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使用增强遗传算法的功耗限制任务调度

Power Consumption Constrained Task Scheduling Using Enhanced Genetic Algorithms
作者:Gang ShenYanqing Zhang 作者单位:Computer Science Department, Georgia State University, P.O. Box 3994, Atlanta, GA 30302-3994, USA;Computer Science Department, Georgia State University, P.O. Box 3994, Atlanta, GA 30302-3994, USA 加工时间:2014-07-18 信息来源:科技报告(Other) 索取原文[21 页]
关键词:计算机系统;算法;线性编程;传感器网络
摘 要:Two typical challenges in the energy aware tasking scheduling are (1) minimizing energy consumption with execution time constraint and (2) minimizing task execution time with energy consumption constraint. This chapter focuses on the later challenge. It is very important to efficiently schedule tasks in mobile devices and sensor networks that have limited power. The goal is to cooperatively complete a set of tasks among diverse computing resources with given energy. Traditional scheduling algorithms, such as list scheduling, are not very efficient for this scheduling problem. Linear programming optimization method does not fit well since it is a non-linear problem. An enhanced genetic algorithm can solve this problem effectively.
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