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WSN低功耗低时延路径式协同计算方法
引用本文:马步云,马新策,黄松,任智源. WSN低功耗低时延路径式协同计算方法[J]. 无线电通信技术, 2021, 0(2): 168-177
作者姓名:马步云  马新策  黄松  任智源
作者单位:西安电子科技大学综合业务网理论及关键技术国家重点实验室
基金项目:中国电子科技集团公司第五十四研究所高校合作课题(99901200100)。
摘    要:针对云计算应用于无线传感器网络(Wireless Sensor Network,WSN)时延敏感型业务时存在的高传输时延问题,提出了一种WSN低功耗低时延路径式协同计算方法.该方法基于一种云雾网络架构开展研究,该架构利用汇聚节点组成雾计算层;在数据传输过程中基于雾计算层的计算能力分步骤完成任务计算,降低任务处理时延;由...

关 键 词:WSN  云雾网络  任务映射  能耗约束

Low-power Low-latency Path-based Collaborative Computing Scheme for WSN
MA Buyun,MA Xince,HUANG Song,REN Zhiyuan. Low-power Low-latency Path-based Collaborative Computing Scheme for WSN[J]. Radio Communications Technology, 2021, 0(2): 168-177
Authors:MA Buyun  MA Xince  HUANG Song  REN Zhiyuan
Affiliation:(State Key Laboratory of Integrated Services Networks,XiDian University,Xi’an 710071,China)
Abstract:A low-power low-latency path-based collaborative computing scheme is proposed to solve the problem of high transmission delay when cloud computing is applied to delay sensitive service in wireless sensor networks.The scheme is based on a cloud and fog network architecture,and the fog layer is composed of the sink nodes.The computing capacity of fog nodes is used to gradually complete the task in the process of data transmission.The computing power of sink nodes is weak and the reduction of latency would lead to increase of power consumption,the working life of WSN is shorted.Thus,a task mapping strategy under energy consumption is proposed and a binary particle swarm optimization(BPSO)algorithm is used to solve delay optimization problem under energy consumption constraints.Simulation results show that the proposed path computing scheme can effectively reduce the latency compared with other algorithms under the same energy consumption constraints.
Keywords:WSN  cloud and fog network  task mapping  energy constrain
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