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Optimal task allocation and scheduling for power saving in multiprocessor systems

Publication Type : Conference Proceedings

Publisher : 2014 Power and Energy Systems Conference: Towards Sustainable Energy, PESTSE 2014

Source : 2014 Power and Energy Systems Conference: Towards Sustainable Energy, PESTSE 2014, IEEE Computer Society, Bangalore (2014)

Url : http://www.scopus.com/inward/record.url?eid=2-s2.0-84901023933&partnerID=40&md5=4c0f248a5e8a9a777da2762571b30265

ISBN : 9781479934201

Keywords : Consumption reductions, Dynamic frequency scaling, Dynamic voltage frequency scaling, energy conservation, Energy utilization, Fault tolerance, Functional requirement, Multi processor systems, Optimal task allocations, Power consumption reduction, Processor utilization, Scheduling, Task allocation, Voltage scaling

Campus : Coimbatore

School : School of Engineering

Department : Electrical and Electronics

Verified : Yes

Year : 2014

Abstract : The wide spread use of multiprocessor system demands for energy saving. Energy issues being the most critical one need prime attention and prevention. This paper presents methods for power consumption reduction in multiprocessor systems by optimally allocating the jobs and scheduling them. The job allocation in multiprocessor systems is very crucial and a novel allocation algorithm for reducing the number of processors is proposed in this work. Scheduling decisions are vital for the system to meet both temporal and functional requirements and is perfect when methods for energy consumption reduction are incorporated into it. The current work aims to reduce power consumption of an embedded processor by Dynamic Voltage Frequency Scaling (DVFS) technique. The simulation results show a considerable amount of reduction in processor utilization and power consumption. © 2014 IEEE.

Cite this Research Publication : Dr. Anju Pillai S. and Dr. Isha T. B., “Optimal task allocation and scheduling for power saving in multiprocessor systems”, 2014 Power and Energy Systems Conference: Towards Sustainable Energy, PESTSE 2014. IEEE Computer Society, Bangalore, 2014.

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