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View all- Godabole PBhole G(2021)Timing Analysis in Multi-Core Real Time Systems2021 IEEE International Symposium on Smart Electronic Systems (iSES)10.1109/iSES52644.2021.00021(38-43)Online publication date: Dec-2021
Profitable Scheduling on Multiple Speed-Scalable Processors
Article No.: 19, Pages 1 - 19
Abstract
We present a new online algorithm for profit-oriented scheduling on multiple speed-scalable processors and provide a tight analysis of the algorithm’s competitiveness. Our results generalize and improve upon work by Chan et al. [2010], which considers a single speed-scalable processor. Using significantly different techniques, we can not only extend their model to multiprocessors but also prove an enhanced and tight competitive ratio for our algorithm.
In our scheduling problem, jobs arrive over time and are preemptable. They have different workloads, values, and deadlines. The scheduler may decide not to finish a job but instead to suffer a loss equaling the job’s value. However, to process a job’s workload until its deadline the scheduler must invest a certain amount of energy. The cost of a schedule is the sum of lost values and invested energy. In order to finish a job, the scheduler has to determine which processors to use and set their speeds accordingly. A processor’s energy consumption is power Pα(s) integrated over time, where Pα(s)=sα is the power consumption when running at speed s. Since we consider the online variant of the problem, the scheduler has no knowledge about future jobs. This problem was introduced by Chan et al. [2010] for the case of a single processor. They presented an online algorithm that is αα + 2eα-competitive. We provide an online algorithm for the case of multiple processors with an improved competitive ratio of αα.
References
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- Profitable Scheduling on Multiple Speed-Scalable Processors
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October 2015
196 pages
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Publication History
Published: 08 September 2015
Accepted: 01 June 2014
Received: 01 October 2013
Published in TOPC Volume 2, Issue 3
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- German Research Foundation (DFG) within the Collaborative Research Center On-The-Fly Computing (SFB 901)
- Graduate School on Applied Network Science (GSANS)
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View all- Godabole PBhole G(2021)Timing Analysis in Multi-Core Real Time Systems2021 IEEE International Symposium on Smart Electronic Systems (iSES)10.1109/iSES52644.2021.00021(38-43)Online publication date: Dec-2021
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