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机构地区:[1]吉首大学软件服务外包学院,湖南张家界427000 [2]湖南大学嵌入式系统及网络实验室,长沙410082
出 处:《计算机应用》2013年第10期2787-2791,共5页journal of Computer Applications
摘 要:随着多处理器系统计算性能的提高,能耗管理已变得越来越重要,如何满足实时约束并有效降低能耗成为实时调度中的一个重要问题。基于多处理器计算系统,针对随机到达的任务,提出一种在线节能调度算法(OLEAS)。该算法在满足任务截止期限的前提下,尽量将任务调度到产生能耗最少的处理器,当某个任务在所有处理器上都不能满足截止期限要求时,则调整处理器之间的部分任务,使之尽量满足截止期限要求。同时,OLEAS尽量使单个处理器上的任务按平均电压/频率执行,以降低能耗,只有当新到任务不满足截止期限要求时,才逐个调高前面任务的电压/频率。模拟实验比较了OLEAS、最早完成时间优先(EFF)、最高电压节能(HVEA)、最低电压节能(LVEA)、贪心最小能耗(MEG)和最小能耗最小完成时间(ME-MC)的性能,结果表明OLEAS在满足任务截止期限和节省能耗方面具有明显的综合优势。With the enhancement of computing performance in muhiprocessor systems, the management of energy consumption becomes more important, and how to meet real-time constraints and effectively reduce energy consumption in the real-time scheduling is also a key issue. Based on multiprocessor computing systems, concerning randomly arrived task, On- Line Energy-Aware Scheduling Algorithm (OLEAS) was proposed. The algorithm meeting the task deadlines under the premise possibly puts the task scheduler on the least energy consumption producing processor. When a task on all the processors could not meet the deadline requirements, the part of the task between the processors shall be adjusted possibly to meet the deadline requirements. Meanwhile, OLEAS was in a bid to execute the task on a single processor according to the average voltage/ frequency, thus reducing the energy consumption. When the new task did not meet the deadline requirements, the former voltage/frequency of unexecuted tasks should be one by one adjusted higher. Compared with the performance of EFF ( Earliest Finish First), HVEA ( Highest Voltage Energy-Aware), LVEA ( Lowest Voltage Energy-Aware), MEG ( Minimum Energy Greedy) and ME-MC (Minimum Energy Minimum Completion time) in simulated experiments, the final result shows OLEAS owns obviously comprehensive advantage in the aspect of meeting task deadlines and energy consumption saving.
分 类 号:TP393[自动化与计算机技术—计算机应用技术]
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