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[ "王章权,男,浙江树人大学信息科技学院副教授,主要研究方向为电力电子技术、控制技术、无线控制。" ]
[ "陈友荣,男,博士,浙江树人大学信息科技学院讲师,主要研究方向为无线传感网、物联网。" ]
[ "任条娟,女,浙江树人大学信息科技学院副教授,主要研究方向为无线传感网、车联网。" ]
[ "许森,男,浙江树人大学信息科技学院助教,主要研究方向为智能控制、车联网。" ]
网络出版日期:2013-10,
纸质出版日期:2013-10-20
移动端阅览
王章权, 陈友荣, 任条娟, 等. 移动无线传感网的生存时间优化算法研究[J]. 电信科学, 2013,29(10):80-87.
Zhangquan Wang, Yourong Chen, Tiaojuan Ren, et al. Research on Lifetime Optimization Algorithm for Mobile Wireless Sensor Network[J]. Telecommunications science, 2013, 29(10): 80-87.
王章权, 陈友荣, 任条娟, 等. 移动无线传感网的生存时间优化算法研究[J]. 电信科学, 2013,29(10):80-87. DOI: 10.3969/j.issn.1000-0801.2013.10.014.
Zhangquan Wang, Yourong Chen, Tiaojuan Ren, et al. Research on Lifetime Optimization Algorithm for Mobile Wireless Sensor Network[J]. Telecommunications science, 2013, 29(10): 80-87. DOI: 10.3969/j.issn.1000-0801.2013.10.014.
当sink节点位置固定不变时,分布在sink 节点周围的传感节点很容易成为枢纽节点,因转发较多的数据而过早失效。为解决上述问题,提出移动无线传感网的生存时间优化算法(LOAMWSN)。LOAMWSN算法考虑sink节点的移动,采用减聚类算法确定sink节点移动的锚点,采用最近邻插值法寻找能遍历所有锚点的最短路径近似解,采用分布式非同步Bellman-Ford算法构建sink节点k跳通信范围内的最短路径树。最终,传感节点沿着最短路径树将数据发送给sink节点。仿真结果表明:在节点均匀分布和非均匀分布的无线传感网中,LOAMWSN算法都可以延长网络生存时间、平衡节点能耗,将平均节点能耗保持在较低水平。在一定的条件下,比Ratio_w、TPGF算法更优。
When the position of sink node is fixed
the sensor nodes which are distributed around the sink node easily become hub nodes
forward a lot of data and fail prematurely.In order to solve this problem
the lifetime optimization algorithm for mobile wireless sensor network(LOAMWSN)was proposed.LOAMWSN algorithm considers the mobility of sink node
uses subtractive cluster algorithm to determine mobile anchor points of sink node
uses the nearest neighbor interpolation method to find the approximate solution of shortest route which traverse all mobile anchor points
uses distributed asynchronous Bellman-Ford algorithm to construct the shortest path tree in the k-hop range of sink node.Finally
sensor nodes transmit data to sink node along the shortest path tree.Simulation results show that in wireless sensor network of node uniform distribution and non-uniform distribution
LOAMWSN algorithm can prolong the network lifetime
balance the node energy consumption
and remain the average node energy consumption at a low level.Under certain conditions
it outperforms Ratio_w and TPGF algorithms.
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