comparison of Spaced Versus Massed Practice Schedules.

Science.gov (United States)

Tye-Murray, Nancy; Spehar, Brent; Barcroft, Joe; Sommers, Mitchell

2017-08-16

The spacing effect in human memory research refers to situations in which people learn items better when they study items in spaced intervals rather than massed intervals. This investigation was conducted to compare the efficacy of meaning-oriented auditory training when administered with a spaced versus massed practice schedule. Forty-seven adult hearing aid users received 16 hr of auditory training. Participants in a spaced group (mean age = 64.6 years, SD = 14.7) trained twice per week, and participants in a massed group (mean age = 69.6 years, SD = 17.5) trained for 5 consecutive days each week. Participants completed speech perception tests before training, immediately following training, and then 3 months later. In line with transfer appropriate processing theory, tests assessed both trained tasks and an untrained task. Auditory training improved the speech recognition performance of participants in both groups. Benefits were maintained for 3 months. No effect of practice schedule was found on overall benefits achieved, on retention of benefits, nor on generalizability of benefits to nontrained tasks. The lack of spacing effect in otherwise effective auditory training suggests that perceptual learning may be subject to different influences than are other types of learning, such as vocabulary learning. Hence, clinicians might have latitude in recommending training schedules to accommodate patients' schedules.

TECHNICAL COORDINATION, SCHEDULE AND INTEGRATION

CERN Multimedia

A. Ball

Introduction and Schedule After nearly seven months of concentrated effort, the installation of services on YB0 moved off the CMS critical path in late November. In line with v36 planning provisions, the additional time needed to finish this challeng¬ing task was accommodated by reducing sequential dependencies between assembly tasks, putting more tasks (especially heavy logistic movements) in parallel with activities on, or within, the central wheel. Thus the lowering of wheels YB-1 and YB -2 and of disk YE-3 is already complete, the latter made possible, in the shadow of YB0 work, by inverting the order of the 3 endcap disks in the surface building. Weather conditions permitting, the Tracker will be transported to point 5 during CMS week for insertion in EB before CERN closes. The lowering of the last two disks will take place mid- and end-of January, respectively. Thus central beampipe installation can be confidently planned to start in February as foreseen, allowing closure of CMS in time for CRA...

Tank waste remediation system retrieval authorization basis amendment task plan

International Nuclear Information System (INIS)

Goetz, T.G.

1998-01-01

This task plan is a documented agreement between Nuclear Safety and Licensing and the Process Development group within the Waste Feed Delivery organization. The purpose of this task plan is to identify the scope of work, tasks and deliverables, responsibilities, manpower, and schedules associated with an authorization basis amendment as a result of the Waste Feed Waste Delivery Program, Project W-211, and Project W-TBD

Changed nursing scheduling for improved safety culture and working conditions - patients' and nurses' perspectives.

Science.gov (United States)

Kullberg, Anna; Bergenmar, Mia; Sharp, Lena

2016-05-01

To evaluate fixed scheduling compared with self-scheduling for nursing staff in oncological inpatient care with regard to patient and staff outcomes. Various scheduling models have been tested to attract and retain nursing staff. Little is known about how these schedules affect staff and patients. Fixed scheduling and self-scheduling have been studied to a small extent, solely from a staff perspective. We implemented fixed scheduling on two of four oncological inpatient wards. Two wards kept self-scheduling. Through a quasi-experimental design, baseline and follow-up measurements were collected among staff and patients. The Safety Attitudes Questionnaire was used among staff, as well as study-specific questions for patients and staff. Fixed scheduling was associated with less overtime and fewer possibilities to change shifts. Self-scheduling was associated with more requests from management for short notice shift changes. The type of scheduling did not affect patient-reported outcomes. Fixed scheduling should be considered in order to lower overtime. Further research is necessary and should explore patient outcomes to a greater extent. Scheduling is a core task for nurse managers. Our study suggests fixed scheduling as a strategy for managers to improve the effective use of resources and safety. © 2016 John Wiley & Sons Ltd.

Evaluation of Meta scheduler Architectures and Task assignment Policies for High throughput Computing

CERN Document Server

Caron, E; Tsaregorodtsev, A Yu

2006-01-01

In this paper we present a model and simulator for many clusters of heterogeneous PCs belonging to a local network. These clusters are assumed to be connected to each other through a global network and each cluster is managed via a local scheduler which is shared by many users. We validate our simulator by comparing the experimental and analytical results of a M/M/4 queuing system. These studies indicate that the simulator is consistent. Next, we do the comparison with a real batch system and we obtain an average error of 10.5\\% for the response time and 12\\% for the makespan. We conclude that the simulator is realistic and well describes the behaviour of a large-scale system. Thus we can study the scheduling of our system called \\dirac in a high throughput context. We justify our decentralized, adaptive and opportunistic approach in comparison to a centralized approach in such a context.

Extending an open-source real-time operating system with hierarchical scheduling

NARCIS (Netherlands)

Holenderski, M.J.; Cools, W.A.; Bril, R.J.; Lukkien, J.J.

2010-01-01

Hierarchical scheduling frameworks (HSFs) have been devised to support the integration of independently developed and analyzed subsystems. This paper presents an efficient, modular and extendible design for enhancing a real-time operating system with periodic tasks, two-level fixed-priority HSF

Optimization of horizontal microcode within and beyond basic blocks: an application of processor scheduling with resources

Energy Technology Data Exchange (ETDEWEB)

Fisher, J.A.

1979-10-01

Microprogram optimization is the rearrangement of microcode written vertically, with one operation issued per step, into legal horizontal microinstructions, in which several operations are issued each instruction cycle. The rearrangement is done in a way that approximately minimizes the running time of the code. This problem is identified with the problem of processor scheduling with resource constraints. Thus, the problem of optimizing basic blocks of microcode can be seen to be np-complete; however, approximate methods for basic blocks which have good records in other, similar scheduling environments can be used. In priority list scheduling the tasks are ordered according to some evaluation function, and then schedules are found by repeated scans of the list. Several evaluation functions are shown to perform very well on large samples of various classes of random data-precedence graphs with characteristics similar to those derived from microprograms. A method of spotting resource bottlenecks in the derived data-precedence graph enables one to obtain a resource-considerate evaluation function, in which tasks which contribute directly to or precede bottlenecks have their priorities raised. The complexity of the calculations necessary to compute the lower bound was greatly reduced. A method is suggested for optimizing beyond basic blocks. Groups of basic blocks are treated as if they were one block; the information necessary to control the motion of tasks between blocks is encoded as data-precedence constraints on the conditional tasks. Long paths of code can thus be optimized, with no back branches, by the same methods used for basic blocks. 9 figures, 6 tables.

Tank Waste Remediation System (TWRS) Retrieval Authorization Basis Amendment Task Plan

International Nuclear Information System (INIS)

HARRIS, J.P.

1999-01-01

This task plan is a documented agreement between Nuclear Safety and Licensing and Retrieval Engineering. The purpose of this task plan is to identify the scope of work, tasks and deliverables, responsibilities, manpower, and schedules associated with an authorization basis amendment as a result of the Waste Feed Delivery Program, Project W-211, Project W-521, and Project W-522

Constraint-based job shop scheduling with ILOG SCHEDULER

NARCIS (Netherlands)

Nuijten, W.P.M.; Le Pape, C.

1998-01-01

We introduce constraint-based scheduling and discuss its main principles. An approximation algorithm based on tree search is developed for the job shop scheduling problem using ILOG SCHEDULER. A new way of calculating lower bounds on the makespan of the job shop scheduling problem is presented and

Schedule-induced masseter EMG in facial pain subjects vs. no-pain controls.

Science.gov (United States)

Gramling, S E; Grayson, R L; Sullivan, T N; Schwartz, S

1997-02-01

Empirical reports suggest that oral habits (e.g., teeth clenching) may be behavioral mediators linking stress to muscle hyperreactivity and the development of facial pain. Another report suggests that excessive behavioral adjuncts develop in conjunction with fixed-time stimulus presentation. The present study assessed the extent to which the oral habits exhibited by facial pain patients are schedule-induced. Subjects with Temporomandibular Disorder (TMD) symptomatology (n = 15) and pain-free controls (n = 15) participated in a 4-phase experiment (adaptation, baseline, task, recovery) designed to elicit schedule-induced behaviors. Self-report of oral habits and negative affect were recorded after each phase. Objective measures of oral habits were obtained via behavioral observation and masseter EMG recordings. Results revealed that negative arousal significantly increased during the fixed-time (FT) task and was also associated with increased oral habits among the TMD subjects. Moreover, 40% of the TMD subjects and none of the controls exhibited a pattern of EMG elevations in the early part of the inter-stimulus interval that met a strict criteria for scheduled-induced behavior per se. Taken together, these results suggest that the TMD subjects were engaging in schedule-induced oral habits. The adjunctive behavior literature seems to provide a plausible explanation as to how oral habits develop and are maintained in TMD patients, despite their painful consequences.

Efficient Workplan Management in Maintenance Tasks

NARCIS (Netherlands)

Wilson, M.; Roos, N.; Huisman, B.; Witteveen, C.

2011-01-01

NedTrain is a Dutch company tasked with performing the maintenance of the rolling stock of the national railway company, NS. NedTrain owns several workshops at different locations. The scheduling in one such workshop will be taken as point of departure for the discussion in this paper. After

The nurse scheduling problem: a goal programming and nonlinear optimization approaches

Science.gov (United States)

Hakim, L.; Bakhtiar, T.; Jaharuddin

2017-01-01

Nurses scheduling is an activity of allocating nurses to conduct a set of tasks at certain room at a hospital or health centre within a certain period. One of obstacles in the nurse scheduling is the lack of resources in order to fulfil the needs of the hospital. Nurse scheduling which is undertaken manually will be at risk of not fulfilling some nursing rules set by the hospital. Therefore, this study aimed to perform scheduling models that satisfy all the specific rules set by the management of Bogor State Hospital. We have developed three models to overcome the scheduling needs. Model 1 is designed to schedule nurses who are solely assigned to a certain inpatient unit and Model 2 is constructed to manage nurses who are assigned to an inpatient room as well as at Polyclinic room as conjunct nurses. As the assignment of nurses on each shift is uneven, then we propose Model 3 to minimize the variance of the workload in order to achieve equitable assignment on every shift. The first two models are formulated in goal programming framework, while the last model is in nonlinear optimization form.

Nonstandard Work Schedules, Family Dynamics, and Mother-Child Interactions During Early Childhood.

Science.gov (United States)

Prickett, Kate C

2018-03-01

The rising number of parents who work nonstandard schedules has led to a growing body of research concerned with what this trend means for children. The negative outcomes for children of parents who work nonstandard schedules are thought to arise from the disruptions these schedules place on family life, and thus, the types of parenting that support their children's development, particularly when children are young. Using a nationally representative sample of two-parent families (Early Childhood Longitudinal Study-Birth cohort, n = 3,650), this study examined whether mothers' and their partners' nonstandard work schedules were associated with mothers' parenting when children were 2 and 4 years old. Structural equation models revealed that mothers' and their partners' nonstandard work schedules were associated with mothers' lower scores on measures of positive and involved parenting. These associations were mediated by fathers' lower levels of participation in cognitively supportive parenting and greater imbalance in cognitively supportive tasks conducted by mothers versus fathers.

Handling machine breakdown for dynamic scheduling by a colony of cognitive agents in a holonic manufacturing framework

Directory of Open Access Journals (Sweden)

T. K. Jana

2015-09-01

Full Text Available There is an ever increasing need of providing quick, yet improved solution to dynamic scheduling by better responsiveness following simple coordination mechanism to better adapt to the changing environments. In this endeavor, a cognitive agent based approach is proposed to deal with machine failure. A Multi Agent based Holonic Adaptive Scheduling (MAHoAS architecture is developed to frame the schedule by explicit communication between the product holons and the resource holons in association with the integrated process planning and scheduling (IPPS holon under normal situation. In the event of breakdown of a resource, the cooperation is sought by implicit communication. Inspired by the cognitive behavior of human being, a cognitive decision making scheme is proposed that reallocates the incomplete task to another resource in the most optimized manner and tries to expedite the processing in view of machine failure. A metamorphic algorithm is developed and implemented in Oracle 9i to identify the best candidate resource for task re-allocation. Integrated approach to process planning and scheduling realized under Multi Agent System (MAS framework facilitates dynamic scheduling with improved performance under such situations. The responsiveness of the resources having cognitive capabilities helps to overcome the adverse consequences of resource failure in a better way.

Nonstandard Maternal Work Schedules: Implications for African American Children’s Early Language Outcomes

OpenAIRE

Odom, Erika C.; Vernon-Feagans, Lynne; Crouter, Ann C.

2013-01-01

In this study, observed maternal positive engagement and perception of work-family spillover were examined as mediators of the association between maternal nonstandard work schedules and children’s expressive language outcomes in 231 African American families living in rural households. Mothers reported their work schedules when their child was 24 months of age and children’s expressive language development was assessed during a picture book task at 24 months and with a standardized assessmen...

Optimal task scheduling policy in energy harvesting wireless sensor networks

NARCIS (Netherlands)

Rao, Vijay S.; Prasad, R. Venkatesha; Niemegeers, Ignas G M M

2015-01-01

Ambient energy harvesting for Wireless Sensor Networks (WSNs) is being pitched as a promising solution for long-lasting deployments in various WSN applications. However, the sensor nodes most often do not have enough energy to handle application, network and house-keeping tasks because amount of

Deadline based scheduling for data-intensive applications in clouds

Institute of Scientific and Technical Information of China (English)

Fu Xiong; Cang Yeliang; Zhu Lipeng; Hu Bin; Deng Song; Wang Dong

2016-01-01

Cloud computing emerges as a new computing pattern that can provide elastic services for any users around the world.It provides good chances to solve large scale scientific problems with fewer efforts.Application deployment remains an important issue in clouds.Appropriate scheduling mechanisms can shorten the total completion time of an application and therefore improve the quality of service (QoS) for cloud users.Unlike current scheduling algorithms which mostly focus on single task allocation,we propose a deadline based scheduling approach for data-intensive applications in clouds.It does not simply consider the total completion time of an application as the sum of all its subtasks' completion time.Not only the computation capacity of virtual machine (VM) is considered,but also the communication delay and data access latencies are taken into account.Simulations show that our proposed approach has a decided advantage over the two other algorithms.

Asynchronous Task-Based Polar Decomposition on Manycore Architectures

KAUST Repository

Sukkari, Dalal

2016-10-25

This paper introduces the first asynchronous, task-based implementation of the polar decomposition on manycore architectures. Based on a new formulation of the iterative QR dynamically-weighted Halley algorithm (QDWH) for the calculation of the polar decomposition, the proposed implementation replaces the original and hostile LU factorization for the condition number estimator by the more adequate QR factorization to enable software portability across various architectures. Relying on fine-grained computations, the novel task-based implementation is also capable of taking advantage of the identity structure of the matrix involved during the QDWH iterations, which decreases the overall algorithmic complexity. Furthermore, the artifactual synchronization points have been severely weakened compared to previous implementations, unveiling look-ahead opportunities for better hardware occupancy. The overall QDWH-based polar decomposition can then be represented as a directed acyclic graph (DAG), where nodes represent computational tasks and edges define the inter-task data dependencies. The StarPU dynamic runtime system is employed to traverse the DAG, to track the various data dependencies and to asynchronously schedule the computational tasks on the underlying hardware resources, resulting in an out-of-order task scheduling. Benchmarking experiments show significant improvements against existing state-of-the-art high performance implementations (i.e., Intel MKL and Elemental) for the polar decomposition on latest shared-memory vendors\\' systems (i.e., Intel Haswell/Broadwell/Knights Landing, NVIDIA K80/P100 GPUs and IBM Power8), while maintaining high numerical accuracy.

Asynchronous Task-Based Polar Decomposition on Single Node Manycore Architectures

KAUST Repository

Sukkari, Dalal E.; Ltaief, Hatem; Faverge, Mathieu; Keyes, David E.

2017-01-01

This paper introduces the first asynchronous, task-based formulation of the polar decomposition and its corresponding implementation on manycore architectures. Based on a formulation of the iterative QR dynamically-weighted Halley algorithm (QDWH) for the calculation of the polar decomposition, the proposed implementation replaces the original LU factorization for the condition number estimator by the more adequate QR factorization to enable software portability across various architectures. Relying on fine-grained computations, the novel task-based implementation is capable of taking advantage of the identity structure of the matrix involved during the QDWH iterations, which decreases the overall algorithmic complexity. Furthermore, the artifactual synchronization points have been weakened compared to previous implementations, unveiling look-ahead opportunities for better hardware occupancy. The overall QDWH-based polar decomposition can then be represented as a directed acyclic graph (DAG), where nodes represent computational tasks and edges define the inter-task data dependencies. The StarPU dynamic runtime system is employed to traverse the DAG, to track the various data dependencies and to asynchronously schedule the computational tasks on the underlying hardware resources, resulting in an out-of-order task scheduling. Benchmarking experiments show significant improvements against existing state-of-the-art high performance implementations for the polar decomposition on latest shared-memory vendors' systems, while maintaining numerical accuracy.

Task rotation in an underground coal mine: A pilot study.

Science.gov (United States)

Jones, Olivia F; James, Carole L

2018-01-01

Task rotation is used to decrease the risk of workplace injuries and improve work satisfaction. To investigate the feasibility, benefits and challenges of implementing a task rotation schedule within an underground coalmine in NSW, Australia. A mixed method case control pilot study with the development and implementation of a task rotation schedule for 6 months with two work crews. A questionnaire including The Nordic Musculoskeletal Questionnaire, The Need for Recovery after Work Scale, and The Australian WHOQOL- BREF Australian Edition was used to survey workers at baseline, 3 and 6 months. A focus group was completed with the intervention crew and management at the completion of the study. In total, twenty-seven participants completed the survey. Significant improvements in the psychological and environmental domains of the WHOQOL-BREF questionnaire were found in the intervention crew. Musculoskeletal pain was highest in the elbow, lower back and knee, and fatigue scores improved, across both groups. The intervention crew felt 'mentally fresher', 'didn't do the same task twice in a row', and 'had more task variety which made the shift go quickly'. Task rotation was positively regarded, with psychological benefits identified. Three rotations during a 9-hour shift were feasible and practical in this environment.

Asynchronous Task-Based Polar Decomposition on Single Node Manycore Architectures

KAUST Repository

Sukkari, Dalal E.

2017-09-29

This paper introduces the first asynchronous, task-based formulation of the polar decomposition and its corresponding implementation on manycore architectures. Based on a formulation of the iterative QR dynamically-weighted Halley algorithm (QDWH) for the calculation of the polar decomposition, the proposed implementation replaces the original LU factorization for the condition number estimator by the more adequate QR factorization to enable software portability across various architectures. Relying on fine-grained computations, the novel task-based implementation is capable of taking advantage of the identity structure of the matrix involved during the QDWH iterations, which decreases the overall algorithmic complexity. Furthermore, the artifactual synchronization points have been weakened compared to previous implementations, unveiling look-ahead opportunities for better hardware occupancy. The overall QDWH-based polar decomposition can then be represented as a directed acyclic graph (DAG), where nodes represent computational tasks and edges define the inter-task data dependencies. The StarPU dynamic runtime system is employed to traverse the DAG, to track the various data dependencies and to asynchronously schedule the computational tasks on the underlying hardware resources, resulting in an out-of-order task scheduling. Benchmarking experiments show significant improvements against existing state-of-the-art high performance implementations for the polar decomposition on latest shared-memory vendors\\' systems, while maintaining numerical accuracy.

Resource-Optimal Scheduling Using Priced Timed Automata

DEFF Research Database (Denmark)

Larsen, Kim Guldstrand; Rasmussen, Jacob Illum; Subramani, K.

2004-01-01

In this paper, we show how the simple structure of the linear programs encountered during symbolic minimum-cost reachability analysis of priced timed automata can be exploited in order to substantially improve the performance of the current algorithm. The idea is rooted in duality of linear......-80 percent performance gain. As a main application area, we show how to solve energy-optimal task graph scheduling problems using the framework of priced timed automata....

Dwell scheduling algorithm based on analyzing scheduling interval for digital array radar%数字阵列雷达波束驻留调度间隔分析算法

Institute of Scientific and Technical Information of China (English)

赵洪涛; 程婷; 何子述

2011-01-01

针对数字阵列雷达波束驻留调度问题,研究了基于调度间隔分析的调度算法.该算法综合分析了1个调度间隔内申请执行的波束驻留任务,且调度过程中进行了脉冲交错.调度准则充分考虑了任务的工作方式优先级和截止期,并以任务丢失率、实现价值率、系统时间利用率作为评估指标.仿真结果表明修正截止期准则主要强调任务的紧迫性,修正工作方式优先级主要强调任务的重要性,而截止期--工作方式优先级和工作方式--截止期调度准则可以在二者间更好地折中,在总体性能上要优于其他调度准则.%Aiming at the problem of beam-dwell scheduling for digital array radar, the algorithm based on analyzing scheduling interval was studied. This algorithm analyzed the dwells applied to be executed in one scheduling interval and introduced pulse interleaving. The scheduling criterion took both priorities and deadlines into account fully, with the Task Drop Ratio, Hit Value Ratio, Time Utilization Ratio as evaluation indexes. The simulation results showed that the modified deadline criterion mainly emphasized the urgency of tasks, while the modified priority criterion mainly emphasized the importance of tasks; the deadline-priority and priority-deadline scheduling criterions could make good balance between urgency and importance. thus superior to other criterions in overall performances.

The application of artificial intelligence to astronomical scheduling problems

Science.gov (United States)

Johnston, Mark D.

1992-01-01

Efficient utilization of expensive space- and ground-based observatories is an important goal for the astronomical community; the cost of modern observing facilities is enormous, and the available observing time is much less than the demand from astronomers around the world. The complexity and variety of scheduling constraints and goals has led several groups to investigate how artificial intelligence (AI) techniques might help solve these kinds of problems. The earliest and most successful of these projects was started at Space Telescope Science Institute in 1987 and has led to the development of the Spike scheduling system to support the scheduling of Hubble Space Telescope (HST). The aim of Spike at STScI is to allocate observations to timescales of days to a week observing all scheduling constraints and maximizing preferences that help ensure that observations are made at optimal times. Spike has been in use operationally for HST since shortly after the observatory was launched in Apr. 1990. Although developed specifically for HST scheduling, Spike was carefully designed to provide a general framework for similar (activity-based) scheduling problems. In particular, the tasks to be scheduled are defined in the system in general terms, and no assumptions about the scheduling timescale are built in. The mechanisms for describing, combining, and propagating temporal and other constraints and preferences are quite general. The success of this approach has been demonstrated by the application of Spike to the scheduling of other satellite observatories: changes to the system are required only in the specific constraints that apply, and not in the framework itself. In particular, the Spike framework is sufficiently flexible to handle both long-term and short-term scheduling, on timescales of years down to minutes or less. This talk will discuss recent progress made in scheduling search techniques, the lessons learned from early HST operations, the application of Spike

Refinery scheduling

Energy Technology Data Exchange (ETDEWEB)

Magalhaes, Marcus V.; Fraga, Eder T. [PETROBRAS, Rio de Janeiro, RJ (Brazil); Shah, Nilay [Imperial College, London (United Kingdom)

2004-07-01

This work addresses the refinery scheduling problem using mathematical programming techniques. The solution adopted was to decompose the entire refinery model into a crude oil scheduling and a product scheduling problem. The envelope for the crude oil scheduling problem is composed of a terminal, a pipeline and the crude area of a refinery, including the crude distillation units. The solution method adopted includes a decomposition technique based on the topology of the system. The envelope for the product scheduling comprises all tanks, process units and products found in a refinery. Once crude scheduling decisions are Also available the product scheduling is solved using a rolling horizon algorithm. All models were tested with real data from PETROBRAS' REFAP refinery, located in Canoas, Southern Brazil. (author)

Optimal distribution of reactivity excess in a system of reactors operating at a variable loading schedule

International Nuclear Information System (INIS)

Bolsunov, A.A.; Zagrebaev, A.M.; Naumov, V.I.

1979-01-01

Considered is the task of reactivity excess distribution optimization in the system of reactors for the purpose of minimazing the summary power production losses at the fixed loading schedule. Mathematical formulation of the task is presented. Given are the curves, characterizing the dependence of possible degree of the reactor power drop on reactivity excees for non-stationary Xe poisoning at different nominal density of neutron flux. Analyzing the results, it is concluded that in case, when the reactors differ only in neutron flux density the reactor with lower neutron flux density should be involved in the variable operation schedule first as the poisoning of this reactor will be less, and therefore, the losses of the system power production will be less. It is advisable to reserve the reactivity excess in the reactor with greater power or in the reactor with higher burnup rate. It is stressed that the obtained results of the optimization task solution point out the possibility of obtaining the certain ecomonic effect and permit to correct the requirements on mobility of separate power units at system approach to NPP operation in a variable loading schedule

Task Classification Based Energy-Aware Consolidation in Clouds

Directory of Open Access Journals (Sweden)

HeeSeok Choi

2016-01-01

Full Text Available We consider a cloud data center, in which the service provider supplies virtual machines (VMs on hosts or physical machines (PMs to its subscribers for computation in an on-demand fashion. For the cloud data center, we propose a task consolidation algorithm based on task classification (i.e., computation-intensive and data-intensive and resource utilization (e.g., CPU and RAM. Furthermore, we design a VM consolidation algorithm to balance task execution time and energy consumption without violating a predefined service level agreement (SLA. Unlike the existing research on VM consolidation or scheduling that applies none or single threshold schemes, we focus on a double threshold (upper and lower scheme, which is used for VM consolidation. More specifically, when a host operates with resource utilization below the lower threshold, all the VMs on the host will be scheduled to be migrated to other hosts and then the host will be powered down, while when a host operates with resource utilization above the upper threshold, a VM will be migrated to avoid using 100% of resource utilization. Based on experimental performance evaluations with real-world traces, we prove that our task classification based energy-aware consolidation algorithm (TCEA achieves a significant energy reduction without incurring predefined SLA violations.

The Token Economy: Reducing the Disruptive and Off-Task Behavior

Science.gov (United States)

Chevalier, Nicole Taylor

2012-01-01

This study investigates the effects of a token economy as an intervention to reduce disruptive and off-task behavior of third grade students in an open concept setting. The intervention combines the use of a token reinforcement with a raffle style drawing. The students receive tokens on an intermittent reinforcement schedule for being on-task,…

tms-sim – Timing Models Scheduling Simulation Framework – Release 2016-07

OpenAIRE

Kluge, Florian

2016-01-01

tms-sim is a framework for the simulation and evaluation of scheduling algorithms. It is being developed to support our work on real-time task scheduling based on time-utility and history-cognisant utility functions. We publish tms-sim under the conditions of the GNU GPL to make our results reproducible and in the hope that it may be useful for others. This report describes the usage of the TMS framework libraries and how they can be used to build further simulation environments. It is not in...

TECHNICAL COORDINATION SCHEDULE & INTEGRATION

CERN Multimedia

W. Zeuner

Introduction The endgame of CMS installation in the underground cavern is in full swing, with several major milestones having been passed since the last CMS week. The Tracker was installed inside the Vactank just before the CERN end-of-year shutdown. Shortly after the reopening in 2008, the two remaining endcap disks, YE-2 and YE-1, were lowered, marking the completion of eight years of assembly in the surface building SX5. The remaining tasks, before the detector can be closed for the Cosmic Run At Four Tesla (CRAFT), are the installation of the thermal shields, the cabling of the negative endcap, the cabling of the tracker and the beam pipe installation. In addition to these installation tasks, a test closure of the positive endcap is planned just before the installation of the central beam pipe. The schedule is tight and complicated but the goal to close CMS by the end of May for a cosmic test with magnetic field remains feasible. Safety With all large components now being underground, the shortage...

River Protection Double-Shell Tank Waste Retrieval Authorization Basis Amendment Task Plan

International Nuclear Information System (INIS)

HARRIS, J.P.

2000-01-01

This task plan is a documented agreement between Nuclear Safety and Licensing and Retrieval Engineering. The purpose of this task plan is to identify the scope of work, tasks and deliverables, responsibilities, manpower, and schedules associated with an authorization basis amendment as a result of the Waste Feed Delivery Program, Project W-211, Project W-521, and Project W-522

Electricity usage scheduling in smart building environments using smart devices.

Science.gov (United States)

Lee, Eunji; Bahn, Hyokyung

2013-01-01

With the recent advances in smart grid technologies as well as the increasing dissemination of smart meters, the electricity usage of every moment can be detected in modern smart building environments. Thus, the utility company adopts different price of electricity at each time slot considering the peak time. This paper presents a new electricity usage scheduling algorithm for smart buildings that adopts real-time pricing of electricity. The proposed algorithm detects the change of electricity prices by making use of a smart device and changes the power mode of each electric device dynamically. Specifically, we formulate the electricity usage scheduling problem as a real-time task scheduling problem and show that it is a complex search problem that has an exponential time complexity. An efficient heuristic based on genetic algorithms is performed on a smart device to cut down the huge searching space and find a reasonable schedule within a feasible time budget. Experimental results with various building conditions show that the proposed algorithm reduces the electricity charge of a smart building by 25.6% on average and up to 33.4%.

A Recovery Model for Production Scheduling: Combination of Disruption Management and Internet of Things

Directory of Open Access Journals (Sweden)

Yang Jiang

2016-01-01

Full Text Available It is difficult to generate the new schedule effectively for minimizing the negative impact when an unanticipated disruption occurs after a subset of tasks has been finished in production scheduling. In such cases, continuing with the original schedule may not be optimal or feasible. Based on disruption management and Internet of things (IoT, this study designs a real-time status analyzer to identify the disruption and propose a recovery model to deal with the disruption. The computational result proves that our algorithm is competitive with the existing heuristics. Furthermore, due to the tradeoff between all participators (mainly including customers, managers of production enterprise, and workers involved in production scheduling, our model is more effective than the total rescheduling and right-shift rescheduling.

Using All-Sky Imaging to Improve Telescope Scheduling (Abstract)

Science.gov (United States)

Cole, G. M.

2017-12-01

(Abstract only) Automated scheduling makes it possible for a small telescope to observe a large number of targets in a single night. But when used in areas which have less-than-perfect sky conditions such automation can lead to large numbers of observations of clouds and haze. This paper describes the development of a "sky-aware" telescope automation system that integrates the data flow from an SBIG AllSky340c camera with an enhanced dispatch scheduler to make optimum use of the available observing conditions for two highly instrumented backyard telescopes. Using the minute-by-minute time series image stream and a self-maintained reference database, the software maintains a file of sky brightness, transparency, stability, and forecasted visibility at several hundred grid positions. The scheduling software uses this information in real time to exclude targets obscured by clouds and select the best observing task, taking into account the requirements and limits of each instrument.

Compilation time analysis to minimize run-time overhead in preemptive scheduling on multiprocessors

Science.gov (United States)

Wauters, Piet; Lauwereins, Rudy; Peperstraete, J.

1994-10-01

This paper describes a scheduling method for hard real-time Digital Signal Processing (DSP) applications, implemented on a multi-processor. Due to the very high operating frequencies of DSP applications (typically hundreds of kHz) runtime overhead should be kept as small as possible. Because static scheduling introduces very little run-time overhead it is used as much as possible. Dynamic pre-emption of tasks is allowed if and only if it leads to better performance in spite of the extra run-time overhead. We essentially combine static scheduling with dynamic pre-emption using static priorities. Since we are dealing with hard real-time applications we must be able to guarantee at compile-time that all timing requirements will be satisfied at run-time. We will show that our method performs at least as good as any static scheduling method. It also reduces the total amount of dynamic pre-emptions compared with run time methods like deadline monotonic scheduling.

Congestion Control and Traffic Scheduling for Collaborative Crowdsourcing in SDN Enabled Mobile Wireless Networks

Directory of Open Access Journals (Sweden)

Dawei Shen

2018-01-01

Full Text Available Currently, a number of crowdsourcing-based mobile applications have been implemented in mobile networks and Internet of Things (IoT, targeted at real-time services and recommendation. The frequent information exchanges and data transmissions in collaborative crowdsourcing are heavily injected into the current communication networks, which poses great challenges for Mobile Wireless Networks (MWN. This paper focuses on the traffic scheduling and load balancing problem in software-defined MWN and designs a hybrid routing forwarding scheme as well as a congestion control algorithm to achieve the feasible solution. The traffic scheduling algorithm first sorts the tasks in an ascending order depending on the amount of tasks and then solves it using a greedy scheme. In the proposed congestion control scheme, the traffic assignment is first transformed into a multiknapsack problem, and then the Artificial Fish Swarm Algorithm (AFSA is utilized to solve this problem. Numerical results on practical network topology reveal that, compared with the traditional schemes, the proposed congestion control and traffic scheduling schemes can achieve load balancing, reduce the probability of network congestion, and improve the network throughput.

A software-based technique enabling composable hierarchical preemptive scheduling for time-triggered applications

NARCIS (Netherlands)

Nejad, A.B.; Molnos, A.; Goossens, K.G.W.

2013-01-01

Many embedded real-time applications are typically time-triggered and preemptive schedulers are used to execute tasks of such applications. Orthogonally, composable partitioned embedded platforms use preemptive time-division multiplexing mechanism to isolate applications. Existing composable systems

Heuristic Method for Decision-Making in Common Scheduling Problems

Directory of Open Access Journals (Sweden)

Edyta Kucharska

2017-10-01

Full Text Available The aim of the paper is to present a heuristic method for decision-making regarding an NP-hard scheduling problem with limitations related to tasks and the resources dependent on the current state of the process. The presented approach is based on the algebraic-logical meta-model (ALMM, which enables making collective decisions in successive process stages, not separately for individual objects or executors. Moreover, taking into account the limitations of the problem, it involves constructing only an acceptable solution and significantly reduces the amount of calculations. A general algorithm based on the presented method is composed of the following elements: preliminary analysis of the problem, techniques for the choice of decision at a given state, the pruning non-perspective trajectory, selection technique of the initial state for the trajectory final part, and the trajectory generation parameters modification. The paper includes applications of the presented approach to scheduling problems on unrelated parallel machines with a deadline and machine setup time dependent on the process state, where the relationship between tasks is defined by the graph. The article also presents the results of computational experiments.

Constraint optimization model of a scheduling problem for a robotic arm in automatic systems

DEFF Research Database (Denmark)

Kristiansen, Ewa; Smith, Stephen F.; Kristiansen, Morten

2014-01-01

are characteristics of the painting process application itself. Unlike spot-welding, painting tasks require movement of the entire robot arm. In addition to minimizing intertask duration, the scheduler must strive to maximize painting quality and the problem is formulated as a multi-objective optimization problem....... The scheduling model is implemented as a stand-alone module using constraint programming, and integrated with a larger automatic system. The results of a number of simulation experiments with simple parts are reported, both to characterize the functionality of the scheduler and to illustrate the operation...... of the entire software system for automatic generation of robot programs for painting....

ARTiS, an Asymmetric Real-Time Scheduler for Linux on Multi-Processor Architectures

OpenAIRE

Piel , Éric; Marquet , Philippe; Soula , Julien; Osuna , Christophe; Dekeyser , Jean-Luc

2005-01-01

The ARTiS system is a real-time extension of the GNU/Linux scheduler dedicated to SMP (Symmetric Multi-Processors) systems. It allows to mix High Performance Computing and real-time. ARTiS exploits the SMP architecture to guarantee the preemption of a processor when the system has to schedule a real-time task. The implementation is available as a modification of the Linux kernel, especially focusing (but not restricted to) IA-64 architecture. The basic idea of ARTiS is to assign a selected se...

An Evaluation of the Value of Choice-Making Opportunities in Single-Operant Arrangements: Simple Fixed- and Progressive-Ratio Schedules

Science.gov (United States)

Tiger, Jeffrey H.; Toussaint, Karen A.; Roath, Christopher T.

2010-01-01

The current study compared the effects of choice and no-choice reinforcement conditions on the task responding of 3 children with autism across 2 single-operant paradigm reinforcer assessments. The first assessment employed simple fixed-ratio (FR) schedules; the second used progressive-ratio (PR) schedules. The latter assessment identified the…

HURON (HUman and Robotic Optimization Network) Multi-Agent Temporal Activity Planner/Scheduler

Science.gov (United States)

Hua, Hook; Mrozinski, Joseph J.; Elfes, Alberto; Adumitroaie, Virgil; Shelton, Kacie E.; Smith, Jeffrey H.; Lincoln, William P.; Weisbin, Charles R.

2012-01-01

HURON solves the problem of how to optimize a plan and schedule for assigning multiple agents to a temporal sequence of actions (e.g., science tasks). Developed as a generic planning and scheduling tool, HURON has been used to optimize space mission surface operations. The tool has also been used to analyze lunar architectures for a variety of surface operational scenarios in order to maximize return on investment and productivity. These scenarios include numerous science activities performed by a diverse set of agents: humans, teleoperated rovers, and autonomous rovers. Once given a set of agents, activities, resources, resource constraints, temporal constraints, and de pendencies, HURON computes an optimal schedule that meets a specified goal (e.g., maximum productivity or minimum time), subject to the constraints. HURON performs planning and scheduling optimization as a graph search in state-space with forward progression. Each node in the graph contains a state instance. Starting with the initial node, a graph is automatically constructed with new successive nodes of each new state to explore. The optimization uses a set of pre-conditions and post-conditions to create the children states. The Python language was adopted to not only enable more agile development, but to also allow the domain experts to easily define their optimization models. A graphical user interface was also developed to facilitate real-time search information feedback and interaction by the operator in the search optimization process. The HURON package has many potential uses in the fields of Operations Research and Management Science where this technology applies to many commercial domains requiring optimization to reduce costs. For example, optimizing a fleet of transportation truck routes, aircraft flight scheduling, and other route-planning scenarios involving multiple agent task optimization would all benefit by using HURON.

Data location-aware job scheduling in the grid. Application to the GridWay metascheduler

International Nuclear Information System (INIS)

Delgado Peris, Antonio; Hernandez, Jose; Huedo, Eduardo; Llorente, Ignacio M

2010-01-01

Grid infrastructures constitute nowadays the core of the computing facilities of the biggest LHC experiments. These experiments produce and manage petabytes of data per year and run thousands of computing jobs every day to process that data. It is the duty of metaschedulers to allocate the tasks to the most appropriate resources at the proper time. Our work reviews the policies that have been proposed for the scheduling of grid jobs in the context of very data-intensive applications. We indicate some of the practical problems that such models will face and describe what we consider essential characteristics of an optimum scheduling system: aim to minimise not only job turnaround time but also data replication, flexibility to support different virtual organisation requirements and capability to coordinate the tasks of data placement and job allocation while keeping their execution decoupled. These ideas have guided the development of an enhanced prototype for GridWay, a general purpose metascheduler, part of the Globus Toolkit and member of the EGEE's RESPECT program. Current GridWay's scheduling algorithm is unaware of data location. Our prototype makes it possible for job requests to set data needs not only as absolute requirements but also as functions for resource ranking. As our tests show, this makes it more flexible than currently used resource brokers to implement different data-aware scheduling algorithms.

Engineering Task Plan for Hepa Filter Differential Pressure (DP) Fan Interlock Upgrades

International Nuclear Information System (INIS)

SIMONS, S.R.

2000-01-01

This document provides a plan for installation of Differential Pressure (DP) fan interlocks on the primary ventilation systems in selected Tank Farm facilities. This plan contains the engineering tasks required for installation and is summarized by the Acceptance for Beneficial Use list. Individuals responsible for each task are identified and scheduled accordingly

Flexible Data-Aware Scheduling for Workflows over an In-Memory Object Store

Energy Technology Data Exchange (ETDEWEB)

Duro, Francisco Rodrigo; Garcia Blas, Javier; Isaila, Florin; Wozniak, Justin M.; Carretero, Jesus; Ross, Rob

2016-01-01

This paper explores novel techniques for improving the performance of many-task workflows based on the Swift scripting language. We propose novel programmer options for automated distributed data placement and task scheduling. These options trigger a data placement mechanism used for distributing intermediate workflow data over the servers of Hercules, a distributed key-value store that can be used to cache file system data. We demonstrate that these new mechanisms can significantly improve the aggregated throughput of many-task workflows with up to 86x, reduce the contention on the shared file system, exploit the data locality, and trade off locality and load balance.

Information Flow Scheduling in Concurrent Multi-Product Development Based on DSM

Science.gov (United States)

Sun, Qing-Chao; Huang, Wei-Qiang; Jiang, Ying-Jie; Sun, Wei

2017-09-01

Multi-product collaborative development is adopted widely in manufacturing enterprise, while the present multi-project planning models don't take technical/data interactions of multiple products into account. To decrease the influence of technical/data interactions on project progresses, the information flow scheduling models based on the extended DSM is presented. Firstly, information dependencies are divided into four types: series, parallel, coupling and similar. Secondly, different types of dependencies are expressed as DSM units, and the extended DSM model is brought forward, described as a block matrix. Furthermore, the information flow scheduling methods is proposed, which involves four types of operations, where partitioning and clustering algorithm are modified from DSM for ensuring progress of high-priority project, merging and converting is the specific computation of the extended DSM. Finally, the information flow scheduling of two machine tools development is analyzed with example, and different project priorities correspond to different task sequences and total coordination cost. The proposed methodology provides a detailed instruction for information flow scheduling in multi-product development, with specially concerning technical/data interactions.

Decommissioning strategy and schedule for a multiple reactor nuclear power plant site

Energy Technology Data Exchange (ETDEWEB)

Monteiro, Deiglys Borges; Moreira, Joao M.L.; Maiorino, Jose Rubens, E-mail: deiglys.monteiro@ufabc.edu.br, E-mail: joao.moreira@ufabc.edu.br, E-mail: joserubens.maiorino@ufabc.edu.br [Universidade Federal do ABC (CECS/UFABC), Santo Andre, SP (Brazil). Centro de Engenharia, Modelagem e Ciencias Aplicadas

2015-07-01

The decommissioning is an important part of every Nuclear Power Plant life cycle gaining importance when there are more than one plant at the same site due to interactions that can arise from the operational ones and a decommissioning plant. In order to prevent undesirable problems, a suitable strategy and a very rigorous schedule should implemented and carried. In this way, decommissioning tasks such as fully decontamination and dismantling of activated and contaminated systems, rooms and structures could be delayed, posing as an interesting option to multiple reactor sites. The present work aims to purpose a strategy and a schedule for the decommissioning of a multiple reactor site highlighting the benefits of delay operational tasks and constructs some auxiliary services in the site during the stand by period of the shutdown plants. As a case study, will be presented a three-reactor site which the decommissioning process actually is in planning stage and that should start in the next decade. (author)

Decommissioning strategy and schedule for a multiple reactor nuclear power plant site

International Nuclear Information System (INIS)

Monteiro, Deiglys Borges; Moreira, Joao M.L.; Maiorino, Jose Rubens

2015-01-01

The decommissioning is an important part of every Nuclear Power Plant life cycle gaining importance when there are more than one plant at the same site due to interactions that can arise from the operational ones and a decommissioning plant. In order to prevent undesirable problems, a suitable strategy and a very rigorous schedule should implemented and carried. In this way, decommissioning tasks such as fully decontamination and dismantling of activated and contaminated systems, rooms and structures could be delayed, posing as an interesting option to multiple reactor sites. The present work aims to purpose a strategy and a schedule for the decommissioning of a multiple reactor site highlighting the benefits of delay operational tasks and constructs some auxiliary services in the site during the stand by period of the shutdown plants. As a case study, will be presented a three-reactor site which the decommissioning process actually is in planning stage and that should start in the next decade. (author)

Limited preemptive scheduling of mixed time-triggered and event-triggered tasks

NARCIS (Netherlands)

Heuvel, van den M.M.H.P.; Bril, R.J.; Zhang, X.; Abdullah, S.M.J.; Isovic, D.

2013-01-01

Many embedded systems have complex timing constraints and, at the same time, have flexibility requirements which prohibit offline planning of the entire system. To support a mixture of time-triggered and event-triggered tasks, some industrial systems deploy a table-driven dispatcher for

Secure Autonomous Automated Scheduling (SAAS). Rev. 1.1

Science.gov (United States)

Walke, Jon G.; Dikeman, Larry; Sage, Stephen P.; Miller, Eric M.

2010-01-01

This report describes network-centric operations, where a virtual mission operations center autonomously receives sensor triggers, and schedules space and ground assets using Internet-based technologies and service-oriented architectures. For proof-of-concept purposes, sensor triggers are received from the United States Geological Survey (USGS) to determine targets for space-based sensors. The Surrey Satellite Technology Limited (SSTL) Disaster Monitoring Constellation satellite, the UK-DMC, is used as the space-based sensor. The UK-DMC's availability is determined via machine-to-machine communications using SSTL's mission planning system. Access to/from the UK-DMC for tasking and sensor data is via SSTL's and Universal Space Network's (USN) ground assets. The availability and scheduling of USN's assets can also be performed autonomously via machine-to-machine communications. All communication, both on the ground and between ground and space, uses open Internet standards

An effective repetitive training schedule to achieve skill proficiency using a novel robotic virtual reality simulator.

Science.gov (United States)

Kang, Sung Gu; Ryu, Byung Ju; Yang, Kyung Sook; Ko, Young Hwii; Cho, Seok; Kang, Seok Ho; Patel, Vipul R; Cheon, Jun

2015-01-01

A robotic virtual reality simulator (Mimic dV-Trainer) can be a useful training method for the da Vinci surgical system. Herein, we investigate several repetitive training schedules and determine which is the most effective. A total of 30 medical students were enrolled and were divided into 3 groups according to the training schedule. Group 1 performed the task 1 hour daily for 4 consecutive days, group II performed the task on once per week for 1 hour for 4 consecutive weeks, and group III performed the task for 4 consecutive hours in 1 day. The effects of training were investigated by analyzing the number of repetitions and the time required to complete the "Tube 2" simulation task when the learning curve plateau was reached. The point at which participants reached a stable score was evaluated using the cumulative sum control graph. The average time to complete the task at the learning curve plateau was 150.3 seconds in group I, 171.9 seconds in group II, and 188.5 seconds in group III. The number of task repetitions required to reach the learning curve plateau was 45 repetitions in group I, 36 repetitions in group II, and 39 repetitions in group III. Therefore, there was continuous improvement in the time required to perform the task after 40 repetitions in group I only. There was a significant correlation between improvement in each trial interval and attempt, and the correlation coefficient (0.924) in group I was higher than that in group II (0.899) and group III (0.838). Daily 1-hour practice sessions performed for 4 consecutive days resulted in the best final score, continuous score improvement, and effective training while minimizing fatigue. This repetition schedule can be used for effectively training novices in future. Copyright © 2015 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Optimized Waterspace Management and Scheduling Using Mixed-Integer Linear Programming

Science.gov (United States)

2016-01-01

PANAMA CITY DIVISION PANAMA CITY, FLORIDA 32407-7001 5(3257...task. This paper is outlined as follows: in Section 2, we discuss the general setup of the the MCM scheduling problem, including the definition of the...Suite 1425 Arlington, VA 22203-1995 Naval Surface Warfare Center, Panama City Division 1 ATTN: Technical Library 110 Vernon Avenue Panama City, FL 32407 27

Re-scheduling nursing shifts: Scoping the challenge and examining the potential of mathematical model based tools

OpenAIRE

Clark, A.; Moule, P.; Topping, A.; Serpell, M.

2015-01-01

Aims: To review research in the literature on nursing shift scheduling/rescheduling, and report key issues identified in a listening exercise with managers in four English NHS trusts to inform the development of mathematical tools for rescheduling decision-making.\\ud Background: Shift rescheduling is unrecognised as an everyday time-consuming management task with different imperatives than scheduling. Poor rescheduling decisions can have quality, cost and morale implications.\\ud Evaluation: A...

HOROPLAN: computer-assisted nurse scheduling using constraint-based programming.

Science.gov (United States)

Darmoni, S J; Fajner, A; Mahé, N; Leforestier, A; Vondracek, M; Stelian, O; Baldenweck, M

1995-01-01

Nurse scheduling is a difficult and time consuming task. The schedule has to determine the day to day shift assignments of each nurse for a specified period of time in a way that satisfies the given requirements as much as possible, taking into account the wishes of nurses as closely as possible. This paper presents a constraint-based, artificial intelligence approach by describing a prototype implementation developed with the Charme language and the first results of its use in the Rouen University Hospital. Horoplan implements a non-cyclical constraint-based scheduling, using some heuristics. Four levels of constraints were defined to give a maximum of flexibility: French level (e.g. number of worked hours in a year), hospital level (e.g. specific day-off), department level (e.g. specific shift) and care unit level (e.g. specific pattern for week-ends). Some constraints must always be verified and can not be overruled and some constraints can be overruled at a certain cost. Rescheduling is possible at any time specially in case of an unscheduled absence.

Parallel Task Processing on a Multicore Platform in a PC-based Control System for Parallel Kinematics

Directory of Open Access Journals (Sweden)

Harald Michalik

2009-02-01

Full Text Available Multicore platforms are such that have one physical processor chip with multiple cores interconnected via a chip level bus. Because they deliver a greater computing power through concurrency, offer greater system density multicore platforms provide best qualifications to address the performance bottleneck encountered in PC-based control systems for parallel kinematic robots with heavy CPU-load. Heavy load control tasks are generated by new control approaches that include features like singularity prediction, structure control algorithms, vision data integration and similar tasks. In this paper we introduce the parallel task scheduling extension of a communication architecture specially tailored for the development of PC-based control of parallel kinematics. The Sche-duling is specially designed for the processing on a multicore platform. It breaks down the serial task processing of the robot control cycle and extends it with parallel task processing paths in order to enhance the overall control performance.

Instructions, multiple schedules, and extinction: Distinguishing rule-governed from schedule-controlled behavior.

Science.gov (United States)

Hayes, S C; Brownstein, A J; Haas, J R; Greenway, D E

1986-09-01

Schedule sensitivity has usually been examined either through a multiple schedule or through changes in schedules after steady-state responding has been established. This study compared the effects of these two procedures when various instructions were given. Fifty-five college students responded in two 32-min sessions under a multiple fixed-ratio 18/differential-reinforcement-of-low-rate 6-s schedule, followed by one session of extinction. Some subjects received no instructions regarding the appropriate rates of responding, whereas others received instructions to respond slowly, rapidly, or both. Relative to the schedule in operation, the instructions were minimal, partially inaccurate, or accurate. When there was little schedule sensitivity in the multiple schedule, there was little in extinction. When apparently schedule-sensitive responding occurred in the multiple schedule, however, sensitivity in extinction occurred only if differential responding in the multiple schedule could not be due to rules supplied by the experimenter. This evidence shows that rule-governed behavior that occurs in the form of schedule-sensitive behavior may not in fact become schedule-sensitive even though it makes contact with the scheduled reinforcers.

Assessing and Increasing Staff Preference for Job Tasks Using Concurrent-Chains Schedules and Probabilistic Outcomes

Science.gov (United States)

Reed, Derek D.; DiGennaro Reed, Florence D.; Campisano, Natalie; Lacourse, Kristen; Azulay, Richard L.

2012-01-01

The assessment and improvement of staff members' subjective valuation of nonpreferred work tasks may be one way to increase the quality of staff members' work life. The Task Enjoyment Motivation Protocol (Green, Reid, Passante, & Canipe, 2008) provides a process for supervisors to identify the aversive qualities of nonpreferred job tasks.…

Minimum Time Path Planning for Robotic Manipulator in Drilling/ Spot Welding Tasks

Directory of Open Access Journals (Sweden)

Qiang Zhang

2016-04-01

Full Text Available In this paper, a minimum time path planning strategy is proposed for multi points manufacturing problems in drilling/spot welding tasks. By optimizing the travelling schedule of the set points and the detailed transfer path between points, the minimum time manufacturing task is realized under fully utilizing the dynamic performance of robotic manipulator. According to the start-stop movement in drilling/spot welding task, the path planning problem can be converted into a traveling salesman problem (TSP and a series of point to point minimum time transfer path planning problems. Cubic Hermite interpolation polynomial is used to parameterize the transfer path and then the path parameters are optimized to obtain minimum point to point transfer time. A new TSP with minimum time index is constructed by using point-point transfer time as the TSP parameter. The classical genetic algorithm (GA is applied to obtain the optimal travelling schedule. Several minimum time drilling tasks of a 3-DOF robotic manipulator are used as examples to demonstrate the effectiveness of the proposed approach.

Task Migration for Fault-Tolerance in Mixed-Criticality Embedded Systems

DEFF Research Database (Denmark)

Saraswat, Prabhat Kumar; Pop, Paul; Madsen, Jan

2009-01-01

In this paper we are interested in mixed-criticality embedded applications implemented on distributed architectures. Depending on their time-criticality, tasks can be hard or soft real-time and regarding safety-criticality, tasks can be fault-tolerant to transient faults, permanent faults, or have...... processors, such that the faults are tolerated, the deadlines for the hard real-time tasks are satisfied and the QoS for soft tasks is maximized. The proposed online adaptive approach has been evaluated using several synthetic benchmarks and a real-life case study....... no dependability requirements. We use Earliest Deadline First (EDF) scheduling for the hard tasks and the Constant Bandwidth Server (CBS) for the soft tasks. The CBS parameters determine the quality of service (QoS) of soft tasks. Transient faults are tolerated using checkpointing with roll- back recovery...

E-Token Energy-Aware Proportionate Sharing Scheduling Algorithm for Multiprocessor Systems

Directory of Open Access Journals (Sweden)

Pasupuleti Ramesh

2017-01-01

Full Text Available WSN plays vital role from small range healthcare surveillance systems to largescale environmental monitoring. Its design for energy constrained applications is a challenging issue. Sensors in WSNs are projected to run separately for longer periods. It is of excessive cost to substitute exhausted batteries which is not even possible in antagonistic situations. Multiprocessors are used in WSNs for high performance scientific computing, where each processor is assigned the same or different workload. When the computational demands of the system increase then the energy efficient approaches play an important role to increase system lifetime. Energy efficiency is commonly carried out by using proportionate fair scheduler. This introduces abnormal overloading effect. In order to overcome the existing problems E-token Energy-Aware Proportionate Sharing (EEAPS scheduling is proposed here. The power consumption for each thread/task is calculated and the tasks are allotted to the multiple processors through the auctioning mechanism. The algorithm is simulated by using the real-time simulator (RTSIM and the results are tested.

Algorithm of composing the schedule of construction and installation works

Science.gov (United States)

Nehaj, Rustam; Molotkov, Georgij; Rudchenko, Ivan; Grinev, Anatolij; Sekisov, Aleksandr

2017-10-01

An algorithm for scheduling works is developed, in which the priority of the work corresponds to the total weight of the subordinate works, the vertices of the graph, and it is proved that for graphs of the tree type the algorithm is optimal. An algorithm is synthesized to reduce the search for solutions when drawing up schedules of construction and installation works, allocating a subset with the optimal solution of the problem of the minimum power, which is determined by the structure of its initial data and numerical values. An algorithm for scheduling construction and installation work is developed, taking into account the schedule for the movement of brigades, which is characterized by the possibility to efficiently calculate the values of minimizing the time of work performance by the parameters of organizational and technological reliability through the use of the branch and boundary method. The program of the computational algorithm was compiled in the MatLAB-2008 program. For the initial data of the matrix, random numbers were taken, uniformly distributed in the range from 1 to 100. It takes 0.5; 2.5; 7.5; 27 minutes to solve the problem. Thus, the proposed method for estimating the lower boundary of the solution is sufficiently accurate and allows efficient solution of the minimax task of scheduling construction and installation works.

DIMACS Workshop on Interconnection Networks and Mapping, and Scheduling Parallel Computations

CERN Document Server

Rosenberg, Arnold L; Sotteau, Dominique; NSF Science and Technology Center in Discrete Mathematics and Theoretical Computer Science; Interconnection networks and mapping and scheduling parallel computations

1995-01-01

The interconnection network is one of the most basic components of a massively parallel computer system. Such systems consist of hundreds or thousands of processors interconnected to work cooperatively on computations. One of the central problems in parallel computing is the task of mapping a collection of processes onto the processors and routing network of a parallel machine. Once this mapping is done, it is critical to schedule computations within and communication among processor from universities and laboratories, as well as practitioners involved in the design, implementation, and application of massively parallel systems. Focusing on interconnection networks of parallel architectures of today and of the near future , the book includes topics such as network topologies,network properties, message routing, network embeddings, network emulation, mappings, and efficient scheduling. inputs for a process are available where and when the process is scheduled to be computed. This book contains the refereed pro...

Schedules of Controlled Substances: Temporary Placement of 4-Fluoroisobutyryl Fentanyl into Schedule I. Temporary scheduling order.

Science.gov (United States)

2017-05-03

The Administrator of the Drug Enforcement Administration is issuing this temporary scheduling order to schedule the synthetic opioid, N-(4-fluorophenyl)-N-(1-phenethylpiperidin-4-yl)isobutyramide (4-fluoroisobutyryl fentanyl or para-fluoroisobutyryl fentanyl), and its isomers, esters, ethers, salts and salts of isomers, esters, and ethers, into schedule I pursuant to the temporary scheduling provisions of the Controlled Substances Act. This action is based on a finding by the Administrator that the placement of 4-fluoroisobutyryl fentanyl into schedule I of the Controlled Substances Act is necessary to avoid an imminent hazard to the public safety. As a result of this order, the regulatory controls and administrative, civil, and criminal sanctions applicable to schedule I controlled substances will be imposed on persons who handle (manufacture, distribute, reverse distribute, import, export, engage in research, conduct instructional activities or chemical analysis, or possess), or propose to handle, 4-fluoroisobutyryl fentanyl.

Putting ROSE to Work: A Proposed Application of a Request-Oriented Scheduling Engine for Space Station Operations

Science.gov (United States)

Jaap, John; Muery, Kim

2000-01-01

Scheduling engines are found at the core of software systems that plan and schedule activities and resources. A Request-Oriented Scheduling Engine (ROSE) is one that processes a single request (adding a task to a timeline) and then waits for another request. For the International Space Station, a robust ROSE-based system would support multiple, simultaneous users, each formulating requests (defining scheduling requirements), submitting these requests via the internet to a single scheduling engine operating on a single timeline, and immediately viewing the resulting timeline. ROSE is significantly different from the engine currently used to schedule Space Station operations. The current engine supports essentially one person at a time, with a pre-defined set of requirements from many payloads, working in either a "batch" scheduling mode or an interactive/manual scheduling mode. A planning and scheduling process that takes advantage of the features of ROSE could produce greater customer satisfaction at reduced cost and reduced flow time. This paper describes a possible ROSE-based scheduling process and identifies the additional software component required to support it. Resulting changes to the management and control of the process are also discussed.

Run-Time HW/SW Scheduling of Data Flow Applications on Reconfigurable Architectures

Directory of Open Access Journals (Sweden)

Ghaffari Fakhreddine

2009-01-01

Full Text Available This paper presents an efficient dynamic and run-time Hardware/Software scheduling approach. This scheduling heuristic consists in mapping online the different tasks of a highly dynamic application in such a way that the total execution time is minimized. We consider soft real-time data flow graph oriented applications for which the execution time is function of the input data nature. The target architecture is composed of two processors connected to a dynamically reconfigurable hardware accelerator. Our approach takes advantage of the reconfiguration property of the considered architecture to adapt the treatment to the system dynamics. We compare our heuristic with another similar approach. We present the results of our scheduling method on several image processing applications. Our experiments include simulation and synthesis results on a Virtex V-based platform. These results show a better performance against existing methods.

T-L Plane Abstraction-Based Energy-Efficient Real-Time Scheduling for Multi-Core Wireless Sensors

Directory of Open Access Journals (Sweden)

Youngmin Kim

2016-07-01

Full Text Available Energy efficiency is considered as a critical requirement for wireless sensor networks. As more wireless sensor nodes are equipped with multi-cores, there are emerging needs for energy-efficient real-time scheduling algorithms. The T-L plane-based scheme is known to be an optimal global scheduling technique for periodic real-time tasks on multi-cores. Unfortunately, there has been a scarcity of studies on extending T-L plane-based scheduling algorithms to exploit energy-saving techniques. In this paper, we propose a new T-L plane-based algorithm enabling energy-efficient real-time scheduling on multi-core sensor nodes with dynamic power management (DPM. Our approach addresses the overhead of processor mode transitions and reduces fragmentations of the idle time, which are inherent in T-L plane-based algorithms. Our experimental results show the effectiveness of the proposed algorithm compared to other energy-aware scheduling methods on T-L plane abstraction.

Effectiveness of Time-Based Attention Schedules on Students in Inclusive Classrooms in Turkey

Science.gov (United States)

Sazak Pinar, Elif

2015-01-01

This study examines the effectiveness of fixed-time (FT) and variable-time (VT) schedules and attention on the problem behaviors and on-task behaviors of students with and without intellectual disabilities in inclusive classrooms in Turkey. Three second-grade students with intellectual disabilities, three students without intellectual…

Resource planning and scheduling of payload for satellite with particle swarm optimization

Science.gov (United States)

Li, Jian; Wang, Cheng

2007-11-01

The resource planning and scheduling technology of payload is a key technology to realize an automated control for earth observing satellite with limited resources on satellite, which is implemented to arrange the works states of various payloads to carry out missions by optimizing the scheme of the resources. The scheduling task is a difficult constraint optimization problem with various and mutative requests and constraints. Based on the analysis of the satellite's functions and the payload's resource constraints, a proactive planning and scheduling strategy based on the availability of consumable and replenishable resources in time-order is introduced along with dividing the planning and scheduling period to several pieces. A particle swarm optimization algorithm is proposed to address the problem with an adaptive mutation operator selection, where the swarm is divided into groups with different probabilities to employ various mutation operators viz., differential evolution, Gaussian and random mutation operators. The probabilities are adjusted adaptively by comparing the effectiveness of the groups to select a proper operator. The simulation results have shown the feasibility and effectiveness of the method.

Nurse Scheduling by Cooperative GA with Effective Mutation Operator

Science.gov (United States)

Ohki, Makoto

In this paper, we propose an effective mutation operators for Cooperative Genetic Algorithm (CGA) to be applied to a practical Nurse Scheduling Problem (NSP). The nurse scheduling is a very difficult task, because NSP is a complex combinatorial optimizing problem for which many requirements must be considered. In real hospitals, the schedule changes frequently. The changes of the shift schedule yields various problems, for example, a fall in the nursing level. We describe a technique of the reoptimization of the nurse schedule in response to a change. The conventional CGA is superior in ability for local search by means of its crossover operator, but often stagnates at the unfavorable situation because it is inferior to ability for global search. When the optimization stagnates for long generation cycle, a searching point, population in this case, would be caught in a wide local minimum area. To escape such local minimum area, small change in a population should be required. Based on such consideration, we propose a mutation operator activated depending on the optimization speed. When the optimization stagnates, in other words, when the optimization speed decreases, the mutation yields small changes in the population. Then the population is able to escape from a local minimum area by means of the mutation. However, this mutation operator requires two well-defined parameters. This means that user have to consider the value of these parameters carefully. To solve this problem, we propose a periodic mutation operator which has only one parameter to define itself. This simplified mutation operator is effective over a wide range of the parameter value.

A review of metaheuristic scheduling techniques in cloud computing

Directory of Open Access Journals (Sweden)

Mala Kalra

2015-11-01

Full Text Available Cloud computing has become a buzzword in the area of high performance distributed computing as it provides on-demand access to shared pool of resources over Internet in a self-service, dynamically scalable and metered manner. Cloud computing is still in its infancy, so to reap its full benefits, much research is required across a broad array of topics. One of the important research issues which need to be focused for its efficient performance is scheduling. The goal of scheduling is to map tasks to appropriate resources that optimize one or more objectives. Scheduling in cloud computing belongs to a category of problems known as NP-hard problem due to large solution space and thus it takes a long time to find an optimal solution. There are no algorithms which may produce optimal solution within polynomial time to solve these problems. In cloud environment, it is preferable to find suboptimal solution, but in short period of time. Metaheuristic based techniques have been proved to achieve near optimal solutions within reasonable time for such problems. In this paper, we provide an extensive survey and comparative analysis of various scheduling algorithms for cloud and grid environments based on three popular metaheuristic techniques: Ant Colony Optimization (ACO, Genetic Algorithm (GA and Particle Swarm Optimization (PSO, and two novel techniques: League Championship Algorithm (LCA and BAT algorithm.

Performance Evaluation of Bidding-Based Multi-Agent Scheduling Algorithms for Manufacturing Systems

Directory of Open Access Journals (Sweden)

Antonio Gordillo

2014-10-01

Full Text Available Artificial Intelligence techniques have being applied to many problems in manufacturing systems in recent years. In the specific field of manufacturing scheduling many studies have been published trying to cope with the complexity of the manufacturing environment. One of the most utilized approaches is (multi agent-based scheduling. Nevertheless, despite the large list of studies reported in this field, there is no resource or scientific study on the performance measure of this type of approach under very common and critical execution situations. This paper focuses on multi-agent systems (MAS based algorithms for task allocation, particularly in manufacturing applications. The goal is to provide a mechanism to measure the performance of agent-based scheduling approaches for manufacturing systems under key critical situations such as: dynamic environment, rescheduling, and priority change. With this mechanism it will be possible to simulate critical situations and to stress the system in order to measure the performance of a given agent-based scheduling method. The proposed mechanism is a pioneering approach for performance evaluation of bidding-based MAS approaches for manufacturing scheduling. The proposed method and evaluation methodology can be used to run tests in different manufacturing floors since it is independent of the workshop configuration. Moreover, the evaluation results presented in this paper show the key factors and scenarios that most affect the market-like MAS approaches for manufacturing scheduling.

A real-time Excel-based scheduling solution for nursing staff reallocation.

Science.gov (United States)

Tuominen, Outi Anneli; Lundgren-Laine, Heljä; Kauppila, Wiveka; Hupli, Maija; Salanterä, Sanna

2016-09-30

Aim This article describes the development and testing of an Excel-based scheduling solution for the flexible allocation and reallocation of nurses to cover sudden, unplanned absences among permanent nursing staff. Method A quasi-experimental, one group, pre- and post-test study design was used ( Box 1 ) with total sampling. Participants (n=17) were selected purposefully by including all ward managers (n=8) and assistant ward managers (n=9) from one university hospital department. The number of sudden absences among the nursing staff was identified during two 4-week data collection periods (pre- and post-test). Results During the use of the paper-based scheduling system, 121 absences were identified; during the use of the Excel-based system, 106 were identified. The main reasons for the use of flexible 'floating' nurses were sick leave (n=66) and workload (n=31). Other reasons (n=29) included patient transfer to another hospital, scheduling errors and the start or end of employment. Conclusion The Excel-based scheduling solution offered better support in obtaining substitute labour inside the organisation, with smaller employment costs. It also reduced the number of tasks ward managers had to carry out during the process of reallocating staff.

2007 Wholesale Power Rate Schedules : 2007 General Rate Schedule Provisions.

Energy Technology Data Exchange (ETDEWEB)

United States. Bonneville Power Administration.

2006-11-01

This schedule is available for the contract purchase of Firm Power to be used within the Pacific Northwest (PNW). Priority Firm (PF) Power may be purchased by public bodies, cooperatives, and Federal agencies for resale to ultimate consumers, for direct consumption, and for Construction, Test and Start-Up, and Station Service. Rates in this schedule are in effect beginning October 1, 2006, and apply to purchases under requirements Firm Power sales contracts for a three-year period. The Slice Product is only available for public bodies and cooperatives who have signed Slice contracts for the FY 2002-2011 period. Utilities participating in the Residential Exchange Program (REP) under Section 5(c) of the Northwest Power Act may purchase Priority Firm Power pursuant to the Residential Exchange Program. Rates under contracts that contain charges that escalate based on BPA's Priority Firm Power rates shall be based on the three-year rates listed in this rate schedule in addition to applicable transmission charges. This rate schedule supersedes the PF-02 rate schedule, which went into effect October 1, 2001. Sales under the PF-07 rate schedule are subject to BPA's 2007 General Rate Schedule Provisions (2007 GRSPs). Products available under this rate schedule are defined in the 2007 GRSPs. For sales under this rate schedule, bills shall be rendered and payments due pursuant to BPA's 2007 GRSPs and billing process.

Genetic algorithm parameters tuning for resource-constrained project scheduling problem

Science.gov (United States)

Tian, Xingke; Yuan, Shengrui

2018-04-01

Project Scheduling Problem (RCPSP) is a kind of important scheduling problem. To achieve a certain optimal goal such as the shortest duration, the smallest cost, the resource balance and so on, it is required to arrange the start and finish of all tasks under the condition of satisfying project timing constraints and resource constraints. In theory, the problem belongs to the NP-hard problem, and the model is abundant. Many combinatorial optimization problems are special cases of RCPSP, such as job shop scheduling, flow shop scheduling and so on. At present, the genetic algorithm (GA) has been used to deal with the classical RCPSP problem and achieved remarkable results. Vast scholars have also studied the improved genetic algorithm for the RCPSP problem, which makes it to solve the RCPSP problem more efficiently and accurately. However, for the selection of the main parameters of the genetic algorithm, there is no parameter optimization in these studies. Generally, we used the empirical method, but it cannot ensure to meet the optimal parameters. In this paper, the problem was carried out, which is the blind selection of parameters in the process of solving the RCPSP problem. We made sampling analysis, the establishment of proxy model and ultimately solved the optimal parameters.

Efficient multitasking: parallel versus serial processing of multiple tasks.

Science.gov (United States)

Fischer, Rico; Plessow, Franziska

2015-01-01

In the context of performance optimizations in multitasking, a central debate has unfolded in multitasking research around whether cognitive processes related to different tasks proceed only sequentially (one at a time), or can operate in parallel (simultaneously). This review features a discussion of theoretical considerations and empirical evidence regarding parallel versus serial task processing in multitasking. In addition, we highlight how methodological differences and theoretical conceptions determine the extent to which parallel processing in multitasking can be detected, to guide their employment in future research. Parallel and serial processing of multiple tasks are not mutually exclusive. Therefore, questions focusing exclusively on either task-processing mode are too simplified. We review empirical evidence and demonstrate that shifting between more parallel and more serial task processing critically depends on the conditions under which multiple tasks are performed. We conclude that efficient multitasking is reflected by the ability of individuals to adjust multitasking performance to environmental demands by flexibly shifting between different processing strategies of multiple task-component scheduling.

The Task Manager for the LHCb On-Line Farm

CERN Document Server

Bonifazi, F; Carbone, A; Galli, D; Gregori, D; Marconi, U; Peco, G; Vagnoni, V

2004-01-01

The Task Manager is a utility to start, stop and list processes on the on-line farm. Each process started by the Task Manager has a string environment variable set, named UTGID (User defined unique Thread Group Identifier) which allows to identify the process. The Task Manager uses the UTGID to list the running processes and to identify the processes to be stopped. It has also the ability to start a process using a particular user name and to set the scheduler type and the priority for the process itself. The Task Manager package includes a Linux DIM server (tmSrv), four Linux command line DIM clients (tmStart, tmLs, tmKill and tmStop) and a JCOP (Joint Control Project) PVSS client.

Project management with dynamic scheduling baseline scheduling, risk analysis and project control

CERN Document Server

Vanhoucke, Mario

2013-01-01

The topic of this book is known as dynamic scheduling, and is used to refer to three dimensions of project management and scheduling: the construction of a baseline schedule and the analysis of a project schedule's risk as preparation of the project control phase during project progress. This dynamic scheduling point of view implicitly assumes that the usability of a project's baseline schedule is rather limited and only acts as a point of reference in the project life cycle.

Distributed late-binding micro-scheduling and data caching for data-intensive workflows

International Nuclear Information System (INIS)

Delgado Peris, A.

2015-01-01

Today's world is flooded with vast amounts of digital information coming from innumerable sources. Moreover, it seems clear that this trend will only intensify in the future. Industry, society and remarkably science are not indifferent to this fact. On the contrary, they are struggling to get the most out of this data, which means that they need to capture, transfer, store and process it in a timely and efficient manner, using a wide range of computational resources. And this task is not always simple. A very representative example of the challenges posed by the management and processing of large quantities of data is that of the Large Hadron Collider experiments, which handle tens of petabytes of physics information every year. Based on the experience of one of these collaborations, we have studied the main issues involved in the management of huge volumes of data and in the completion of sizeable workflows that consume it. In this context, we have developed a general-purpose architecture for the scheduling and execution of workflows with heavy data requirements: the Task Queue. This new system builds on the late-binding overlay model, which has helped experiments to successfully overcome the problems associated to the heterogeneity and complexity of large computational grids. Our proposal introduces several enhancements to the existing systems. The execution agents of the Task Queue architecture share a Distributed Hash Table (DHT) and perform job matching and assignment cooperatively. In this way, scalability problems of centralized matching algorithms are avoided and workflow execution times are improved. Scalability makes fine-grained micro-scheduling possible and enables new functionalities, like the implementation of a distributed data cache on the execution nodes and the integration of data location information in the scheduling decisions...(Author)

Non-traditional Sensor Tasking for SSA: A Case Study

Science.gov (United States)

Herz, A.; Herz, E.; Center, K.; Martinez, I.; Favero, N.; Clark, C.; Therien, W.; Jeffries, M.

Industry has recognized that maintaining SSA of the orbital environment going forward is too challenging for the government alone. Consequently there are a significant number of commercial activities in various stages of development standing-up novel sensors and sensor networks to assist in SSA gathering and dissemination. Use of these systems will allow government and military operators to focus on the most sensitive space control issues while allocating routine or lower priority data gathering responsibility to the commercial side. The fact that there will be multiple (perhaps many) commercial sensor capabilities available in this new operational model begets a common access solution. Absent a central access point to assert data needs, optimized use of all commercial sensor resources is not possible and the opportunity for coordinated collections satisfying overarching SSA-elevating objectives is lost. Orbit Logic is maturing its Heimdall Web system - an architecture facilitating “data requestor” perspectives (allowing government operations centers to assert SSA data gathering objectives) and “sensor operator” perspectives (through which multiple sensors of varying phenomenology and capability are integrated via machine -machine interfaces). When requestors submit their needs, Heimdall’s planning engine determines tasking schedules across all sensors, optimizing their use via an SSA-specific figure-of-merit. ExoAnalytic was a key partner in refining the sensor operator interfaces, working with Orbit Logic through specific details of sensor tasking schedule delivery and the return of observation data. Scant preparation on both sides preceded several integration exercises (walk-then-run style), which culminated in successful demonstration of the ability to supply optimized schedules for routine public catalog data collection – then adapt sensor tasking schedules in real-time upon receipt of urgent data collection requests. This paper will provide a

NASA scheduling technologies

Science.gov (United States)

Adair, Jerry R.

1994-01-01

This paper is a consolidated report on ten major planning and scheduling systems that have been developed by the National Aeronautics and Space Administration (NASA). A description of each system, its components, and how it could be potentially used in private industry is provided in this paper. The planning and scheduling technology represented by the systems ranges from activity based scheduling employing artificial intelligence (AI) techniques to constraint based, iterative repair scheduling. The space related application domains in which the systems have been deployed vary from Space Shuttle monitoring during launch countdown to long term Hubble Space Telescope (HST) scheduling. This paper also describes any correlation that may exist between the work done on different planning and scheduling systems. Finally, this paper documents the lessons learned from the work and research performed in planning and scheduling technology and describes the areas where future work will be conducted.

CP Methods for Scheduling and Routing with Time-Dependent Task Costs

DEFF Research Database (Denmark)

Tierney, Kevin; Kelareva, Elena; Kilby, Philip

2013-01-01

a cost function, and Mixed Integer Programming (MIP) are often used for solving such problems. However, Constraint Programming (CP), particularly with Lazy Clause Genera- tion (LCG), has been found to be faster than MIP for some scheduling problems with time-varying action costs. In this paper, we...... compare CP and LCG against a solve-and-improve approach for two recently introduced problems in maritime logistics with time-varying action costs: the Liner Shipping Fleet Repositioning Problem (LSFRP) and the Bulk Port Cargo Throughput Optimisation Problem (BPCTOP). We present a novel CP model...... for the LSFRP, which is faster than all previous methods and outperforms a simplified automated planning model without time-varying costs. We show that a LCG solver is faster for solving the BPCTOP than a standard finite domain CP solver with a simplified model. We find that CP and LCG are effective methods...

The Impact of the Implementation Cost of Replication in Data Grid Job Scheduling

Directory of Open Access Journals (Sweden)

Babar Nazir

2018-05-01

Full Text Available Data Grids deal with geographically-distributed large-scale data-intensive applications. Schemes scheduled for data grids attempt to not only improve data access time, but also aim to improve the ratio of data availability to a node, where the data requests are generated. Data replication techniques manage large data by storing a number of data files efficiently. In this paper, we propose centralized dynamic scheduling strategy-replica placement strategies (CDSS-RPS. CDSS-RPS schedule the data and task so that it minimizes the implementation cost and data transfer time. CDSS-RPS consists of two algorithms, namely (a centralized dynamic scheduling (CDS and (b replica placement strategy (RPS. CDS considers the computing capacity of a node and finds an appropriate location for the job. RPS attempts to improve file access time by using replication on the basis of number of accesses, storage capacity of a computing node, and response time of a requested file. Extensive simulations are carried out to demonstrate the effectiveness of the proposed strategy. Simulation results demonstrate that the replication and scheduling strategies improve the implementation cost and average access time significantly.

75 FR 42831 - Proposed Collection; Comment Request for Form 1065, Schedule C, Schedule D, Schedule K-1...

Science.gov (United States)

2010-07-22

.../or continuing information collections, as required by the Paperwork Reduction Act of 1995, Public Law... Income, Credits, Deductions and Other Items), Schedule L (Balance Sheets per Books), Schedule M-1 (Reconciliation of Income (Loss) per Books With Income (Loss) per Return)), Schedule M-2 (Analysis of Partners...

Multi-objective AGV scheduling in an FMS using a hybrid of genetic algorithm and particle swarm optimization.

Directory of Open Access Journals (Sweden)

Maryam Mousavi

Full Text Available Flexible manufacturing system (FMS enhances the firm's flexibility and responsiveness to the ever-changing customer demand by providing a fast product diversification capability. Performance of an FMS is highly dependent upon the accuracy of scheduling policy for the components of the system, such as automated guided vehicles (AGVs. An AGV as a mobile robot provides remarkable industrial capabilities for material and goods transportation within a manufacturing facility or a warehouse. Allocating AGVs to tasks, while considering the cost and time of operations, defines the AGV scheduling process. Multi-objective scheduling of AGVs, unlike single objective practices, is a complex and combinatorial process. In the main draw of the research, a mathematical model was developed and integrated with evolutionary algorithms (genetic algorithm (GA, particle swarm optimization (PSO, and hybrid GA-PSO to optimize the task scheduling of AGVs with the objectives of minimizing makespan and number of AGVs while considering the AGVs' battery charge. Assessment of the numerical examples' scheduling before and after the optimization proved the applicability of all the three algorithms in decreasing the makespan and AGV numbers. The hybrid GA-PSO produced the optimum result and outperformed the other two algorithms, in which the mean of AGVs operation efficiency was found to be 69.4, 74, and 79.8 percent in PSO, GA, and hybrid GA-PSO, respectively. Evaluation and validation of the model was performed by simulation via Flexsim software.

Multi-objective AGV scheduling in an FMS using a hybrid of genetic algorithm and particle swarm optimization.

Science.gov (United States)

Mousavi, Maryam; Yap, Hwa Jen; Musa, Siti Nurmaya; Tahriri, Farzad; Md Dawal, Siti Zawiah

2017-01-01

Flexible manufacturing system (FMS) enhances the firm's flexibility and responsiveness to the ever-changing customer demand by providing a fast product diversification capability. Performance of an FMS is highly dependent upon the accuracy of scheduling policy for the components of the system, such as automated guided vehicles (AGVs). An AGV as a mobile robot provides remarkable industrial capabilities for material and goods transportation within a manufacturing facility or a warehouse. Allocating AGVs to tasks, while considering the cost and time of operations, defines the AGV scheduling process. Multi-objective scheduling of AGVs, unlike single objective practices, is a complex and combinatorial process. In the main draw of the research, a mathematical model was developed and integrated with evolutionary algorithms (genetic algorithm (GA), particle swarm optimization (PSO), and hybrid GA-PSO) to optimize the task scheduling of AGVs with the objectives of minimizing makespan and number of AGVs while considering the AGVs' battery charge. Assessment of the numerical examples' scheduling before and after the optimization proved the applicability of all the three algorithms in decreasing the makespan and AGV numbers. The hybrid GA-PSO produced the optimum result and outperformed the other two algorithms, in which the mean of AGVs operation efficiency was found to be 69.4, 74, and 79.8 percent in PSO, GA, and hybrid GA-PSO, respectively. Evaluation and validation of the model was performed by simulation via Flexsim software.

KASS v.2.2. scheduling software for construction

Directory of Open Access Journals (Sweden)

Krzemiński Michał

2016-01-01

Full Text Available The paper presents fourth version of specialist useful software in scheduling KASS v.2.2 (Algorithm Scheduling Krzeminski System. KASS software is designed for construction scheduling, specially form flow shop models. The program is being dedicated closely for the purposes of the construction. In distinguishing to other used programs in tasks of this type operational research criteria were designed closely with the thought about construction works and about the specificity of the building production. The minimal time, the minimal slack of brigades, the minimal slacks of the chosen working brigade and costs of the transfer operation of working fronts are included in operational research criteria between work centers. It is possible to enter data into the program both by hand as well as to load the Excel from files, similarly is with results, they are presented on-screen as well as a possibility of enrolling them in the file exists Excel. An element is very valid for it since allows for further simple processing of received results. In providing software for performing operational research calculations a technique of the complete review and simulation technology are being exploited. Described algorithms a program is using which will stay in the article as well as shown computational examples will remain.

Residential Consumption Scheduling Based on Dynamic User Profiling

Science.gov (United States)

Mangiatordi, Federica; Pallotti, Emiliano; Del Vecchio, Paolo; Capodiferro, Licia

Deployment of household appliances and of electric vehicles raises the electricity demand in the residential areas and the impact of the building's electrical power. The variations of electricity consumption across the day, may affect both the design of the electrical generation facilities and the electricity bill, mainly when a dynamic pricing is applied. This paper focuses on an energy management system able to control the day-ahead electricity demand in a residential area, taking into account both the variability of the energy production costs and the profiling of the users. The user's behavior is dynamically profiled on the basis of the tasks performed during the previous days and of the tasks foreseen for the current day. Depending on the size and on the flexibility in time of the user tasks, home inhabitants are grouped in, one over N, energy profiles, using a k-means algorithm. For a fixed energy generation cost, each energy profile is associated to a different hourly energy cost. The goal is to identify any bad user profile and to make it pay a highest bill. A bad profile example is when a user applies a lot of consumption tasks and low flexibility in task reallocation time. The proposed energy management system automatically schedules the tasks, solving a multi-objective optimization problem based on an MPSO strategy. The goals, when identifying bad users profiles, are to reduce the peak to average ratio in energy demand, and to minimize the energy costs, promoting virtuous behaviors.

The Reduction of Directed Cyclic Graph for Task Assignment Problem

Directory of Open Access Journals (Sweden)

Ariffin W.N.M.

2018-01-01

Full Text Available In this paper, a directed cyclic graph (DCG is proposed as the task graph. It is undesirable and impossible to complete the task according to the constraints if the cycle exists. Therefore, an effort should be done in order to eliminate the cycle to obtain a directed acyclic graph (DAG, so that the minimum amount of time required for the entire task can be found. The technique of reducing the complexity of the directed cyclic graph to a directed acyclic graph by reversing the orientation of the path is the main contribution of this study. The algorithm was coded using Java programming and consistently produced good assignment and task schedule.

Accelerating exact schedulability analysis for fixed-priority pre-emptive scheduling

NARCIS (Netherlands)

Hang, Y.; Jiale, Z.; Keskin, U.; Bril, R.J.

2010-01-01

The schedulability analysis for fixed-priority preemptive scheduling (FPPS) plays a significant role in the real-time systems domain. The so-called Hyperplanes Exact Test (HET) [1] is an example of an exact schedulability test for FPPS. In this paper, we aim at improving the efficiency of HET by

Heuristics in dynamic scheduling : A practical framework with a case study in elevator dispatching

NARCIS (Netherlands)

De Jong, J.L.

2012-01-01

Dynamic scheduling problems are ubiquitous: traffic lights, elevators, planning of manufacturing plants, air traffic control, etc. Tasks have to be put on a timeline as smart as possible to reach certain goals. These goals may be related to production costs, the use of (scarce) resources, deadlines.

A Genetic Algorithm-based Heuristic for Part-Feeding Mobile Robot Scheduling Problem

DEFF Research Database (Denmark)

Dang, Vinh Quang; Nielsen, Izabela Ewa; Bocewicz, Grzegorz

2012-01-01

This present study deals with the problem of sequencing feeding tasks of a single mobile robot with manipulation arm which is able to provide parts or components for feeders of machines in a manufacturing cell. The mobile robot has to be scheduled in order to keep machines within the cell producing...... products without any shortage of parts. A method based on the characteristics of feeders and inspired by the (s, Q) inventory system, is thus applied to define time windows for feeding tasks of the robot. The performance criterion is to minimize total traveling time of the robot in a given planning horizon...

An On-Time Power-Aware Scheduling Scheme for Medical Sensor SoC-Based WBAN Systems

Science.gov (United States)

Hwang, Tae-Ho; Kim, Dong-Sun; Kim, Jung-Guk

2013-01-01

The focus of many leading technologies in the field of medical sensor systems is on low power consumption and robust data transmission. For example, the implantable cardioverter-defibrillator (ICD), which is used to maintain the heart in a healthy state, requires a reliable wireless communication scheme with an extremely low duty-cycle, high bit rate, and energy-efficient media access protocols. Because such devices must be sustained for over 5 years without access to battery replacement, they must be designed to have extremely low power consumption in sleep mode. Here, an on-time, energy-efficient scheduling scheme is proposed that performs power adjustments to minimize the sleep-mode current. The novelty of this scheduler is that it increases the determinacy of power adjustment and the predictability of scheduling by employing non-pre-emptible dual priority scheduling. This predictable scheduling also guarantees the punctuality of important periodic tasks based on their serialization, by using their worst case execution time) and the power consumption optimization. The scheduler was embedded into a system on chip (SoC) developed to support the wireless body area network—a wakeup-radio and wakeup-timer for implantable medical devices. This scheduling system is validated by the experimental results of its performance when used with life-time extensions of ICD devices. PMID:23271602

An on-time power-aware scheduling scheme for medical sensor SoC-based WBAN systems.

Science.gov (United States)

Hwang, Tae-Ho; Kim, Dong-Sun; Kim, Jung-Guk

2012-12-27

The focus of many leading technologies in the field of medical sensor systems is on low power consumption and robust data transmission. For example, the implantable cardioverter-defibrillator (ICD), which is used to maintain the heart in a healthy state, requires a reliable wireless communication scheme with an extremely low duty-cycle, high bit rate, and energy-efficient media access protocols. Because such devices must be sustained for over 5 years without access to battery replacement, they must be designed to have extremely low power consumption in sleep mode. Here, an on-time, energy-efficient scheduling scheme is proposed that performs power adjustments to minimize the sleep-mode current. The novelty of this scheduler is that it increases the determinacy of power adjustment and the predictability of scheduling by employing non-pre-emptible dual priority scheduling. This predictable scheduling also guarantees the punctuality of important periodic tasks based on their serialization, by using their worst case execution time) and the power consumption optimization. The scheduler was embedded into a system on chip (SoC) developed to support the wireless body area network-a wakeup-radio and wakeup-timer for implantable medical devices. This scheduling system is validated by the experimental results of its performance when used with life-time extensions of ICD devices.

The role of the production scheduling system in rescheduling

Science.gov (United States)

Kalinowski, K.; Grabowik, C.; Kempa, W.; Paprocka, I.

2015-11-01

The paper presents the rescheduling problem in the context of cooperation between production scheduling system (PSS) and other units in an integrated manufacturing environment - decision makers and software systems. The main aim is to discuss the PSS functionality for maximizing automation of the rescheduling process, reducing the response time and improving the quality of generated solutions. PSSs operate in the meeting of tactical and operational level of planning and control, and play an important role in the production preparation and control. On the basis of information about orders, technology and production system state (e.g. resources availability) they prepare and/or update a detailed plan of production flow - a schedule. All necessary data for scheduling and rescheduling are usually collected in other systems both from organizational and technical production preparation, e.g. ERP, PLM, MES, CAPP or others, as well as they are entered directly by the decision- makers/operators. Data acquired in this way are often incomplete and inconsistent. Therefore the existing rescheduling software works according to interactive method - rather support but does not replace the human decision maker in tasks planning. When rescheduling, due to the limited amount of time to make a decision this interaction is particularly important. An additional problem arises in data acquisition, in the process of data exchanging between systems or in the identification of new data sources and their processing. Different approaches to rescheduling were characterized, including those solutions, where all these operations are carried out by an autonomous system and those in which scheduling is performed only upon request from the outside, for the newly created scheduling data representing the current state of the production system.

Scheduling System for Multiple Unmanned Aerial Vehicles in Indoor Environments Using the CSP Approach

DEFF Research Database (Denmark)

Park, Youngsoo; Khosiawan, Yohanes; Moon, Ilkyeong

2016-01-01

In recent years there has been an increased demand in use of multiple unmanned aerial vehicles (UAVs) for surveillance and material handling tasks in indoor environments. However, only a limited number of studies have been reported on UAV scheduling in an indoor 3D environment. This paper present...

Preemptive and Non-Preemptive Real-Time UniProcessor Scheduling

OpenAIRE

George , Laurent; Rivierre , Nicolas; Spuri , Marco

1996-01-01

Projet REFLECS; Scheduling theory, as it applies to hard-real-time environment, has been widely studied in the last twenty years and it might be unclear to make it out within the plethora of results available. Our goal is first to collect in a single paper the results known for uniproces sor, non-idling, preemptive/non-preemptive, fixed/dynamic priority driven contexts, consid ering general task sets as a central figure for the description of possible processor loads. Second to establish new ...

Preventive Maintenance Scheduling for Multicogeneration Plants with Production Constraints Using Genetic Algorithms

Directory of Open Access Journals (Sweden)

Khaled Alhamad

2015-01-01

Full Text Available This paper describes a method developed to schedule the preventive maintenance tasks of the generation and desalination units in separate and linked cogeneration plants provided that all the necessary maintenance and production constraints are satisfied. The proposed methodology is used to generate two preventing maintenance schedules, one for electricity and the other for distiller. Two types of crossover operators were adopted, 2-point and 4-point. The objective function of the model is to maximize the available number of operational units in each plant. The results obtained were satisfying the problem parameters. However, 4-point slightly produce better solution than 2-point ones for both electricity and water distiller. The performance as well as the effectiveness of the genetic algorithm in solving preventive maintenance scheduling is applied and tested on a real system of 21 units for electricity and 21 units for water. The results presented here show a great potential for utility applications for effective energy management over a time horizon of 52 weeks. The model presented is an effective decision tool that optimizes the solution of the maintenance scheduling problem for cogeneration plants under maintenance and production constraints.

Optimal Residential Load Scheduling Under Utility and Rooftop Photovoltaic Units

Directory of Open Access Journals (Sweden)

Ghulam Hafeez

2018-03-01

Full Text Available With the rapid advancement in technology, electrical energy consumption is increasing rapidly. Especially, in the residential sector, more than 80% of electrical energy is being consumed because of consumer negligence. This brings the challenging task of maintaining the balance between the demand and supply of electric power. In this paper, we focus on the problem of load balancing via load scheduling under utility and rooftop photovoltaic (PV units to reduce electricity cost and peak to average ratio (PAR in demand-side management. For this purpose, we adopted genetic algorithm (GA, binary particle swarm optimization (BPSO, wind-driven optimization (WDO, and our proposed genetic WDO (GWDO algorithm, which is a hybrid of GA and WDO, to schedule the household load. For energy cost estimation, combined real-time pricing (RTP and inclined block rate (IBR were used. The proposed algorithm shifts load from peak consumption hours to off-peak hours based on combined pricing scheme and generation from rooftop PV units. Simulation results validate our proposed GWDO algorithm in terms of electricity cost and PAR reduction while considering all three scenarios which we have considered in this work: (1 load scheduling without renewable energy sources (RESs and energy storage system (ESS, (2 load scheduling with RESs, and (3 load scheduling with RESs and ESS. Furthermore, our proposed scheme reduced electricity cost and PAR by 22.5% and 29.1% in scenario 1, 47.7% and 30% in scenario 2, and 49.2% and 35.4% in scenario 3, respectively, as compared to unscheduled electricity consumption.

Ant colony optimization and event-based dynamic task scheduling and staffing for software projects

Science.gov (United States)

Ellappan, Vijayan; Ashwini, J.

2017-11-01

In programming change organizations from medium to inconceivable scale broadens, the issue of wander orchestrating is amazingly unusual and testing undertaking despite considering it a manual system. Programming wander-organizing requirements to deal with the issue of undertaking arranging and in addition the issue of human resource portion (also called staffing) in light of the way that most of the advantages in programming ventures are individuals. We propose a machine learning approach with finds respond in due order regarding booking by taking in the present arranging courses of action and an event based scheduler revives the endeavour arranging system moulded by the learning computation in perspective of the conformity in event like the begin with the Ander, the instant at what time possessions be free starting to ended errands, and the time when delegates stick together otherwise depart the wander inside the item change plan. The route toward invigorating the timetable structure by the even based scheduler makes the arranging method dynamic. It uses structure components to exhibit the interrelated surges of endeavours, slip-ups and singular all through different progression organizes and is adjusted to mechanical data. It increases past programming wander movement ask about by taking a gander at a survey based process with a one of a kind model, organizing it with the data based system for peril assessment and cost estimation, and using a choice showing stage.

Web Publishing Schedule

Science.gov (United States)

Section 207(f)(2) of the E-Gov Act requires federal agencies to develop an inventory and establish a schedule of information to be published on their Web sites, make those schedules available for public comment. To post the schedules on the web site.

Not all choices are created equal: Task-relevant choices enhance motor learning compared to task-irrelevant choices.

Science.gov (United States)

Carter, Michael J; Ste-Marie, Diane M

2017-12-01

Lewthwaite et al. (2015) reported that the learning benefits of exercising choice (i.e., their self-controlled condition) are not restricted to task-relevant features (e.g., feedback). They found that choosing one's golf ball color (Exp. 1) or choosing which of two tasks to perform at a later time plus which of two artworks to hang (Exp. 2) resulted in better retention than did being denied these same choices (i.e., yoked condition). The researchers concluded that the learning benefits derived from choice, whether irrelevant or relevant to the to-be-learned task, are predominantly motivational because choice is intrinsically rewarding and satisfies basic psychological needs. However, the absence of a group that made task-relevant choices and the lack of psychological measures significantly weakened their conclusions. Here, we investigated how task-relevant and task-irrelevant choices affect motor-skill learning. Participants practiced a spatiotemporal motor task in either a task-relevant group (choice over feedback schedule), a task-irrelevant group (choice over the color of an arm-wrap plus game selection), or a no-choice group. The results showed significantly greater learning in the task-relevant group than in both the task-irrelevant and no-choice groups, who did not differ significantly. Critically, these learning differences were not attributed to differences in perceptions of competence or autonomy, but instead to superior error-estimation abilities. These results challenge the perspective that motivational influences are the root cause of self-controlled learning advantages. Instead, the findings add to the growing evidence highlighting that the informational value gained from task-relevant choices makes a greater relative contribution to these advantages than motivational influences do.

Schedule Matters: Understanding the Relationship between Schedule Delays and Costs on Overruns

Science.gov (United States)

Majerowicz, Walt; Shinn, Stephen A.

2016-01-01

This paper examines the relationship between schedule delays and cost overruns on complex projects. It is generally accepted by many project practitioners that cost overruns are directly related to schedule delays. But what does "directly related to" actually mean? Some reasons or root causes for schedule delays and associated cost overruns are obvious, if only in hindsight. For example, unrealistic estimates, supply chain difficulties, insufficient schedule margin, technical problems, scope changes, or the occurrence of risk events can negatively impact schedule performance. Other factors driving schedule delays and cost overruns may be less obvious and more difficult to quantify. Examples of these less obvious factors include project complexity, flawed estimating assumptions, over-optimism, political factors, "black swan" events, or even poor leadership and communication. Indeed, is it even possible the schedule itself could be a source of delay and subsequent cost overrun? Through literature review, surveys of project practitioners, and the authors' own experience on NASA programs and projects, the authors will categorize and examine the various factors affecting the relationship between project schedule delays and cost growth. The authors will also propose some ideas for organizations to consider to help create an awareness of the factors which could cause or influence schedule delays and associated cost growth on complex projects.

Comparison of genetic algorithm and harmony search for generator maintenance scheduling

International Nuclear Information System (INIS)

Khan, L.; Mumtaz, S.; Khattak, A.

2012-01-01

GMS (Generator Maintenance Scheduling) ranks very high in decision making of power generation management. Generators maintenance schedule decides the time period of maintenance tasks and a reliable reserve margin is also maintained during this time period. In this paper, a comparison of GA (Genetic Algorithm) and US (Harmony Search) algorithm is presented to solve generators maintenance scheduling problem for WAPDA (Water And Power Development Authority) Pakistan. GA is a search procedure, which is used in search problems to compute exact and optimized solution. GA is considered as global search heuristic technique. HS algorithm is quite efficient, because the convergence rate of this algorithm is very fast. HS algorithm is based on the concept of music improvisation process of searching for a perfect state of harmony. The two algorithms generate feasible and optimal solutions and overcome the limitations of the conventional methods including extensive computational effort, which increases exponentially as the size of the problem increases. The proposed methods are tested, validated and compared on the WAPDA electric system. (author)

Multi-Attribute Task Battery - Applications in pilot workload and strategic behavior research

Science.gov (United States)

Arnegard, Ruth J.; Comstock, J. R., Jr.

1991-01-01

The Multi-Attribute Task (MAT) Battery provides a benchmark set of tasks for use in a wide range of lab studies of operator performance and workload. The battery incorporates tasks analogous to activities that aircraft crewmembers perform in flight, while providing a high degree of experimenter control, performance data on each subtask, and freedom to nonpilot test subjects. Features not found in existing computer based tasks include an auditory communication task (to simulate Air Traffic Control communication), a resource management task permitting many avenues or strategies of maintaining target performance, a scheduling window which gives the operator information about future task demands, and the option of manual or automated control of tasks. Performance data are generated for each subtask. In addition, the task battery may be paused and onscreen workload rating scales presented to the subject. The MAT Battery requires a desktop computer with color graphics. The communication task requires a serial link to a second desktop computer with a voice synthesizer or digitizer card.

An On-Time Power-Aware Scheduling Scheme for Medical Sensor SoC-Based WBAN Systems

Directory of Open Access Journals (Sweden)

Jung-Guk Kim

2012-12-01

Full Text Available The focus of many leading technologies in the field of medical sensor systems is on low power consumption and robust data transmission. For example, the implantable cardioverter-defibrillator (ICD, which is used to maintain the heart in a healthy state, requires a reliable wireless communication scheme with an extremely low duty-cycle, high bit rate, and energy-efficient media access protocols. Because such devices must be sustained for over 5 years without access to battery replacement, they must be designed to have extremely low power consumption in sleep mode. Here, an on-time, energy-efficient scheduling scheme is proposed that performs power adjustments to minimize the sleep-mode current. The novelty of this scheduler is that it increases the determinacy of power adjustment and the predictability of scheduling by employing non-pre-emptible dual priority scheduling. This predictable scheduling also guarantees the punctuality of important periodic tasks based on their serialization, by using their worst case execution time and the power consumption optimization. The scheduler was embedded into a system on chip (SoC developed to support the wireless body area network—a wakeup-radio and wakeup-timer for implantable medical devices. This scheduling system is validated by the experimental results of its performance when used with life-time extensions of ICD devices.

PERFORMANCE ANALYSIS BETWEEN EXPLICIT SCHEDULING AND IMPLICIT SCHEDULING OF PARALLEL ARRAY-BASED DOMAIN DECOMPOSITION USING OPENMP

Directory of Open Access Journals (Sweden)

MOHAMMED FAIZ ABOALMAALY

2014-10-01

Full Text Available With the continuous revolution of multicore architecture, several parallel programming platforms have been introduced in order to pave the way for fast and efficient development of parallel algorithms. Back into its categories, parallel computing can be done through two forms: Data-Level Parallelism (DLP or Task-Level Parallelism (TLP. The former can be done by the distribution of data among the available processing elements while the latter is based on executing independent tasks concurrently. Most of the parallel programming platforms have built-in techniques to distribute the data among processors, these techniques are technically known as automatic distribution (scheduling. However, due to their wide range of purposes, variation of data types, amount of distributed data, possibility of extra computational overhead and other hardware-dependent factors, manual distribution could achieve better outcomes in terms of performance when compared to the automatic distribution. In this paper, this assumption is investigated by conducting a comparison between automatic and our newly proposed manual distribution of data among threads in parallel. Empirical results of matrix addition and matrix multiplication show a considerable performance gain when manual distribution is applied against automatic distribution.

29 CFR 825.203 - Scheduling of intermittent or reduced schedule leave.

Science.gov (United States)

2010-07-01

... leave intermittently or on a reduced leave schedule for planned medical treatment, then the employee... 29 Labor 3 2010-07-01 2010-07-01 false Scheduling of intermittent or reduced schedule leave. 825... OF LABOR OTHER LAWS THE FAMILY AND MEDICAL LEAVE ACT OF 1993 Employee Leave Entitlements Under the...

ATLAS construction schedule

CERN Multimedia

Kotamaki, M

The goal during the last few months has been to freeze and baseline as much as possible the schedules of various ATLAS systems and activities. The main motivations for the re-baselining of the schedules have been the new LHC schedule aiming at first collisions in early 2006 and the encountered delays in civil engineering as well as in the production of some of the detectors. The process was started by first preparing a new installation schedule that takes into account all the new external constraints and the new ATLAS staging scenario. The installation schedule version 3 was approved in the March EB and it provides the Ready For Installation (RFI) milestones for each system, i.e. the date when the system should be available for the start of the installation. TCn is now interacting with the systems aiming at a more realistic and resource loaded version 4 before the end of the year. Using the new RFI milestones as driving dates a new summary schedule has been prepared, or is under preparation, for each system....

Solving multi-objective job shop scheduling problems using a non-dominated sorting genetic algorithm

Science.gov (United States)

Piroozfard, Hamed; Wong, Kuan Yew

2015-05-01

The efforts of finding optimal schedules for the job shop scheduling problems are highly important for many real-world industrial applications. In this paper, a multi-objective based job shop scheduling problem by simultaneously minimizing makespan and tardiness is taken into account. The problem is considered to be more complex due to the multiple business criteria that must be satisfied. To solve the problem more efficiently and to obtain a set of non-dominated solutions, a meta-heuristic based non-dominated sorting genetic algorithm is presented. In addition, task based representation is used for solution encoding, and tournament selection that is based on rank and crowding distance is applied for offspring selection. Swapping and insertion mutations are employed to increase diversity of population and to perform intensive search. To evaluate the modified non-dominated sorting genetic algorithm, a set of modified benchmarking job shop problems obtained from the OR-Library is used, and the results are considered based on the number of non-dominated solutions and quality of schedules obtained by the algorithm.

Short term economic emission power scheduling of hydrothermal energy systems using improved water cycle algorithm

International Nuclear Information System (INIS)

Haroon, S.S.; Malik, T.N.

2017-01-01

Due to the increasing environmental concerns, the demand of clean and green energy and concern of atmospheric pollution is increasing. Hence, the power utilities are forced to limit their emissions within the prescribed limits. Therefore, the minimization of fuel cost as well as exhaust gas emissions is becoming an important and challenging task in the short-term scheduling of hydro-thermal energy systems. This paper proposes a novel algorithm known as WCA-ER (Water Cycle Algorithm with Evaporation Rate) to inspect the short term EEPSHES (Economic Emission Power Scheduling of Hydrothermal Energy Systems). WCA has its ancestries from the natural hydrologic cycle i.e. the raining process forms streams and these streams start flowing towards the rivers which finally flow towards the sea. The worth of WCA-ER has been tested on the standard economic emission power scheduling of hydrothermal energy test system consisting of four hydropower and three thermal plants. The problem has been investigated for the three case studies (i) ECS (Economic Cost Scheduling), (ii) ES (Economic Emission Scheduling) and (iii) ECES (Economic Cost and Emission Scheduling). The results obtained show that WCA-ER is superior to many other methods in the literature in bringing lower fuel cost and emissions. (author)

A Taxonomy for Heavy-Duty Telemanipulation Tasks Using Elemental Actions

Directory of Open Access Journals (Sweden)

Alexander Owen-Hill

2013-10-01

Full Text Available In the maintenance of large scientific facilities, telemanipulation procedures can involve various subprocedures which in turn are made up of a sequence of subtasks. This work presents a taxonomy which describes a set of elemental actions for heavy-duty telemanipulation, along with an example of these actions in a standard maintenance subprocedure. As maintenance tasks are often very different at high-level, this generalized way of deconstructing tasks allows a highly adaptable approach to describe the sequence of any procedure, which can then be used for such applications as task monitoring, automation or detection of incomplete tasks. We describe in detail the properties of each elemental action and apply the taxonomy to an example subprocedure to show how the process can be generalizable. An automatic state-machine creation stage is shown, which would be used at the task scheduling stage to simplify calculations carried out during the moment-by-moment execution of the task.

Comparison of Multiobjective Evolutionary Algorithms for Operations Scheduling under Machine Availability Constraints

Directory of Open Access Journals (Sweden)

M. Frutos

2013-01-01

Full Text Available Many of the problems that arise in production systems can be handled with multiobjective techniques. One of those problems is that of scheduling operations subject to constraints on the availability of machines and buffer capacity. In this paper we analyze different Evolutionary multiobjective Algorithms (MOEAs for this kind of problems. We consider an experimental framework in which we schedule production operations for four real world Job-Shop contexts using three algorithms, NSGAII, SPEA2, and IBEA. Using two performance indexes, Hypervolume and R2, we found that SPEA2 and IBEA are the most efficient for the tasks at hand. On the other hand IBEA seems to be a better choice of tool since it yields more solutions in the approximate Pareto frontier.

Modelling and Scheduling Autonomous Mobile Robot for a Real-World Industrial Application

DEFF Research Database (Denmark)

Dang, Vinh Quang; Nielsen, Izabela Ewa; Bøgh, Simon

2013-01-01

proposes an approach composing of: a mobile robot system design (“Little Helper”), an appropriate and comprehensive industrial application (multiple-part feeding tasks), an implementation concept for industrial environments (the bartender concept), and a real-time heuristics integrated into Mission...... from the real-time heuristics. The results also demonstrated that the proposed real-time heuristics has capability of finding the best schedule in online production mode....

TRU Waste Management Program. Cost/schedule optimization analysis

International Nuclear Information System (INIS)

Detamore, J.A.; Raudenbush, M.H.; Wolaver, R.W.; Hastings, G.A.

1985-10-01

This Current Year Work Plan presents in detail a description of the activities to be performed by the Joint Integration Office Rockwell International (JIO/RI) during FY86. It breaks down the activities into two major work areas: Program Management and Program Analysis. Program Management is performed by the JIO/RI by providing technical planning and guidance for the development of advanced TRU waste management capabilities. This includes equipment/facility design, engineering, construction, and operations. These functions are integrated to allow transition from interim storage to final disposition. JIO/RI tasks include program requirements identification, long-range technical planning, budget development, program planning document preparation, task guidance development, task monitoring, task progress information gathering and reporting to DOE, interfacing with other agencies and DOE lead programs, integrating public involvement with program efforts, and preparation of reports for DOE detailing program status. Program Analysis is performed by the JIO/RI to support identification and assessment of alternatives, and development of long-term TRU waste program capabilities. These analyses include short-term analyses in response to DOE information requests, along with performing an RH Cost/Schedule Optimization report. Systems models will be developed, updated, and upgraded as needed to enhance JIO/RI's capability to evaluate the adequacy of program efforts in various fields. A TRU program data base will be maintained and updated to provide DOE with timely responses to inventory related questions

The effects of practice schedule and critical thinking prompts on learning and transfer of complex judgment

NARCIS (Netherlands)

Helsdingen, Anne; Van Gog, Tamara; Van Merriënboer, Jeroen

2010-01-01

Helsdingen, A. S., Van Gog, T., & Van Merriënboer, J. J. G. (2011). The effects of practice schedule and critical thinking prompts on learning and transfer of complex judgment task. Journal of Educational Psychology, 103(2), 383-398. doi:10.1037/a0022370

Automated mixed traffic vehicle control and scheduling study

Science.gov (United States)

Peng, T. K. C.; Chon, K.

1976-01-01

The operation and the expected performance of a proposed automatic guideway transit system which uses low speed automated mixed traffic vehicles (AMTVs) were analyzed. Vehicle scheduling and headway control policies were evaluated with a transit system simulation model. The effect of mixed traffic interference on the average vehicle speed was examined with a vehicle pedestrian interface model. Control parameters regulating vehicle speed were evaluated for safe stopping and passenger comfort. Some preliminary data on the cost and operation of an experimental AMTV system are included. These data were the result of a separate task conducted at JPL, and were included as background information.

Operational Excellence through Schedule Optimization and Production Simulation of Application Specific Integrated Circuits.

Energy Technology Data Exchange (ETDEWEB)

Flory, John Andrew [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Padilla, Denise D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Gauthier, John H. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Zwerneman, April Marie [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Miller, Steven P [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2016-05-01

Upcoming weapon programs require an aggressive increase in Application Specific Integrated Circuit (ASIC) production at Sandia National Laboratories (SNL). SNL has developed unique modeling and optimization tools that have been instrumental in improving ASIC production productivity and efficiency, identifying optimal operational and tactical execution plans under resource constraints, and providing confidence in successful mission execution. With ten products and unprecedented levels of demand, a single set of shared resources, highly variable processes, and the need for external supplier task synchronization, scheduling is an integral part of successful manufacturing. The scheduler uses an iterative multi-objective genetic algorithm and a multi-dimensional performance evaluator. Schedule feasibility is assessed using a discrete event simulation (DES) that incorporates operational uncertainty, variability, and resource availability. The tools provide rapid scenario assessments and responses to variances in the operational environment, and have been used to inform major equipment investments and workforce planning decisions in multiple SNL facilities.

CMS readiness for multi-core workload scheduling

Science.gov (United States)

Perez-Calero Yzquierdo, A.; Balcas, J.; Hernandez, J.; Aftab Khan, F.; Letts, J.; Mason, D.; Verguilov, V.

2017-10-01

In the present run of the LHC, CMS data reconstruction and simulation algorithms benefit greatly from being executed as multiple threads running on several processor cores. The complexity of the Run 2 events requires parallelization of the code to reduce the memory-per- core footprint constraining serial execution programs, thus optimizing the exploitation of present multi-core processor architectures. The allocation of computing resources for multi-core tasks, however, becomes a complex problem in itself. The CMS workload submission infrastructure employs multi-slot partitionable pilots, built on HTCondor and GlideinWMS native features, to enable scheduling of single and multi-core jobs simultaneously. This provides a solution for the scheduling problem in a uniform way across grid sites running a diversity of gateways to compute resources and batch system technologies. This paper presents this strategy and the tools on which it has been implemented. The experience of managing multi-core resources at the Tier-0 and Tier-1 sites during 2015, along with the deployment phase to Tier-2 sites during early 2016 is reported. The process of performance monitoring and optimization to achieve efficient and flexible use of the resources is also described.

CMS Readiness for Multi-Core Workload Scheduling

Energy Technology Data Exchange (ETDEWEB)

Perez-Calero Yzquierdo, A. [Madrid, CIEMAT; Balcas, J. [Caltech; Hernandez, J. [Madrid, CIEMAT; Aftab Khan, F. [NCP, Islamabad; Letts, J. [UC, San Diego; Mason, D. [Fermilab; Verguilov, V. [CLMI, Sofia

2017-11-22

In the present run of the LHC, CMS data reconstruction and simulation algorithms benefit greatly from being executed as multiple threads running on several processor cores. The complexity of the Run 2 events requires parallelization of the code to reduce the memory-per- core footprint constraining serial execution programs, thus optimizing the exploitation of present multi-core processor architectures. The allocation of computing resources for multi-core tasks, however, becomes a complex problem in itself. The CMS workload submission infrastructure employs multi-slot partitionable pilots, built on HTCondor and GlideinWMS native features, to enable scheduling of single and multi-core jobs simultaneously. This provides a solution for the scheduling problem in a uniform way across grid sites running a diversity of gateways to compute resources and batch system technologies. This paper presents this strategy and the tools on which it has been implemented. The experience of managing multi-core resources at the Tier-0 and Tier-1 sites during 2015, along with the deployment phase to Tier-2 sites during early 2016 is reported. The process of performance monitoring and optimization to achieve efficient and flexible use of the resources is also described.

Modeling Nurse Scheduling Problem Using 0-1 Goal Programming A Case Study Of Tafo Government Hospital Kumasi-Ghana

Directory of Open Access Journals (Sweden)

Wallace Agyei

2015-03-01

Full Text Available Abstract The problem of scheduling nurses at the Out-Patient Department OPD at Tafo Government Hospital Kumasi Ghana is presented. Currently the schedules are prepared by head nurse who performs this difficult and time consuming task by hand. Due to the existence of many constraints the resulting schedule usually does not guarantee the fairness of distribution of work. The problem was formulated as 0-1goal programming model with the of objective of evenly balancing the workload among nurses and satisfying their preferences as much as possible while complying with the legal and working regulations.. The developed model was then solved using LINGO14.0 software. The resulting schedules based on 0-1goal programming model balanced the workload in terms of the distribution of shift duties fairness in terms of the number of consecutive night duties and satisfied the preferences of the nurses. This is an improvement over the schedules done manually.

A Dynamic Intelligent Decision Approach to Dependency Modeling of Project Tasks in Complex Engineering System Optimization

Directory of Open Access Journals (Sweden)

Tinggui Chen

2013-01-01

Full Text Available Complex engineering system optimization usually involves multiple projects or tasks. On the one hand, dependency modeling among projects or tasks highlights structures in systems and their environments which can help to understand the implications of connectivity on different aspects of system performance and also assist in designing, optimizing, and maintaining complex systems. On the other hand, multiple projects or tasks are either happening at the same time or scheduled into a sequence in order to use common resources. In this paper, we propose a dynamic intelligent decision approach to dependency modeling of project tasks in complex engineering system optimization. The approach takes this decision process as a two-stage decision-making problem. In the first stage, a task clustering approach based on modularization is proposed so as to find out a suitable decomposition scheme for a large-scale project. In the second stage, according to the decomposition result, a discrete artificial bee colony (ABC algorithm inspired by the intelligent foraging behavior of honeybees is developed for the resource constrained multiproject scheduling problem. Finally, a certain case from an engineering design of a chemical processing system is utilized to help to understand the proposed approach.

Work Scheduling by Use of Worker Model in Consideration of Learning by On-The-Job Training

Science.gov (United States)

Tateno, Toshitake; Shimizu, Keiko

This paper deals with a method of scheduling manual work in consideration of learning by on-the-job training (OJT). In skilled work such as maintenance of trains and airplanes, workers must learn many tasks by OJT. While the work processing time of novice workers is longer than that of experts, the time will be reduced with repeated OJT. Therefore, OJT is important for maintaining the skill level and the long-term work efficiency of an organization. In order to devise a schedule considering OJT, the scheduler must incorporate a management function of workers to trace dynamically changing work experience. In this paper, after the relationship between scheduling problems and worker management problems is defined, a simulation method, in which a worker model and an agent-based mechanism are utilized, is proposed to derive the optimal OJT strategy toward high long-term performance. Finally, we present some case studies showing the effectiveness of OJT planning based on the simulation.

Optimal Sensor Networks Scheduling in Identification of Distributed Parameter Systems

CERN Document Server

Patan, Maciej

2012-01-01

Sensor networks have recently come into prominence because they hold the potential to revolutionize a wide spectrum of both civilian and military applications. An ingenious characteristic of sensor networks is the distributed nature of data acquisition. Therefore they seem to be ideally prepared for the task of monitoring processes with spatio-temporal dynamics which constitute one of most general and important classes of systems in modelling of the real-world phenomena. It is clear that careful deployment and activation of sensor nodes are critical for collecting the most valuable information from the observed environment. Optimal Sensor Network Scheduling in Identification of Distributed Parameter Systems discusses the characteristic features of the sensor scheduling problem, analyzes classical and recent approaches, and proposes a wide range of original solutions, especially dedicated for networks with mobile and scanning nodes. Both researchers and practitioners will find the case studies, the proposed al...

Constraint-based scheduling applying constraint programming to scheduling problems

CERN Document Server

Baptiste, Philippe; Nuijten, Wim

2001-01-01

Constraint Programming is a problem-solving paradigm that establishes a clear distinction between two pivotal aspects of a problem: (1) a precise definition of the constraints that define the problem to be solved and (2) the algorithms and heuristics enabling the selection of decisions to solve the problem. It is because of these capabilities that Constraint Programming is increasingly being employed as a problem-solving tool to solve scheduling problems. Hence the development of Constraint-Based Scheduling as a field of study. The aim of this book is to provide an overview of the most widely used Constraint-Based Scheduling techniques. Following the principles of Constraint Programming, the book consists of three distinct parts: The first chapter introduces the basic principles of Constraint Programming and provides a model of the constraints that are the most often encountered in scheduling problems. Chapters 2, 3, 4, and 5 are focused on the propagation of resource constraints, which usually are responsibl...

Scheduling for decommissioning projects

International Nuclear Information System (INIS)

Podmajersky, O.E.

1987-01-01

This paper describes the Project Scheduling system being employed by the Decommissioning Operations Contractor at the Shippingport Station Decommissioning Project (SSDP). Results from the planning system show that the project continues to achieve its cost and schedule goals. An integrated cost and schedule control system (C/SCS) which uses the concept of earned value for measurement of performance was instituted in accordance with DOE orders. The schedule and cost variances generated by the C/SCS system are used to confirm management's assessment of project status. This paper describes the types of schedules and tools used on the SSDP project to plan and monitor the work, and identifies factors that are unique to a decommissioning project that make scheduling critical to the achievement of the project's goals. 1 fig

Program reference schedule baseline

International Nuclear Information System (INIS)

1986-07-01

This Program Reference Schedule Baseline (PRSB) provides the baseline Program-level milestones and associated schedules for the Civilian Radioactive Waste Management Program. It integrates all Program-level schedule-related activities. This schedule baseline will be used by the Director, Office of Civilian Radioactive Waste Management (OCRWM), and his staff to monitor compliance with Program objectives. Chapter 1 includes brief discussions concerning the relationship of the PRSB to the Program Reference Cost Baseline (PRCB), the Mission Plan, the Project Decision Schedule, the Total System Life Cycle Cost report, the Program Management Information System report, the Program Milestone Review, annual budget preparation, and system element plans. Chapter 2 includes the identification of all Level 0, or Program-level, milestones, while Chapter 3 presents and discusses the critical path schedules that correspond to those Level 0 milestones

Status Report on the Development of Micro-Scheduling Software for the Advanced Outage Control Center Project

Energy Technology Data Exchange (ETDEWEB)

Germain, Shawn St. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Thomas, Kenneth [Idaho National Lab. (INL), Idaho Falls, ID (United States); Farris, Ronald [Idaho National Lab. (INL), Idaho Falls, ID (United States); Joe, Jeffrey [Idaho National Lab. (INL), Idaho Falls, ID (United States)

2014-09-01

The long-term viability of existing nuclear power plants (NPPs) in the United States (U.S.) is dependent upon a number of factors, including maintaining high capacity factors, maintaining nuclear safety, and reducing operating costs, particularly those associated with refueling outages. Refueling outages typically take 20-30 days, and for existing light water NPPs in the U.S., the reactor cannot be in operation during the outage. Furthermore, given that many NPPs generate between $1-1.5 million/day in revenue when in operation, there is considerable interest in shortening the length of refueling outages. Yet, refueling outages are highly complex operations, involving multiple concurrent and dependent activities that are difficult to coordinate. Finding ways to improve refueling outage performance while maintaining nuclear safety has proven to be difficult. The Advanced Outage Control Center project is a research and development (R&D) demonstration activity under the Light Water Reactor Sustainability (LWRS) Program. LWRS is a R&D program which works with industry R&D programs to establish technical foundations for the licensing and managing of long-term, safe, and economical operation of current NPPs. The Advanced Outage Control Center project has the goal of improving the management of commercial NPP refueling outages. To accomplish this goal, this INL R&D project is developing an advanced outage control center (OCC) that is specifically designed to maximize the usefulness of communication and collaboration technologies for outage coordination and problem resolution activities. This report describes specific recent efforts to develop a capability called outage Micro-Scheduling. Micro-Scheduling is the ability to allocate and schedule outage support task resources on a sub-hour basis. Micro-Scheduling is the real-time fine-tuning of the outage schedule to react to the actual progress of the primary outage activities to ensure that support task resources are

Second-order schedules of token reinforcement with pigeons: effects of fixed- and variable-ratio exchange schedules.

Science.gov (United States)

Foster, T A; Hackenberg, T D; Vaidya, M

2001-09-01

Pigeons' key pecks produced food under second-order schedules of token reinforcement, with light-emitting diodes serving as token reinforcers. In Experiment 1, tokens were earned according to a fixed-ratio 50 schedule and were exchanged for food according to either fixed-ratio or variable-ratio exchange schedules, with schedule type varied across conditions. In Experiment 2, schedule type was varied within sessions using a multiple schedule. In one component, tokens were earned according to a fixed-ratio 50 schedule and exchanged according to a variable-ratio schedule. In the other component, tokens were earned according to a variable-ratio 50 schedule and exchanged according to a fixed-ratio schedule. In both experiments, the number of responses per exchange was varied parametrically across conditions, ranging from 50 to 400 responses. Response rates decreased systematically with increases in the fixed-ratio exchange schedules, but were much less affected by changes in the variable-ratio exchange schedules. Response rates were consistently higher under variable-ratio exchange schedules than tinder comparable fixed-ratio exchange schedules, especially at higher exchange ratios. These response-rate differences were due both to greater pre-ratio pausing and to lower local rates tinder the fixed-ratio exchange schedules. Local response rates increased with proximity to food under the higher fixed-ratio exchange schedules, indicative of discriminative control by the tokens.

Perceptions of randomized security schedules.

Science.gov (United States)

Scurich, Nicholas; John, Richard S

2014-04-01

Security of infrastructure is a major concern. Traditional security schedules are unable to provide omnipresent coverage; consequently, adversaries can exploit predictable vulnerabilities to their advantage. Randomized security schedules, which randomly deploy security measures, overcome these limitations, but public perceptions of such schedules have not been examined. In this experiment, participants were asked to make a choice between attending a venue that employed a traditional (i.e., search everyone) or a random (i.e., a probability of being searched) security schedule. The absolute probability of detecting contraband was manipulated (i.e., 1/10, 1/4, 1/2) but equivalent between the two schedule types. In general, participants were indifferent to either security schedule, regardless of the probability of detection. The randomized schedule was deemed more convenient, but the traditional schedule was considered fairer and safer. There were no differences between traditional and random schedule in terms of perceived effectiveness or deterrence. Policy implications for the implementation and utilization of randomized schedules are discussed. © 2013 Society for Risk Analysis.

Unifying practice schedules in the timescales of motor learning and performance.

Science.gov (United States)

Verhoeven, F Martijn; Newell, Karl M

2018-06-01

In this article, we elaborate from a multiple time scales model of motor learning to examine the independent and integrated effects of massed and distributed practice schedules within- and between-sessions on the persistent (learning) and transient (warm-up, fatigue) processes of performance change. The timescales framework reveals the influence of practice distribution on four learning-related processes: the persistent processes of learning and forgetting, and the transient processes of warm-up decrement and fatigue. The superposition of the different processes of practice leads to a unified set of effects for massed and distributed practice within- and between-sessions in learning motor tasks. This analysis of the interaction between the duration of the interval of practice trials or sessions and parameters of the introduced time scale model captures the unified influence of the between trial and session scheduling of practice on learning and performance. It provides a starting point for new theoretically based hypotheses, and the scheduling of practice that minimizes the negative effects of warm-up decrement, fatigue and forgetting while exploiting the positive effects of learning and retention. Copyright © 2018 Elsevier B.V. All rights reserved.

TME (Task Mapping Editor): tool for executing distributed parallel computing. TME user's manual

International Nuclear Information System (INIS)

Takemiya, Hiroshi; Yamagishi, Nobuhiro; Imamura, Toshiyuki

2000-03-01

At the Center for Promotion of Computational Science and Engineering, a software environment PPExe has been developed to support scientific computing on a parallel computer cluster (distributed parallel scientific computing). TME (Task Mapping Editor) is one of components of the PPExe and provides a visual programming environment for distributed parallel scientific computing. Users can specify data dependence among tasks (programs) visually as a data flow diagram and map these tasks onto computers interactively through GUI of TME. The specified tasks are processed by other components of PPExe such as Meta-scheduler, RIM (Resource Information Monitor), and EMS (Execution Management System) according to the execution order of these tasks determined by TME. In this report, we describe the usage of TME. (author)

Using system architecture, review entry criteria, and standard work package data to enable rapid development of integrated master schedules

OpenAIRE

Porter, Burton W., Jr.

2016-01-01

Approved for public release; distribution is unlimited While engineers must participate in the construction of the Integrated Master Schedule, this thesis proposes a way to reduce that effort through automation. When standardized sub processes exist, automated task name construction with consistent action/object naming convention can be applied to multiple system artifacts. These repeating sub processes also allow the derivation of task sequence and dependencies. The Architecture-Based Uti...

How should periods without social interaction be scheduled? Children's preference for practical schedules of positive reinforcement.

Science.gov (United States)

Luczynski, Kevin C; Hanley, Gregory P

2014-01-01

Several studies have shown that children prefer contingent reinforcement (CR) rather than yoked noncontingent reinforcement (NCR) when continuous reinforcement is programmed in the CR schedule. Preference has not, however, been evaluated for practical schedules that involve CR. In Study 1, we assessed 5 children's preference for obtaining social interaction via a multiple schedule (periods of fixed-ratio 1 reinforcement alternating with periods of extinction), a briefly signaled delayed reinforcement schedule, and an NCR schedule. The multiple schedule promoted the most efficient level of responding. In general, children chose to experience the multiple schedule and avoided the delay and NCR schedules, indicating that they preferred multiple schedules as the means to arrange practical schedules of social interaction. In Study 2, we evaluated potential controlling variables that influenced 1 child's preference for the multiple schedule and found that the strong positive contingency was the primary variable. © Society for the Experimental Analysis of Behavior.

The comparison of predictive scheduling algorithms for different sizes of job shop scheduling problems

Science.gov (United States)

Paprocka, I.; Kempa, W. M.; Grabowik, C.; Kalinowski, K.; Krenczyk, D.

2016-08-01

In the paper a survey of predictive and reactive scheduling methods is done in order to evaluate how the ability of prediction of reliability characteristics influences over robustness criteria. The most important reliability characteristics are: Mean Time to Failure, Mean Time of Repair. Survey analysis is done for a job shop scheduling problem. The paper answers the question: what method generates robust schedules in the case of a bottleneck failure occurrence before, at the beginning of planned maintenance actions or after planned maintenance actions? Efficiency of predictive schedules is evaluated using criteria: makespan, total tardiness, flow time, idle time. Efficiency of reactive schedules is evaluated using: solution robustness criterion and quality robustness criterion. This paper is the continuation of the research conducted in the paper [1], where the survey of predictive and reactive scheduling methods is done only for small size scheduling problems.

Scheduling with Time Lags

NARCIS (Netherlands)

X. Zhang (Xiandong)

2010-01-01

textabstractScheduling is essential when activities need to be allocated to scarce resources over time. Motivated by the problem of scheduling barges along container terminals in the Port of Rotterdam, this thesis designs and analyzes algorithms for various on-line and off-line scheduling problems

Automated personnel data base system specifications, Task V. Final report

International Nuclear Information System (INIS)

Bartley, H.J.; Bocast, A.K.; Deppner, F.O.; Harrison, O.J.; Kraas, I.W.

1978-11-01

The full title of this study is 'Development of Qualification Requirements, Training Programs, Career Plans, and Methodologies for Effective Management and Training of Inspection and Enforcement Personnel.' Task V required the development of an automated personnel data base system for NRC/IE. This system is identified as the NRC/IE Personnel, Assignment, Qualifications, and Training System (PAQTS). This Task V report provides the documentation for PAQTS including the Functional Requirements Document (FRD), the Data Requirements Document (DRD), the Hardware and Software Capabilities Assessment, and the Detailed Implementation Schedule. Specific recommendations to facilitate implementation of PAQTS are also included

Schedule Analytics

Science.gov (United States)

2016-04-30

Warfare, Naval Sea Systems Command Acquisition Cycle Time : Defining the Problem David Tate, Institute for Defense Analyses Schedule Analytics Jennifer...research was comprised of the following high- level steps :  Identify and review primary data sources 1...research. However, detailed reviews of the OMB IT Dashboard data revealed that schedule data is highly aggregated. Program start date and program end date

A Study of the Operating Room Scheduling System at Tripler Army Medical Center, Hawaii

Science.gov (United States)

1981-08-01

PROCESSING CLASS V SYSTEM .... .......... . A BIBLIOGRAPHY ....... ........... . . . .. . ii ’I. INTRODUCTIO9 Development of the Problem Convinced that...of the most difficult administrativo tasks that a modern hospital must face, and proposed using a combination of a master posting sheet and a...deal with scheduling problems.9 This particular process also incorporates the two-room system doscribed earlier, and the author admits that this

Optimal task mapping in safety-critical real-time parallel systems

International Nuclear Information System (INIS)

Aussagues, Ch.

1998-01-01

This PhD thesis is dealing with the correct design of safety-critical real-time parallel systems. Such systems constitutes a fundamental part of high-performance systems for command and control that can be found in the nuclear domain or more generally in parallel embedded systems. The verification of their temporal correctness is the core of this thesis. our contribution is mainly in the following three points: the analysis and extension of a programming model for such real-time parallel systems; the proposal of an original method based on a new operator of synchronized product of state machines task-graphs; the validation of the approach by its implementation and evaluation. The work addresses particularly the main problem of optimal task mapping on a parallel architecture, such that the temporal constraints are globally guaranteed, i.e. the timeliness property is valid. The results incorporate also optimally criteria for the sizing and correct dimensioning of a parallel system, for instance in the number of processing elements. These criteria are connected with operational constraints of the application domain. Our approach is based on the off-line analysis of the feasibility of the deadline-driven dynamic scheduling that is used to schedule tasks inside one processor. This leads us to define the synchronized-product, a system of linear, constraints is automatically generated and then allows to calculate a maximum load of a group of tasks and then to verify their timeliness constraints. The communications, their timeliness verification and incorporation to the mapping problem is the second main contribution of this thesis. FInally, the global solving technique dealing with both task and communication aspects has been implemented and evaluated in the framework of the OASIS project in the LETI research center at the CEA/Saclay. (author)

Preemptive scheduling with rejection

NARCIS (Netherlands)

Hoogeveen, H.; Skutella, M.; Woeginger, Gerhard

2003-01-01

We consider the problem of preemptively scheduling a set of n jobs on m (identical, uniformly related, or unrelated) parallel machines. The scheduler may reject a subset of the jobs and thereby incur job-dependent penalties for each rejected job, and he must construct a schedule for the remaining

Preemptive scheduling with rejection

NARCIS (Netherlands)

Hoogeveen, J.A.; Skutella, M.; Woeginger, G.J.; Paterson, M.

2000-01-01

We consider the problem of preemptively scheduling a set of n jobs on m (identical, uniformly related, or unrelated) parallel machines. The scheduler may reject a subset of the jobs and thereby incur job-dependent penalties for each rejected job, and he must construct a schedule for the remaining

Engineering task plan for the annual revision of the rotary mode core sampling system safety equipment list

International Nuclear Information System (INIS)

BOGER, R.M.

1999-01-01

This Engineering Task Plan addresses an effort to provide an update to the RMCS Systems 3 and 4 SEL and DCM in order to incorporate the changes to the authorization basis implemented by HNF-SD-WM-BIO-001, Rev. 0 (Draft), Addendum 5 , Safety Analysis for Rotary Mode Core Sampling. Responsibilities, task description, cost estimate, and schedule are presented

Vehicle scheduling schemes for commercial and emergency logistics integration.

Science.gov (United States)

Li, Xiaohui; Tan, Qingmei

2013-01-01

In modern logistics operations, large-scale logistics companies, besides active participation in profit-seeking commercial business, also play an essential role during an emergency relief process by dispatching urgently-required materials to disaster-affected areas. Therefore, an issue has been widely addressed by logistics practitioners and caught researchers' more attention as to how the logistics companies achieve maximum commercial profit on condition that emergency tasks are effectively and performed satisfactorily. In this paper, two vehicle scheduling models are proposed to solve the problem. One is a prediction-related scheme, which predicts the amounts of disaster-relief materials and commercial business and then accepts the business that will generate maximum profits; the other is a priority-directed scheme, which, firstly groups commercial and emergency business according to priority grades and then schedules both types of business jointly and simultaneously by arriving at the maximum priority in total. Moreover, computer-based simulations are carried out to evaluate the performance of these two models by comparing them with two traditional disaster-relief tactics in China. The results testify the feasibility and effectiveness of the proposed models.

Fog computing job scheduling optimization based on bees swarm

Science.gov (United States)

Bitam, Salim; Zeadally, Sherali; Mellouk, Abdelhamid

2018-04-01

Fog computing is a new computing architecture, composed of a set of near-user edge devices called fog nodes, which collaborate together in order to perform computational services such as running applications, storing an important amount of data, and transmitting messages. Fog computing extends cloud computing by deploying digital resources at the premise of mobile users. In this new paradigm, management and operating functions, such as job scheduling aim at providing high-performance, cost-effective services requested by mobile users and executed by fog nodes. We propose a new bio-inspired optimization approach called Bees Life Algorithm (BLA) aimed at addressing the job scheduling problem in the fog computing environment. Our proposed approach is based on the optimized distribution of a set of tasks among all the fog computing nodes. The objective is to find an optimal tradeoff between CPU execution time and allocated memory required by fog computing services established by mobile users. Our empirical performance evaluation results demonstrate that the proposal outperforms the traditional particle swarm optimization and genetic algorithm in terms of CPU execution time and allocated memory.

Application of an object-oriented framework for task scheduling in an ExPSEE environment Aplicação de um framework orientado a objetos para escalonamento de tarefas no ambiente ExPSEE

Directory of Open Access Journals (Sweden)

Itana Maria de Souza Gimenes

2000-05-01

Full Text Available The application of an object-oriented framework for task scheduling in the ExPSEE Environment is provided. ExPSEE is an experimental Process-centred Software Engineering Environment. However, this framework can be used in other domains such as Workflow Management Systems and Project Management Systems. The task scheduling framework was based on both current methods for the development of frameworks and on an existing architectural pattern for process managers. A prototype of the framework was developed using the Java Language. It shows the experience of extracting a framework from well-known applications that can be reused in practical domains. The research in current paper contributes in the production of a framework and gives insights in the application of novel techniques towards the development of frameworksEste artigo apresenta a aplicação de um framework orientado a objetos para escalonamento de tarefas no ambiente ExPSEE. ExPSEE é um ambiente experimental de engenharia de software orientado a processos, no entanto, o framework também pode ser utilizado em outros domínios tais como sistemas de gerenciamento de workflow e sistemas de gerenciamento de projetos. O framework foi concebido com base em métodos atuais para desenvolvimento de frameworks e em um padrão existente para gerenciadores de processos. Um protótipo do framework foi desenvolvido usando a linguagem Java. O trabalho desenvolvido mostra a experiência de extração de um framework a partir de aplicações conhecidas e que pode ser reutilizado em domínios de aplicação prática. Assim, o presente trabalho contribui tanto na produção de um framework quanto na geração de conhecimento sobre a aplicação de técnicas inovadoras de desenvolvimento de frameworks

Simultaneous personnel and vehicle shift scheduling in the waste management sector.

Science.gov (United States)

Ghiani, Gianpaolo; Guerriero, Emanuela; Manni, Andrea; Manni, Emanuele; Potenza, Agostino

2013-07-01

Urban waste management is becoming an increasingly complex task, absorbing a huge amount of resources, and having a major environmental impact. The design of a waste management system consists in various activities, and one of these is related to the definition of shift schedules for both personnel and vehicles. This activity has a great incidence on the tactical and operational cost for companies. In this paper, we propose an integer programming model to find an optimal solution to the integrated problem. The aim is to determine optimal schedules at minimum cost. Moreover, we design a fast and effective heuristic to face large-size problems. Both approaches are tested on data from a real-world case in Southern Italy and compared to the current practice utilized by the company managing the service, showing that simultaneously solving these problems can lead to significant monetary savings. Copyright © 2013 Elsevier Ltd. All rights reserved.

Designing cyclic appointment schedules for outpatient clinics with scheduled and unscheduled patient arrivals

NARCIS (Netherlands)

Kortbeek, Nikky; Zonderland, Maartje E.; Braaksma, Aleida; Vliegen, Ingrid M. H.; Boucherie, Richard J.; Litvak, Nelly; Hans, Erwin W.

2014-01-01

We present a methodology to design appointment systems for outpatient clinics and diagnostic facilities that offer both walk-in and scheduled service. The developed blueprint for the appointment schedule prescribes the number of appointments to plan per day and the moment on the day to schedule the

Designing cyclic appointment schedules for outpatient clinics with scheduled and unscheduled patient arrivals

NARCIS (Netherlands)

Kortbeek, Nikky; Zonderland, Maartje Elisabeth; Boucherie, Richardus J.; Litvak, Nelli; Hans, Elias W.

2011-01-01

We present a methodology to design appointment systems for outpatient clinics and diagnostic facilities that offer both walk-in and scheduled service. The developed blueprint for the appointment schedule prescribes the number of appointments to plan per day and the moment on the day to schedule the

NRC comprehensive records disposition schedule

International Nuclear Information System (INIS)

1992-03-01

Title 44 United States Code, ''Public Printing and Documents,'' regulations cited in the General Services Administration's (GSA) ''Federal Information Resources Management Regulations'' (FIRMR), Part 201-9, ''Creation, Maintenance, and Use of Records,'' and regulation issued by the National Archives and Records Administration (NARA) in 36 CFR Chapter XII, Subchapter B, ''Records Management,'' require each agency to prepare and issue a comprehensive records disposition schedule that contains the NARA approved records disposition schedules for records unique to the agency and contains the NARA's General Records Schedules for records common to several or all agencies. The approved records disposition schedules specify the appropriate duration of retention and the final disposition for records created or maintained by the NRC. NUREG-0910, Rev. 2, contains ''NRC's Comprehensive Records Disposition Schedule,'' and the original authorized approved citation numbers issued by NARA. Rev. 2 totally reorganizes the records schedules from a functional arrangement to an arrangement by the host office. A subject index and a conversion table have also been developed for the NRC schedules to allow staff to identify the new schedule numbers easily and to improve their ability to locate applicable schedules

Integrating Preventive Maintenance Scheduling As Probability Machine Failure And Batch Production Scheduling

Directory of Open Access Journals (Sweden)

Zahedi Zahedi

2016-06-01

Full Text Available This paper discusses integrated model of batch production scheduling and machine maintenance scheduling. Batch production scheduling uses minimize total actual flow time criteria and machine maintenance scheduling uses the probability of machine failure based on Weibull distribution. The model assumed no nonconforming parts in a planning horizon. The model shows an increase in the number of the batch (length of production run up to a certain limit will minimize the total actual flow time. Meanwhile, an increase in the length of production run will implicate an increase in the number of PM. An example was given to show how the model and algorithm work.

Scheduling with Group Dynamics: a Multi-Robot Task Allocation Algorithm based on Vacancy Chains

National Research Council Canada - National Science Library

Dahl, Torbjorn S; Mataric, Maja J; Sukhatme, Gaurav S

2002-01-01

.... We present a multi-robot task allocation algorithm that is sensitive to group dynamics. Our algorithm is based on vacancy chains, a resource distribution process common in human and animal societies...

Task Action Plans for generic activities: Category A

International Nuclear Information System (INIS)

1978-10-01

The document contains listings of generic technical activities as identified and placed in priority categories by the Office of Nuclear Reactor Regulation (NRR). In addition, it contains definitions of Priority Categories A, B, C, and D and copies of forty approved Task Action Plans for Category A activites. Problem Descriptions for the Category B, C and D tasks are contained in NUREG--0471. This material was developed within the context of NRR's Program for the Resolution of Generic Issues Related to Nuclear Power Plants. As part of this program, the assignment of identified issues to priority categories and the approval of Task Action Plans were made by NRR's Technical Activities Steering Committee, chaired by the Deputy Director, NRR. The original document was published in November 1977. In December 1977 it was updated to add the Task Action Plan for Task No. A-17, Systems Interactions in Nuclear Power Plants. This update adds Task Action Plans for Tasks A-13, A-18, A-21, A-22, A-32, A-37, A-38 and A-40. Task A-41 has been included in Task A-40. In addition, as part of this update, the following changes were made to each Task Action Plan (with the exception of the Task Action Plan for Task A-9): (1) a title page was added that includes information such as Lead NRR Organization, Lead Supervisor, Task Manager, Applicability, and Projected Completion Date; (2) detailed schedule information was deleted; and (3) a new Section 3 entitled Basis for Continued Plant Operation and Licensing Pending Completion of Task was added. These changes represent general reformatting and the addition or deletion of certain general types of information. Some substantive revisions were made to several of the plans, however, a general revision of all of the plans was not undertaken at this time

Outage scheduling and implementation

International Nuclear Information System (INIS)

Allison, J.E.; Segall, P.; Smith, R.R.

1986-01-01

Successful preparation and implementation of an outage schedule and completion of scheduled and emergent work within an identified critical path time frame is a result of careful coordination by Operations, Work Control, Maintenance, Engineering, Planning and Administration and others. At the Fast Flux Test Facility (FFTF) careful planning has been responsible for meeting all scheduled outage critical paths

Masking with faces in central visual field under a variety of temporal schedules.

Science.gov (United States)

Daar, Marwan; Wilson, Hugh R

2015-11-01

With a few exceptions, previous studies have explored masking using either a backward mask or a common onset trailing mask, but not both. In a series of experiments, we demonstrate the use of faces in central visual field as a viable method to study the relationship between these two types of mask schedule. We tested observers in a two alternative forced choice face identification task, where both target and mask comprised synthetic faces, and show that a simple model can successfully predict masking across a variety of masking schedules ranging from a backward mask to a common onset trailing mask and a number of intermediate variations. Our data are well accounted for by a window of sensitivity to mask interference that is centered at around 100 ms. Copyright © 2015 Elsevier Ltd. All rights reserved.

Energy Efficient Real-Time Scheduling Using DPM on Mobile Sensors with a Uniform Multi-Cores

Directory of Open Access Journals (Sweden)

Youngmin Kim

2017-12-01

Full Text Available In wireless sensor networks (WSNs, sensor nodes are deployed for collecting and analyzing data. These nodes use limited energy batteries for easy deployment and low cost. The use of limited energy batteries is closely related to the lifetime of the sensor nodes when using wireless sensor networks. Efficient-energy management is important to extending the lifetime of the sensor nodes. Most effort for improving power efficiency in tiny sensor nodes has focused mainly on reducing the power consumed during data transmission. However, recent emergence of sensor nodes equipped with multi-cores strongly requires attention to be given to the problem of reducing power consumption in multi-cores. In this paper, we propose an energy efficient scheduling method for sensor nodes supporting a uniform multi-cores. We extend the proposed T-Ler plane based scheduling for global optimal scheduling of a uniform multi-cores and multi-processors to enable power management using dynamic power management. In the proposed approach, processor selection for a scheduling and mapping method between the tasks and processors is proposed to efficiently utilize dynamic power management. Experiments show the effectiveness of the proposed approach compared to other existing methods.

Production practices affecting worker task demands in concrete operations: A case study.

Science.gov (United States)

Memarian, Babak; Mitropoulos, Panagiotis

2015-01-01

Construction work involves significant physical, mental, and temporal task demands. Excessive task demands can have negative consequences for safety, errors and production. This exploratory study investigates the magnitude and sources of task demands on a concrete operation, and examines the effect of the production practices on the workers' task demands. The NASA Task Load Index was used to measure the perceived task demands of two work crews. The operation involved the construction of a cast-in-place concrete building under high schedule pressures. Interviews with each crew member were used to identify the main sources of the perceived demands. Extensive field observations and interviews with the supervisors and crews identified the production practices. The workers perceived different level of task demands depending on their role. The production practices influenced the task demands in two ways: (1) practices related to work organization, task design, resource management, and crew management mitigated the task demands; and (2) other practices related to work planning and crew management increased the crew's ability to cope with and adapt to high task demands. The findings identify production practices that regulate the workers' task demands. The effect of task demands on performance is mitigated by the ability to cope with high demands.

Automatic programming via iterated local search for dynamic job shop scheduling.

Science.gov (United States)

Nguyen, Su; Zhang, Mengjie; Johnston, Mark; Tan, Kay Chen

2015-01-01

Dispatching rules have been commonly used in practice for making sequencing and scheduling decisions. Due to specific characteristics of each manufacturing system, there is no universal dispatching rule that can dominate in all situations. Therefore, it is important to design specialized dispatching rules to enhance the scheduling performance for each manufacturing environment. Evolutionary computation approaches such as tree-based genetic programming (TGP) and gene expression programming (GEP) have been proposed to facilitate the design task through automatic design of dispatching rules. However, these methods are still limited by their high computational cost and low exploitation ability. To overcome this problem, we develop a new approach to automatic programming via iterated local search (APRILS) for dynamic job shop scheduling. The key idea of APRILS is to perform multiple local searches started with programs modified from the best obtained programs so far. The experiments show that APRILS outperforms TGP and GEP in most simulation scenarios in terms of effectiveness and efficiency. The analysis also shows that programs generated by APRILS are more compact than those obtained by genetic programming. An investigation of the behavior of APRILS suggests that the good performance of APRILS comes from the balance between exploration and exploitation in its search mechanism.

Scheduling theory, algorithms, and systems

CERN Document Server

Pinedo, Michael L

2016-01-01

This new edition of the well-established text Scheduling: Theory, Algorithms, and Systems provides an up-to-date coverage of important theoretical models in the scheduling literature as well as important scheduling problems that appear in the real world. The accompanying website includes supplementary material in the form of slide-shows from industry as well as movies that show actual implementations of scheduling systems. The main structure of the book, as per previous editions, consists of three parts. The first part focuses on deterministic scheduling and the related combinatorial problems. The second part covers probabilistic scheduling models; in this part it is assumed that processing times and other problem data are random and not known in advance. The third part deals with scheduling in practice; it covers heuristics that are popular with practitioners and discusses system design and implementation issues. All three parts of this new edition have been revamped, streamlined, and extended. The reference...

INEL integrated spent nuclear fuel consolidation task team report

International Nuclear Information System (INIS)

Henry, R.N.; Clark, J.H.; Chipman, N.A.

1994-01-01

This document describes a draft plan and schedule to consolidate spent nuclear fuel (SNF) and special nuclear material (SNW) from aging storage facilities throughout the Idaho National Engineering Laboratory (INEL) to the Idaho Chemical Processing Plant (ICPP) in a safe, cost-effective, and expedient manner. A fully integrated and resource-loaded schedule was developed to achieve consolidation as soon as possible. All of the INEL SNF and SNM management task, projects, and related activities from fiscal year 1994 to the end of the consolidation period are logic-tied and integrated with each other. The schedule and plan are presented to initiate discussion of their implementation, which is expected to generate alternate concepts that can be evaluated using the methodology described in this report. Three perturbations to consolidating SNF as soon as possible are also explored. If the schedule is executed as proposed, the new and on-going consolidation activities will require about 6 years to complete and about $25.3M of additional funding. Reduced annual operating costs are expected to recover the additional investment in about 6.4 years. The total consolidation program as proposed will cost about $66.8M and require about 6 years to recover via reduced operating costs from retired SNF/SNM storage facilities. Detailed schedules and cost estimates for the Test Reactor Area Materials Test Reactor canal transfers are included as an example of the level of detail that is typical of the entire schedule (see Appendix D). The remaining work packages for each of the INEL SNF consolidation transfers are summarized in this document. Detailed cost and resource information is available upon request for any of the SNF consolidation transfers

Gain scheduling using the Youla parameterization

DEFF Research Database (Denmark)

Niemann, Hans Henrik; Stoustrup, Jakob

1999-01-01

Gain scheduling controllers are considered in this paper. The gain scheduling problem where the scheduling parameter vector cannot be measured directly, but needs to be estimated is considered. An estimation of the scheduling vector has been derived by using the Youla parameterization. The use...... in connection with H_inf gain scheduling controllers....

NRC comprehensive records disposition schedule

International Nuclear Information System (INIS)

1982-07-01

Effective January 1, 1982, NRC will institute records retention and disposal practices in accordance with the approved Comprehensive Records Disposition Schedule (CRDS). CRDS is comprised of NRC Schedules (NRCS) 1 to 4 which apply to the agency's program or substantive records and General Records Schedules (GRS) 1 to 22 which apply to housekeeping or facilitative records. The schedules are assembled functionally/organizationally to facilitate their use. Preceding the records descriptions and disposition instructions for both NRCS and GRS, there are brief statements on the organizational units which accumulate the records in each functional area, and other information regarding the schedules' applicability

Performance Evaluation of New Joint EDF-RM Scheduling Algorithm for Real Time Distributed System

Directory of Open Access Journals (Sweden)

Rashmi Sharma

2014-01-01

Full Text Available In Real Time System, the achievement of deadline is the main target of every scheduling algorithm. Earliest Deadline First (EDF, Rate Monotonic (RM, and least Laxity First are some renowned algorithms that work well in their own context. As we know, there is a very common problem Domino's effect in EDF that is generated due to overloading condition (EDF is not working well in overloading situation. Similarly, performance of RM is degraded in underloading condition. We can say that both algorithms are complements of each other. Deadline missing in both events happens because of their utilization bounding strategy. Therefore, in this paper we are proposing a new scheduling algorithm that carries through the drawback of both existing algorithms. Joint EDF-RM scheduling algorithm is implemented in global scheduler that permits task migration mechanism in between processors in the system. In order to check the improved behavior of proposed algorithm we perform simulation. Results are achieved and evaluated in terms of Success Ratio (SR, Average CPU Utilization (ECU, Failure Ratio (FR, and Maximum Tardiness parameters. In the end, the results are compared with the existing (EDF, RM, and D_R_EDF algorithms. It has been shown that the proposed algorithm performs better during overloading condition as well in underloading condition.

Data-oriented scheduling for PROOF

International Nuclear Information System (INIS)

Xu Neng; Guan Wen; Wu Sau Lan; Ganis, Gerardo

2011-01-01

The Parallel ROOT Facility - PROOF - is a distributed analysis system optimized for I/O intensive analysis tasks of HEP data. With LHC entering the analysis phase, PROOF has become a natural ingredient for computing farms at Tier3 level. These analysis facilities will typically be used by a few tenths of users, and can also be federated into a sort of analysis cloud corresponding to the Virtual Organization of the experiment. Proper scheduling is required to guarantee fair resource usage, to enforce priority policies and to optimize the throughput. In this paper we discuss an advanced priority system that we are developing for PROOF. The system has been designed to automatically adapt to unknown length of the tasks, to take into account the data location and availability (including distribution across geographically separated sites), and the {group, user} default priorities. In this system, every element - user, group, dataset, job slot and storage - gets its priority and those priorities are dynamically linked with each other. In order to tune the interplay between the various components, we have designed and started implementing a simulation application that can model various type and size of PROOF clusters. In this application a monitoring package records all the changes of them so that we can easily understand and tune the performance. We will discuss the status of our simulation and show examples of the results we are expecting from it.

Simulated Annealing-Based Ant Colony Algorithm for Tugboat Scheduling Optimization

Directory of Open Access Journals (Sweden)

Qi Xu

2012-01-01

Full Text Available As the “first service station” for ships in the whole port logistics system, the tugboat operation system is one of the most important systems in port logistics. This paper formulated the tugboat scheduling problem as a multiprocessor task scheduling problem (MTSP after analyzing the characteristics of tugboat operation. The model considers factors of multianchorage bases, different operation modes, and three stages of operations (berthing/shifting-berth/unberthing. The objective is to minimize the total operation times for all tugboats in a port. A hybrid simulated annealing-based ant colony algorithm is proposed to solve the addressed problem. By the numerical experiments without the shifting-berth operation, the effectiveness was verified, and the fact that more effective sailing may be possible if tugboats return to the anchorage base timely was pointed out; by the experiments with the shifting-berth operation, one can see that the objective is most sensitive to the proportion of the shifting-berth operation, influenced slightly by the tugboat deployment scheme, and not sensitive to the handling operation times.

Task and work performance on Skylab missions 2, 3, and 4: Time and motion study: Experiment M151

Science.gov (United States)

Kubis, J. F.; Mclaughlin, E. J.; Jackson, J. M.; Rusnak, R.; Mcbride, G. H.; Saxon, S. V.

1977-01-01

Human task performance was evaluated under weightlessness conditions during long duration space flight in order to study the characteristics of the adaptation function. Results show that despite pronounced variability in training schedules and in initial reaction to the Skylab environment, in-flight task performance was relatively equivalent among Skylab crews, and behavioral performance continued to improve from beginning to end of all missions.

Optimal SSN Tasking to Enhance Real-time Space Situational Awareness

Science.gov (United States)

Ferreira, J., III; Hussein, I.; Gerber, J.; Sivilli, R.

2016-09-01

Space Situational Awareness (SSA) is currently constrained by an overwhelming number of resident space objects (RSOs) that need to be tracked and the amount of data these observations produce. The Joint Centralized Autonomous Tasking System (JCATS) is an autonomous, net-centric tool that approaches these SSA concerns from an agile, information-based stance. Finite set statistics and stochastic optimization are used to maintain an RSO catalog and develop sensor tasking schedules based on operator configured, state information-gain metrics to determine observation priorities. This improves the efficiency of sensors to target objects as awareness changes and new information is needed, not at predefined frequencies solely. A net-centric, service-oriented architecture (SOA) allows for JCATS integration into existing SSA systems. Testing has shown operationally-relevant performance improvements and scalability across multiple types of scenarios and against current sensor tasking tools.

Approximating Preemptive Stochastic Scheduling

OpenAIRE

Megow Nicole; Vredeveld Tjark

2009-01-01

We present constant approximative policies for preemptive stochastic scheduling. We derive policies with a guaranteed performance ratio of 2 for scheduling jobs with release dates on identical parallel machines subject to minimizing the sum of weighted completion times. Our policies as well as their analysis apply also to the recently introduced more general model of stochastic online scheduling. The performance guarantee we give matches the best result known for the corresponding determinist...

Feasibility of the adaptive and automatic presentation of tasks (ADAPT system for rehabilitation of upper extremity function post-stroke

Directory of Open Access Journals (Sweden)

Choi Younggeun

2011-08-01

Full Text Available Abstract Background Current guidelines for rehabilitation of arm and hand function after stroke recommend that motor training focus on realistic tasks that require reaching and manipulation and engage the patient intensively, actively, and adaptively. Here, we investigated the feasibility of a novel robotic task-practice system, ADAPT, designed in accordance with such guidelines. At each trial, ADAPT selects a functional task according to a training schedule and with difficulty based on previous performance. Once the task is selected, the robot picks up and presents the corresponding tool, simulates the dynamics of the tasks, and the patient interacts with the tool to perform the task. Methods Five participants with chronic stroke with mild to moderate impairments (> 9 months post-stroke; Fugl-Meyer arm score 49.2 ± 5.6 practiced four functional tasks (selected out of six in a pre-test with ADAPT for about one and half hour and 144 trials in a pseudo-random schedule of 3-trial blocks per task. Results No adverse events occurred and ADAPT successfully presented the six functional tasks without human intervention for a total of 900 trials. Qualitative analysis of trajectories showed that ADAPT simulated the desired task dynamics adequately, and participants reported good, although not excellent, task fidelity. During training, the adaptive difficulty algorithm progressively increased task difficulty leading towards an optimal challenge point based on performance; difficulty was then continuously adjusted to keep performance around the challenge point. Furthermore, the time to complete all trained tasks decreased significantly from pretest to one-hour post-test. Finally, post-training questionnaires demonstrated positive patient acceptance of ADAPT. Conclusions ADAPT successfully provided adaptive progressive training for multiple functional tasks based on participant's performance. Our encouraging results establish the feasibility of ADAPT; its

Schedules of Controlled Substances: Temporary Placement of ortho-Fluorofentanyl, Tetrahydrofuranyl Fentanyl, and Methoxyacetyl Fentanyl Into Schedule I. Temporary amendment; temporary scheduling order.

Science.gov (United States)

2017-10-26

The Administrator of the Drug Enforcement Administration is issuing this temporary scheduling order to schedule the synthetic opioids, N-(2-fluorophenyl)-N-(1-phenethylpiperidin-4-yl)propionamide (ortho-fluorofentanyl or 2-fluorofentanyl), N-(1-phenethylpiperidin-4-yl)-N-phenyltetrahydrofuran-2-carboxamide (tetrahydrofuranyl fentanyl), and 2-methoxy-N-(1-phenethylpiperidin-4-yl)-N-phenylacetamide (methoxyacetyl fentanyl), into Schedule I. This action is based on a finding by the Administrator that the placement of ortho-fluorofentanyl, tetrahydrofuranyl fentanyl, and methoxyacetyl fentanyl into Schedule I of the Controlled Substances Act is necessary to avoid an imminent hazard to the public safety. As a result of this order, the regulatory controls and administrative, civil, and criminal sanctions applicable to Schedule I controlled substances will be imposed on persons who handle (manufacture, distribute, reverse distribute, import, export, engage in research, conduct instructional activities or chemical analysis, or possess), or propose to handle, ortho-fluorofentanyl, tetrahydrofuranyl fentanyl, and methoxyacetyl fentanyl.

Analysis and Enhancement of IEEE 802.15.4e DSME Beacon Scheduling Model

Directory of Open Access Journals (Sweden)

Kwang-il Hwang

2014-01-01

Full Text Available In order to construct a successful Internet of things (IoT, reliable network construction and maintenance in a sensor domain should be supported. However, IEEE 802.15.4, which is the most representative wireless standard for IoT, still has problems in constructing a large-scale sensor network, such as beacon collision. To overcome some problems in IEEE 802.15.4, the 15.4e task group proposed various different modes of operation. Particularly, the IEEE 802.15.4e deterministic and synchronous multichannel extension (DSME mode presents a novel scheduling model to solve beacon collision problems. However, the DSME model specified in the 15.4e draft does not present a concrete design model but a conceptual abstract model. Therefore, in this paper we introduce a DSME beacon scheduling model and present a concrete design model. Furthermore, validity and performance of DSME are evaluated through experiments. Based on experiment results, we analyze the problems and limitations of DSME, present solutions step by step, and finally propose an enhanced DSME beacon scheduling model. Through additional experiments, we prove the performance superiority of enhanced DSME.

Congestion game scheduling for virtual drug screening optimization

Science.gov (United States)

Nikitina, Natalia; Ivashko, Evgeny; Tchernykh, Andrei

2018-02-01

In virtual drug screening, the chemical diversity of hits is an important factor, along with their predicted activity. Moreover, interim results are of interest for directing the further research, and their diversity is also desirable. In this paper, we consider a problem of obtaining a diverse set of virtual screening hits in a short time. To this end, we propose a mathematical model of task scheduling for virtual drug screening in high-performance computational systems as a congestion game between computational nodes to find the equilibrium solutions for best balancing the number of interim hits with their chemical diversity. The model considers the heterogeneous environment with workload uncertainty, processing time uncertainty, and limited knowledge about the input dataset structure. We perform computational experiments and evaluate the performance of the developed approach considering organic molecules database GDB-9. The used set of molecules is rich enough to demonstrate the feasibility and practicability of proposed solutions. We compare the algorithm with two known heuristics used in practice and observe that game-based scheduling outperforms them by the hit discovery rate and chemical diversity at earlier steps. Based on these results, we use a social utility metric for assessing the efficiency of our equilibrium solutions and show that they reach greatest values.

CARMENES instrument control system and operational scheduler

Science.gov (United States)

Garcia-Piquer, Alvaro; Guàrdia, Josep; Colomé, Josep; Ribas, Ignasi; Gesa, Lluis; Morales, Juan Carlos; Pérez-Calpena, Ana; Seifert, Walter; Quirrenbach, Andreas; Amado, Pedro J.; Caballero, José A.; Reiners, Ansgar

2014-07-01

The main goal of the CARMENES instrument is to perform high-accuracy measurements of stellar radial velocities (1m/s) with long-term stability. CARMENES will be installed in 2015 at the 3.5 m telescope in the Calar Alto Observatory (Spain) and it will be equipped with two spectrographs covering from the visible to the near-infrared. It will make use of its near-IR capabilities to observe late-type stars, whose peak of the spectral energy distribution falls in the relevant wavelength interval. The technology needed to develop this instrument represents a challenge at all levels. We present two software packages that play a key role in the control layer for an efficient operation of the instrument: the Instrument Control System (ICS) and the Operational Scheduler. The coordination and management of CARMENES is handled by the ICS, which is responsible for carrying out the operations of the different subsystems providing a tool to operate the instrument in an integrated manner from low to high user interaction level. The ICS interacts with the following subsystems: the near-IR and visible channels, composed by the detectors and exposure meters; the calibration units; the environment sensors; the front-end electronics; the acquisition and guiding module; the interfaces with telescope and dome; and, finally, the software subsystems for operational scheduling of tasks, data processing, and data archiving. We describe the ICS software design, which implements the CARMENES operational design and is planned to be integrated in the instrument by the end of 2014. The CARMENES operational scheduler is the second key element in the control layer described in this contribution. It is the main actor in the translation of the survey strategy into a detailed schedule for the achievement of the optimization goals. The scheduler is based on Artificial Intelligence techniques and computes the survey planning by combining the static constraints that are known a priori (i.e., target

Modeling the Scheduling of Eye Movements and Manual Responses in Performing a Sequence of Discrete Tasks

Science.gov (United States)

Wu, Shu-Chieh; Remington, Roger W.; Lewis, Richard

2006-01-01

Common tasks in daily life are often accomplished by a sequence of actions that interleave information acquisition through the eyes and action execution by the hands. How are eye movements coordinated with the release of manual responses and how may their coordination be represented at the level of component mental operations? We have previously presented data from a typing-like task requiring separate choice responses to a series of five stimuli. We found a consistent pattern of results in both motor and ocular timing, and hypothesized possible relationships among underlying components. Here we report a model of that task, which demonstrates how the observed timing of eye movements to successive stimuli could be accounted for by assuming systems: an open-loop system generating saccades at a periodic rate, and a closed-loop system commanding a saccade based on stimulus processing. We relate this model to models of reading and discuss the motivation for dual control.

A task management system for compliance with health, safety, and environmental regulations

International Nuclear Information System (INIS)

Crump, J.J.; O'Gorman, T.P.

1992-01-01

Shell Western E and P Inc. (SWEPI) has developed a new computer system to help it comply with health, safety, and environmental (HS and E) regulations. It is a task management system that functions at the detailed inventory level. It schedules work, instructs operations, and records compliance status. This article discusses design and development of the system

Revisiting Symbiotic Job Scheduling

OpenAIRE

Eyerman , Stijn; Michaud , Pierre; Rogiest , Wouter

2015-01-01

International audience; —Symbiotic job scheduling exploits the fact that in a system with shared resources, the performance of jobs is impacted by the behavior of other co-running jobs. By coscheduling combinations of jobs that have low interference, the performance of a system can be increased. In this paper, we investigate the impact of using symbiotic job scheduling for increasing throughput. We find that even for a theoretically optimal scheduler, this impact is very low, despite the subs...

SPANR planning and scheduling

Science.gov (United States)

Freund, Richard F.; Braun, Tracy D.; Kussow, Matthew; Godfrey, Michael; Koyama, Terry

2001-07-01

SPANR (Schedule, Plan, Assess Networked Resources) is (i) a pre-run, off-line planning and (ii) a runtime, just-in-time scheduling mechanism. It is designed to support primarily commercial applications in that it optimizes throughput rather than individual jobs (unless they have highest priority). Thus it is a tool for a commercial production manager to maximize total work. First the SPANR Planner is presented showing the ability to do predictive 'what-if' planning. It can answer such questions as, (i) what is the overall effect of acquiring new hardware or (ii) what would be the effect of a different scheduler. The ability of the SPANR Planner to formulate in advance tree-trimming strategies is useful in several commercial applications, such as electronic design or pharmaceutical simulations. The SPANR Planner is demonstrated using a variety of benchmarks. The SPANR Runtime Scheduler (RS) is briefly presented. The SPANR RS can provide benefit for several commercial applications, such as airframe design and financial applications. Finally a design is shown whereby SPANR can provide scheduling advice to most resource management systems.

Self-scheduling with Microsoft Excel.

Science.gov (United States)

Irvin, S A; Brown, H N

1999-01-01

Excessive time was being spent by the emergency department (ED) staff, head nurse, and unit secretary on a complex 6-week manual self-scheduling system. This issue, plus inevitable errors and staff dissatisfaction, resulted in a manager-lead initiative to automate elements of the scheduling process using Microsoft Excel. The implementation of this initiative included: common coding of all 8-hour and 12-hour shifts, with each 4-hour period represented by a cell; the creation of a 6-week master schedule using the "count-if" function of Excel based on current staffing guidelines; staff time-off requests then entered by the department secretary; the head nurse, with staff input, then fine-tuned the schedule to provide even unit coverage. Outcomes of these changes included an increase in staff satisfaction, time saved by the head nurse, and staff work time saved because there was less arguing about the schedule. Ultimately, the automated self-scheduling method was expanded to the entire 700-bed hospital.

Immunization Schedules for Adults

Science.gov (United States)

... ACIP Vaccination Recommendations Why Immunize? Vaccines: The Basics Immunization Schedule for Adults (19 Years of Age and ... diseases that can be prevented by vaccines . 2018 Immunization Schedule Recommended Vaccinations for Adults by Age and ...

Instant Childhood Immunization Schedule

Science.gov (United States)

... Recommendations Why Immunize? Vaccines: The Basics Instant Childhood Immunization Schedule Recommend on Facebook Tweet Share Compartir Get ... date. See Disclaimer for additional details. Based on Immunization Schedule for Children 0 through 6 Years of ...

Nontraditional work schedules for pharmacists.

Science.gov (United States)

Mahaney, Lynnae; Sanborn, Michael; Alexander, Emily

2008-11-15

Nontraditional work schedules for pharmacists at three institutions are described. The demand for pharmacists and health care in general continues to increase, yet significant material changes are occurring in the pharmacy work force. These changing demographics, coupled with historical vacancy rates and turnover trends for pharmacy staff, require an increased emphasis on workplace changes that can improve staff recruitment and retention. At William S. Middleton Memorial Veterans Affairs Hospital in Madison, Wisconsin, creative pharmacist work schedules and roles are now mainstays to the recruitment and retention of staff. The major challenge that such scheduling presents is the 8 hours needed to prepare a six-week schedule. Baylor Medical Center at Grapevine in Dallas, Texas, has a total of 45 pharmacy employees, and slightly less than half of the 24.5 full-time-equivalent staff work full-time, with most preferring to work one, two, or three days per week. As long as the coverage needs of the facility are met, Envision Telepharmacy in Alpine, Texas, allows almost any scheduling arrangement preferred by individual pharmacists or the pharmacist group covering the facility. Staffing involves a great variety of shift lengths and intervals, with shifts ranging from 2 to 10 hours. Pharmacy leaders must be increasingly aware of opportunities to provide staff with unique scheduling and operational enhancements that can provide for a better work-life balance. Compressed workweeks, job-sharing, and team scheduling were the most common types of alternative work schedules implemented at three different institutions.

Scheduling algorithms for saving energy and balancing load

Energy Technology Data Exchange (ETDEWEB)

Antoniadis, Antonios

2012-08-03

In this thesis we study problems of scheduling tasks in computing environments. We consider both the modern objective function of minimizing energy consumption, and the classical objective of balancing load across machines. We first investigate offline deadline-based scheduling in the setting of a single variable-speed processor that is equipped with a sleep state. The objective is that of minimizing the total energy consumption. Apart from settling the complexity of the problem by showing its NP-hardness, we provide a lower bound of 2 for general convex power functions, and a particular natural class of schedules called s{sub crit}-schedules. We also present an algorithmic framework for designing good approximation algorithms. For general convex power functions our framework improves the best known approximation-factor from 2 to 4/3. This factor can be reduced even further to 137/117 for a specific well-motivated class of power functions. Furthermore, we give tight bounds to show that our framework returns optimal s{sub crit}-schedules for the two aforementioned power-function classes. We then focus on the multiprocessor setting where each processor has the ability to vary its speed. Job migration is allowed, and we again consider classical deadline-based scheduling with the objective of energy minimization. We first study the offline problem and show that optimal schedules can be computed efficiently in polynomial time for any convex and non-decreasing power function. Our algorithm relies on repeated maximum flow computations. Regarding the online problem and power functions P(s) = s{sup {alpha}}, where s is the processor speed and {alpha} > 1 a constant, we extend the two well-known single-processor algorithms Optimal Available and Average Rate. We prove that Optimal Available is {alpha}{sup {alpha}}-competitive as in the single-processor case. For Average Rate we show a competitive factor of (2{alpha}){sup {alpha}}/2 + 1, i.e., compared to the single

BIM-BASED SCHEDULING OF CONSTRUCTION

DEFF Research Database (Denmark)

Andersson, Niclas; Büchmann-Slorup, Rolf

2010-01-01

The potential of BIM is generally recognized in the construction industry, but the practical application of BIM for management purposes is, however, still limited among contractors. The objective of this study is to review the current scheduling process of construction in light of BIM...... and communicate. Scheduling on the detailed level, on the other hand, follows a stipulated approach to scheduling, i.e. the Last Planner System (LPS), which is characterized by involvement of all actors in the construction phase. Thus, the major challenge when implementing BIM-based scheduling is to improve...

HUMAN-MACHINE INTERACTION IN SOLVING TASKS OF THE PLANNING DEPARTMENT

Directory of Open Access Journals (Sweden)

Boris Alekseyevich Kucherov

2017-12-01

Full Text Available The paper discusses issues of human-machine interaction in solving tasks of the planning department under severe resource restrictions using information technology. The negative factors influencing specialists of the planning department in solving their tasks under the given circumstances are shown. Specific features of designing the user interface in this subject area are noted. Directions to increase the efficiency of reaction of the planning department’s specialists to change the current situation by visual and sound notification of various events are marked. Various ways to develop user interface to generate a conflict-free plan under severe resource restrictions are considered. The variants of informative presentation of operational and statistical information to stakeholders are analyzed. These issues are discussed by the example of the planning department which solves the tasks of allocation of control facilities for spacecraft (a subset of satellite range scheduling problem,

Network scheduling at Belene NPP construction site

International Nuclear Information System (INIS)

Matveev, A.

2010-01-01

Four types of schedules differing in the level of their detail are singled out to enhance the efficiency of Belene NPP Project implementation planning and monitoring: Level 1 Schedule–Summary Integrated Overall Time Schedule (SIOTS) is an appendix to EPC Contract. The main purpose of SIOTS is the large scale presentation of the current information on the Project implementation. Level 2 Schedule–Integrated Overall Time Schedule (IOTS)is the contract schedule for the Contractor (ASE JSC) and their subcontractors.The principal purpose of IOTS is the work progress planning and monitoring, the analysis of the effect of activities implementation upon the progress of the Project as a whole. IOTS is the reporting schedule at the Employer –Contractor level. Level 3 Schedules, Detail Time Schedules(DTS) are developed by those who actually perform the work and are agreed upon with Atomstroyexport JSC.The main purpose of DTS is the detail planning of Atomstroyexport subcontractor's activities. DTSare the reporting schedules at the level of Contractor-Subcontractor. Level 4 Schedules are the High Detail Time Schedules (HDTS), which are the day-to-day plans of work implementation and are developed, as a rule, for a week's time period.Each lower level time schedule details the activities of the higher level time schedule

Parents' Family Time and Work Schedules: The Split-Shift Schedule in Spain

NARCIS (Netherlands)

Gracia, P.; Kalmijn, M.

2016-01-01

This study used data on couples from the 2003 Spanish Time Use Survey (N = 1,416) to analyze how work schedules are associated with family, couple, parent–child, and non-family leisure activities. Spain is clearly an interesting case for the institutionalized split-shift schedule, a long lunch break

Low Latency Workflow Scheduling and an Application of Hyperspectral Brightness Temperatures

Science.gov (United States)

Nguyen, P. T.; Chapman, D. R.; Halem, M.

2012-12-01

New system analytics for Big Data computing holds the promise of major scientific breakthroughs and discoveries from the exploration and mining of the massive data sets becoming available to the science community. However, such data intensive scientific applications face severe challenges in accessing, managing and analyzing petabytes of data. While the Hadoop MapReduce environment has been successfully applied to data intensive problems arising in business, there are still many scientific problem domains where limitations in the functionality of MapReduce systems prevent its wide adoption by those communities. This is mainly because MapReduce does not readily support the unique science discipline needs such as special science data formats, graphic and computational data analysis tools, maintaining high degrees of computational accuracies, and interfacing with application's existing components across heterogeneous computing processors. We address some of these limitations by exploiting the MapReduce programming model for satellite data intensive scientific problems and address scalability, reliability, scheduling, and data management issues when dealing with climate data records and their complex observational challenges. In addition, we will present techniques to support the unique Earth science discipline needs such as dealing with special science data formats (HDF and NetCDF). We have developed a Hadoop task scheduling algorithm that improves latency by 2x for a scientific workflow including the gridding of the EOS AIRS hyperspectral Brightness Temperatures (BT). This workflow processing algorithm has been tested at the Multicore Computing Center private Hadoop based Intel Nehalem cluster, as well as in a virtual mode under the Open Source Eucalyptus cloud. The 55TB AIRS hyperspectral L1b Brightness Temperature record has been gridded at the resolution of 0.5x1.0 degrees, and we have computed a 0.9 annual anti-correlation to the El Nino Southern oscillation in

A Literature Survey for Earliness/Tardiness Scheduling Problems with Learning Effect

Directory of Open Access Journals (Sweden)

Mesut Cemil İŞLER

2009-02-01

Full Text Available When a task or work is done continuously, there will be an experience so following times needs of required resources (manpower, materials, etc. will be reduced. This learning curve described first by Wright. Wright determined how workmanship costs decreased while proceed plain increasing. This investigations correctness found consistent by plain producers. Learning effect is an effect that, works can be done in shorter time in the rate of repeat of work with repeating same or similar works in production process. Nowadays classical production systems adapted more acceptable systems with new approaches. Just in time production system (JIT philosophy is one of the most important production system philosophies. JIT which is known production without stock stands on using all product resources optimum. Minimization problem of Earliness/Tardiness finishing penalty, which we can describe Just in time scheduling, appeared by inspired from JIT philosophy. In this study, there is literature survey which directed to earliness/tardiness performance criteria and learning effect processing in scheduling and as a result of this it is obtained some establishing for literature.

Using Improved Ant Colony Algorithm to Investigate EMU Circulation Scheduling Problem

Directory of Open Access Journals (Sweden)

Yu Zhou

2014-01-01

Full Text Available High-speed railway is one of the most important ways to solve the long-standing travel difficulty problem in China. However, due to the high acquisition and maintenance cost, it is impossible for decision-making departments to purchase enough EMUs to satisfy the explosive travel demand. Therefore, there is an urgent need to study how to utilize EMU more efficiently and reduce costs in the case of completing a given task in train diagram. In this paper, an EMU circulation scheduling model is built based on train diagram constraints, maintenance constraints, and so forth; in the model solving process, an improved ACA algorithm has been designed. A case study is conducted to verify the feasibility of the model. Moreover, contrast tests have been carried out to compare the efficiency between the improved ACA and the traditional approaches. The results reveal that improved ACA method can solve the model with less time and the quality of each representative index is much better, which means that efficiency of the improved ACA method is higher and better scheduling scheme can be obtained.

Prioritized schedule for review of industrial safety and occupational health programs

International Nuclear Information System (INIS)

1996-12-01

This document provides the rationale and criteria for developing a schedule for reviewing the Industrial Safety and Occupational Health programs for the Management and Operating Contractor (MOC) of the Waste Isolation Pilot Plant. The reviews will evaluate the MOC's compliance with applicable Department of Energy (DOE) orders and regulatory requirements. The scope of this task includes developing prioritization criteria, determining the review priority of each program based upon the criteria, identifying review requirements for each program, and preparing a detailed review schedule. In keeping with the Carlsbad Area Office (CAO) structure for the review of site activities, these review activities will be addressed as surveillances, although the original basis for this requirement refers to these activities as appraisals. Surveillances and appraisals are the same within this document. Surveillances are defined as: ''The act of monitoring or observing to verify whether an item, activity, system, or process conforms to specified requirements. Surveillance of a technical work activity is normally done in real time, i.e., the surveillance is accomplished as the work is being performed.''

Future aircraft networks and schedules

Science.gov (United States)

Shu, Yan

2011-07-01

Because of the importance of air transportation scheduling, the emergence of small aircraft and the vision of future fuel-efficient aircraft, this thesis has focused on the study of aircraft scheduling and network design involving multiple types of aircraft and flight services. It develops models and solution algorithms for the schedule design problem and analyzes the computational results. First, based on the current development of small aircraft and on-demand flight services, this thesis expands a business model for integrating on-demand flight services with the traditional scheduled flight services. This thesis proposes a three-step approach to the design of aircraft schedules and networks from scratch under the model. In the first step, both a frequency assignment model for scheduled flights that incorporates a passenger path choice model and a frequency assignment model for on-demand flights that incorporates a passenger mode choice model are created. In the second step, a rough fleet assignment model that determines a set of flight legs, each of which is assigned an aircraft type and a rough departure time is constructed. In the third step, a timetable model that determines an exact departure time for each flight leg is developed. Based on the models proposed in the three steps, this thesis creates schedule design instances that involve almost all the major airports and markets in the United States. The instances of the frequency assignment model created in this thesis are large-scale non-convex mixed-integer programming problems, and this dissertation develops an overall network structure and proposes iterative algorithms for solving these instances. The instances of both the rough fleet assignment model and the timetable model created in this thesis are large-scale mixed-integer programming problems, and this dissertation develops subproblem schemes for solving these instances. Based on these solution algorithms, this dissertation also presents

Conception of Self-Construction Production Scheduling System

Science.gov (United States)

Xue, Hai; Zhang, Xuerui; Shimizu, Yasuhiro; Fujimura, Shigeru

With the high speed innovation of information technology, many production scheduling systems have been developed. However, a lot of customization according to individual production environment is required, and then a large investment for development and maintenance is indispensable. Therefore now the direction to construct scheduling systems should be changed. The final objective of this research aims at developing a system which is built by it extracting the scheduling technique automatically through the daily production scheduling work, so that an investment will be reduced. This extraction mechanism should be applied for various production processes for the interoperability. Using the master information extracted by the system, production scheduling operators can be supported to accelerate the production scheduling work easily and accurately without any restriction of scheduling operations. By installing this extraction mechanism, it is easy to introduce scheduling system without a lot of expense for customization. In this paper, at first a model for expressing a scheduling problem is proposed. Then the guideline to extract the scheduling information and use the extracted information is shown and some applied functions are also proposed based on it.

Immunization Schedules for Infants and Children

Science.gov (United States)

... ACIP Vaccination Recommendations Why Immunize? Vaccines: The Basics Immunization Schedule for Infants and Children (Birth through 6 ... any questions please talk to your doctor. 2018 Immunization Schedule Recommended Vaccinations for Infants and Children Schedule ...

A Formal Product-Line Engineering Approach for Schedulers

NARCIS (Netherlands)

Orhan, Güner; Aksit, Mehmet; Rensink, Arend; Jololian, Leon; Robbins, David E.; Fernandes, Steven L.

2017-01-01

Scheduling techniques have been applied to a large category of software systems, such as, processor scheduling in operating systems, car scheduling in elevator systems, facility scheduling at airports, antenna scheduling in radar systems, scheduling of events, control signals and data in

Robust and Flexible Scheduling with Evolutionary Computation

DEFF Research Database (Denmark)

Jensen, Mikkel T.

Over the last ten years, there have been numerous applications of evolutionary algorithms to a variety of scheduling problems. Like most other research on heuristic scheduling, the primary aim of the research has been on deterministic formulations of the problems. This is in contrast to real world...... scheduling problems which are usually not deterministic. Usually at the time the schedule is made some information about the problem and processing environment is available, but this information is uncertain and likely to change during schedule execution. Changes frequently encountered in scheduling...... environments include machine breakdowns, uncertain processing times, workers getting sick, materials being delayed and the appearance of new jobs. These possible environmental changes mean that a schedule which was optimal for the information available at the time of scheduling can end up being highly...

Serial or overlapping processing in multitasking as individual preference: Effects of stimulus preview on task switching and concurrent dual-task performance.

Science.gov (United States)

Reissland, Jessika; Manzey, Dietrich

2016-07-01

-grained analyses of response scheduling again revealed individual differences regarding the preference for strictly serial processing vs. some sort of task interleaving and overlapping processing. However, neither group showed a striking benefit in dual-task efficiency, although the results show that the costs of multitasking can partly be compensated by overlapping processing. Copyright © 2016 Elsevier B.V. All rights reserved.

The development of KMRR schedule and progress control system (KSPCS) for the master schedule of KMRR project

International Nuclear Information System (INIS)

Choi, Chang Woong; Lee, Tae Joon; Kim, Joon Yun; Cho, Yun Ho; Hah, Jong Hyun

1993-07-01

This report was to development the computerized schedule and progress control system for the master schedule of KMRR project with ARTEMIS 7000/386 CM (Ver. 7.4.2.) based on project management theory (PERT/CPM, PDM, and S-curve). This system has been efficiently used for KMRR master schedule and will be utilized for the detail scheduling of KMRR project. (Author) 23 refs., 26 figs., 52 tabs

The development of KMRR schedule and progress control system (KSPCS) for the master schedule of KMRR project

Energy Technology Data Exchange (ETDEWEB)

Choi, Chang Woong; Lee, Tae Joon; Kim, Joon Yun; Cho, Yun Ho; Hah, Jong Hyun [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

1993-07-01

This report was to development the computerized schedule and progress control system for the master schedule of KMRR project with ARTEMIS 7000/386 CM (Ver. 7.4.2.) based on project management theory (PERT/CPM, PDM, and S-curve). This system has been efficiently used for KMRR master schedule and will be utilized for the detail scheduling of KMRR project. (Author) 23 refs., 26 figs., 52 tabs.

Comparative study of heuristics algorithms in solving flexible job shop scheduling problem with condition based maintenance

Directory of Open Access Journals (Sweden)

Yahong Zheng

2014-05-01

Full Text Available Purpose: This paper focuses on a classic optimization problem in operations research, the flexible job shop scheduling problem (FJSP, to discuss the method to deal with uncertainty in a manufacturing system.Design/methodology/approach: In this paper, condition based maintenance (CBM, a kind of preventive maintenance, is suggested to reduce unavailability of machines. Different to the simultaneous scheduling algorithm (SSA used in the previous article (Neale & Cameron,1979, an inserting algorithm (IA is applied, in which firstly a pre-schedule is obtained through heuristic algorithm and then maintenance tasks are inserted into the pre-schedule scheme.Findings: It is encouraging that a new better solution for an instance in benchmark of FJSP is obtained in this research. Moreover, factually SSA used in literature for solving normal FJSPPM (FJSP with PM is not suitable for the dynamic FJSPPM. Through application in the benchmark of normal FJSPPM, it is found that although IA obtains inferior results compared to SSA used in literature, it performs much better in executing speed.Originality/value: Different to traditional scheduling of FJSP, uncertainty of machines is taken into account, which increases the complexity of the problem. An inserting algorithm (IA is proposed to solve the dynamic scheduling problem. It is stated that the quality of the final result depends much on the quality of the pre-schedule obtained during the procedure of solving a normal FJSP. In order to find the best solution of FJSP, a comparative study of three heuristics is carried out, the integrated GA, ACO and ABC. In the comparative study, we find that GA performs best in the three heuristic algorithms. Meanwhile, a new better solution for an instance in benchmark of FJSP is obtained in this research.

Computation Offloading for Frame-Based Real-Time Tasks under Given Server Response Time Guarantees

Directory of Open Access Journals (Sweden)

Anas S. M. Toma

2014-11-01

Full Text Available Computation offloading has been adopted to improve the performance of embedded systems by offloading the computation of some tasks, especially computation-intensive tasks, to servers or clouds. This paper explores computation offloading for real-time tasks in embedded systems, provided given response time guarantees from the servers, to decide which tasks should be offloaded to get the results in time. We consider frame-based real-time tasks with the same period and relative deadline. When the execution order of the tasks is given, the problem can be solved in linear time. However, when the execution order is not specified, we prove that the problem is NP-complete. We develop a pseudo-polynomial-time algorithm for deriving feasible schedules, if they exist.  An approximation scheme is also developed to trade the error made from the algorithm and the complexity. Our algorithms are extended to minimize the period/relative deadline of the tasks for performance maximization. The algorithms are evaluated with a case study for a surveillance system and synthesized benchmarks.

78 FR 21818 - Schedules of Controlled Substances: Placement of Methylone Into Schedule I

Science.gov (United States)

2013-04-12

..., methamphetamine, and MDMA, Schedule I and II substances. These effects included elevated body temperature... of reuptake of monoamines, and in vivo studies (microdialysis, locomotor activity, body temperature.... Yet another commenter claimed that Schedule I placement would ``cripple efforts at learning,'' make it...

Effects of Simulated Surface Effect Ship Motions on Crew Habitability. Phase II. Volume 3. Visual-Motor Tasks and Subjective Evaluations

Science.gov (United States)

1977-05-01

simulated rmotions ; and detaiJl.s on the daily work/rest schedule, as well as the overall run ,schedule (Ref.20). * Volume 4, "Crew Cognitive Functions...the outset: 1) the very small sampling of well- motivated crewmen made it difficult to generalize the results to a wider population; and 2) the...a:; backups. Selection of primary crewmen was based on satisfactory task learning and motivation demonstrated during the training period, any minor

Decentralized Ground Staff Scheduling

DEFF Research Database (Denmark)

Sørensen, M. D.; Clausen, Jens

2002-01-01

scheduling is investigated. The airport terminal is divided into zones, where each zone consists of a set of stands geographically next to each other. Staff is assigned to work in only one zone and the staff scheduling is planned decentralized for each zone. The advantage of this approach is that the staff...... work in a smaller area of the terminal and thus spends less time walking between stands. When planning decentralized the allocation of stands to flights influences the staff scheduling since the workload in a zone depends on which flights are allocated to stands in the zone. Hence solving the problem...... depends on the actual stand allocation but also on the number of zones and the layout of these. A mathematical model of the problem is proposed, which integrates the stand allocation and the staff scheduling. A heuristic solution method is developed and applied on a real case from British Airways, London...

Schedule control in Ling Ao nuclear power project

International Nuclear Information System (INIS)

Xie Ahai

2007-01-01

Ling Ao Nuclear Power Station (LANP) is first one built up by self-reliance in China with power capacity 990x2 MWe. The results of quality control, schedule control and cost control are satisfactory. The commercial operation days of Unit 1 and Unit 2 were 28th May 2002 and 8th Jan. 2003 respectively, which were 48 days and 66 days in advance of the project schedule. This paper presents the practices of self-reliance schedule control system in LANP. The paper includes 10 sections: schedule control system; targets of schedule control; schedule control at early stage of project; construction schedule; scheduling practice; Point curves; schedule control of design and procurement; a good practice of construction schedule control on site; commissioning and startup schedule; schedule control culture. Three figures are attached. The main contents of the self-reliance schedule control system are as follows: to draw up reasonable schedules and targets; to setup management mechanism and procedures; to organize powerful project management team; to establish close monitoring system; to provide timely progress reports and statistics information. Five kinds of schedule control targets are introduced, i.e. bar-chart schedule; milesones; Point curves; interface management; hydraulic test schedule of auxiliary piping loops; EMR/EMC/EESR issuance schedules. Six levels of bar-chart schedules were adopted in LANP, but the bar-chart schedules were not satisfactory for complicated erection condition on site, even using six levels of schedules. So a kind of Point curves was developed and their advantages are explained. Scheduling method of three elements: activity, duration, logic, which was adopted in LANP, is introduced. The duration of each piping activities in LANP level 2 project schedule was calculated based on the relevant working Point quantities. The analysis and adjustment of Point curves are illustrated, i.e. balance of monthly quantities; possible production in the peakload