SENAS: Security driven ENergy Aware Scheduler for Real Time Approximate Computing Tasks on Multi-Processor Systems

被引:2
|
作者
Guha, Krishnendu [1 ]
Saha, Sangeet [2 ]
McDonald-Maier, Klaus [2 ]
机构
[1] Univ Florida, Dept Elect & Comp Engn, Gainesville, FL 32611 USA
[2] Univ Essex, Sch Comp Sci & Elect Engn, Colchester, England
基金
英国工程与自然科学研究理事会;
关键词
Approximate Computation; Energy Aware Scheduling; Real-time Security; Multi-Processor; Power Draining;
D O I
10.1109/IOLTS56730.2022.9897811
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Present day real time approximate computing applications like image and video processing involves execution of a set of tasks before a certain amount of time or deadline. In addition to this, present day systems are associated with strict energy budget that cannot be changed post deployment. The tasks comprises of a mandatory and optional part. Completion of all mandatory portions of all tasks before deadline is much more important than result accuracy in such real time approximate computing applications. Based on the energy budget, the optional portions can be executed that determines the quality of service (QoS) of the system. In ideal scenario, sufficient energy budget is present that ensures completion of both mandatory and optional portions in a system with a pre-determined number of processors. However, if fault or malware attack occurs on one or more processors, then the system will cease to work and results may be fatal. In this work, we consider such a scenario where the processors may be faulty and stop functioning in post deployment phases or some malware may cause unexpected delays in processing or may cause unexpected power draining at runtime that will prevent the system from meeting its deadline. We propose a Security driven ENergy Aware Scheduler (SENAS) that works as a self aware agent. Initially, based on the available energy budget, SENAS determines which task is to be executed in which processor of a system. At runtime, SENAS constantly monitors the working of the processors and on detecting any anomaly in any of the processors, it reschedules its tasks at runtime by reducing execution of the optional portions of the tasks and ensuring completion before deadline with high QoS.
引用
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页数:5
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