信息物理融合系统中最小延迟数据聚集调度算法综述  

A survey on minimum latency data aggregation scheduling in Cyber Physical Systems

作　　者：陈权[1] 高宏[1] 金代亮 

机构地区：[1]哈尔滨工业大学计算机科学与技术学院,哈尔滨150001 [2]哈尔滨工业大学网络与信息中心,哈尔滨150001

出　　处：《智能计算机与应用》2018年第1期82-86,共5页Intelligent Computer and Applications

基　　金：国家自然科学基金(61190115;61033015);国家重点基础研究发展计划(973)(2012CB316200)

摘　　要：数据聚集调度问题研究sink节点如何能够无冲突地获取整个网络的汇总信息,是信息物理融合系统中一个非常重要的服务。在数据聚集调度问题中,聚集延迟是指整个网络中最后一个数据包到达sink节点的时间。最小延迟聚集调度问题则寻求一个快速无冲突的调度来最小化聚集延迟。在节点一直醒着的网络中,考虑到整个网络的大小和数据传输中的干扰问题,最小延迟聚集调度问题被证明为NP-难问题。另外,当网络中的节点采用低占空比模式来节省能耗时,由于节点只能在其处于活动状态时接受数据,最小延迟聚集调度问题变得更加复杂。近年来最小延迟聚集调度问题得到了大量的关注,本文将对该问题研究所取得的进展进行综述。Data aggregation seeks to compute a collision-free schedule for the sink to obtain the summary information of the wholenetwork, which is an essential operation in Cyber Physical Systems. As for data aggregation scheduling, data aggregation latency isdefined as the latest time slot during which the sink receives the last piece of aggregated data from one of its neighbors. Then theMinimum Latency Data Aggregation Scheduling （MLAS） problem is to compute a fast and collision-free schedule to minimize dataaggregation latency. In node always-awake network, the MLAS problem is proved to be NP-hard due to the size of network and thecollisions existed in transmissions. Additionally, when the node works with the duty-cycle model, the MLAS problem becomesmore complicated since each node can only receive when it is active. Currently, the MLAS problem has attracted a tremendousamount of attentions from researchers, and will be reviewed in this paper.

关 键 词：信息物理融合系统 传感器网络 数据聚集 调度 

分 类 号：TP393.01[自动化与计算机技术—计算机应用技术]