在基于移动sink传感器网络中,传感器节点能量受限,数据收集的能耗问题一直是研究的热点.通过建立最大化最小能耗概率模型,提出一种最大化最小能耗概率(Maximizing Minimum Probability of Energy Consumption,MMPEC)数据收集方法.MMPEC...在基于移动sink传感器网络中,传感器节点能量受限,数据收集的能耗问题一直是研究的热点.通过建立最大化最小能耗概率模型,提出一种最大化最小能耗概率(Maximizing Minimum Probability of Energy Consumption,MMPEC)数据收集方法.MMPEC对网络中子节点与汇聚节点之间的路径长度进行分布式优化,使得整个网络的能耗达到最低的概率最大化.仿真结果表明,MMPEC在能耗方面优于同类基于移动sink的WSN分层数据收集方法.展开更多
Wireless Sensor Networks(WSNs)are usually formed with many tiny sensors which are randomly deployed within sensing field for target monitoring.These sensors can transmit their monitored data to the sink in a multi-hop...Wireless Sensor Networks(WSNs)are usually formed with many tiny sensors which are randomly deployed within sensing field for target monitoring.These sensors can transmit their monitored data to the sink in a multi-hop communication manner.However,the‘hot spots’problem will be caused since nodes near sink will consume more energy during forwarding.Recently,mobile sink based technology provides an alternative solution for the long-distance communication and sensor nodes only need to use single hop communication to the mobile sink during data transmission.Even though it is difficult to consider many network metrics such as sensor position,residual energy and coverage rate etc.,it is still very important to schedule a reasonable moving trajectory for the mobile sink.In this paper,a novel trajectory scheduling method based on coverage rate for multiple mobile sinks(TSCR-M)is presented especially for large-scale WSNs.An improved particle swarm optimization(PSO)combined with mutation operator is introduced to search the parking positions with optimal coverage rate.Then the genetic algorithm(GA)is adopted to schedule the moving trajectory for multiple mobile sinks.Extensive simulations are performed to validate the performance of our proposed method.展开更多
针对移动无线传感器网络设计一种不依赖于节点地理位置的基于移动汇聚节点(Sink)的数据收集算法(Mobile Sink-based Data Gathering,MSDG)。该算法解决了无线传感器网络中多跳路由通信时出现能量空洞的"热点"问题。Sink沿途...针对移动无线传感器网络设计一种不依赖于节点地理位置的基于移动汇聚节点(Sink)的数据收集算法(Mobile Sink-based Data Gathering,MSDG)。该算法解决了无线传感器网络中多跳路由通信时出现能量空洞的"热点"问题。Sink沿途以最近的固定节点作为根节点动态构建路由树。簇内移动节点感知的数据经簇头进行数据融合计算,然后将融合后的数据沿路由树反向逐跳转发给Sink。仿真结果表明,MSDG在节点的平均能耗和网络生存时间等方面的性能远超过LEACH、ACE-L等数据收集协议。展开更多
文摘在基于移动sink传感器网络中,传感器节点能量受限,数据收集的能耗问题一直是研究的热点.通过建立最大化最小能耗概率模型,提出一种最大化最小能耗概率(Maximizing Minimum Probability of Energy Consumption,MMPEC)数据收集方法.MMPEC对网络中子节点与汇聚节点之间的路径长度进行分布式优化,使得整个网络的能耗达到最低的概率最大化.仿真结果表明,MMPEC在能耗方面优于同类基于移动sink的WSN分层数据收集方法.
基金This work was supported by the National Natural Science Foundation of China(61772454,61811530332,61811540410)It was also supported by the open research fund of Key Lab of Broadband Wireless Communication and Sensor Network Technology(Nanjing University of Posts and Telecommunications)Ministry of Education(No.JZNY201905).
文摘Wireless Sensor Networks(WSNs)are usually formed with many tiny sensors which are randomly deployed within sensing field for target monitoring.These sensors can transmit their monitored data to the sink in a multi-hop communication manner.However,the‘hot spots’problem will be caused since nodes near sink will consume more energy during forwarding.Recently,mobile sink based technology provides an alternative solution for the long-distance communication and sensor nodes only need to use single hop communication to the mobile sink during data transmission.Even though it is difficult to consider many network metrics such as sensor position,residual energy and coverage rate etc.,it is still very important to schedule a reasonable moving trajectory for the mobile sink.In this paper,a novel trajectory scheduling method based on coverage rate for multiple mobile sinks(TSCR-M)is presented especially for large-scale WSNs.An improved particle swarm optimization(PSO)combined with mutation operator is introduced to search the parking positions with optimal coverage rate.Then the genetic algorithm(GA)is adopted to schedule the moving trajectory for multiple mobile sinks.Extensive simulations are performed to validate the performance of our proposed method.
文摘针对移动无线传感器网络设计一种不依赖于节点地理位置的基于移动汇聚节点(Sink)的数据收集算法(Mobile Sink-based Data Gathering,MSDG)。该算法解决了无线传感器网络中多跳路由通信时出现能量空洞的"热点"问题。Sink沿途以最近的固定节点作为根节点动态构建路由树。簇内移动节点感知的数据经簇头进行数据融合计算,然后将融合后的数据沿路由树反向逐跳转发给Sink。仿真结果表明,MSDG在节点的平均能耗和网络生存时间等方面的性能远超过LEACH、ACE-L等数据收集协议。
