云计算与无线传感器网络集成的作业调度

Chunsheng Zhu, Xiuhua Li, Victor C. M. Leung, Xiping Hu, L. Yang
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引用次数: 23

摘要

云计算(CC)强大的数据存储和数据处理能力与无线传感器网络(WSN)无处不在的数据采集能力在CC-WSN集成中相互补充,越来越受到学术界和工业界的关注。然而,集成无线传感器网络的CC作业调度是一个关键而未被探索的课题。为了填补这一空白,本文首先分析了CC-WSN集成作业调度的特点,然后研究了两种传统和流行的作业调度算法(Min-Min和Max-Min)。在此基础上,提出了基于优先级的两阶段Min-Min (PTMM)算法和基于优先级的两阶段Max-Min (PTAM)算法。大量的实验结果表明,对于集成了WSN的CC, PTMM和PTAM比Min-Min和Max-Min的期望完成时间更短。
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Job Scheduling for Cloud Computing Integrated with Wireless Sensor Network
The powerful data storage and data processing abilities of cloud computing (CC) and the ubiquitous data gathering capability of wireless sensor network (WSN) complement each other in CC-WSN integration, which is attracting growing interest from both academia and industry. However, job scheduling for CC integrated with WSN is a critical and unexplored topic. To fill this gap, this paper first analyzes the characteristics of job scheduling with respect to CC-WSN integration and then studies two traditional and popular job scheduling algorithms (i.e., Min-Min and Max-Min). Further, two novel job scheduling algorithms, namely priority-based two phase Min-Min (PTMM) and priority-based two phase Max-Min (PTAM), are proposed for CC integrated with WSN. Extensive experimental results show that PTMM and PTAM achieve shorter expected completion time than Min-Min and Max-Min, for CC integrated with WSN.
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