一种基于学习自动机的WSN区域覆盖算法

发布时间：2018-11-04 20:26

【摘要】：基于连通支配集(Connected dominating set,CDS)的区域覆盖算法大都采用休眠节点数量的最大化机制来实现节能,这将给无线传感器网络中的活动节点带来沉重的负担。活动节点电能的迅速耗尽将导致CDS失效,产生覆盖盲区。不断激活其他休眠节点,会出现频繁的网络拓扑变化,导致网络收敛性出现问题。提出了一种基于学习自动机的WSN区域覆盖算法。采用受度限制的连通支配集d-CDS来构造WSN骨干网络,利用学习自动机选择当前节点的最优邻居节点,以此实现对所构造CDS的优化,实现活动节点的负载均衡,改善区域覆盖性能。通过仿真实验对比Gossip、ST-MSN和TMPO等算法,表明本文提出的算法在网络覆盖比率、活动节点的剩余电量等方面均存在优势。
[Abstract]:Most of the region coverage algorithms based on the connected dominating set (Connected dominating set,CDS) use the maximum number of dormant nodes to achieve energy saving which will bring a heavy burden to the active nodes in wireless sensor networks. The rapid depletion of the active node energy will lead to the failure of the CDS, resulting in coverage of blind areas. When other dormant nodes are continuously activated, frequent network topology changes will occur, resulting in problems of network convergence. A WSN region coverage algorithm based on learning automata is proposed. The connected dominating set d-CDS is used to construct the WSN backbone network, and the learning automata is used to select the optimal neighbor node of the current node. In order to realize the optimization of the constructed CDS, the load balance of the active node is realized. Improve area coverage. The comparison between Gossip,ST-MSN and TMPO shows that the proposed algorithm has advantages in network coverage ratio and residual power of active nodes.
【作者单位】：河南科技学院信息工程学院;武汉理工大学信息工程学院;鹤壁汽车工程职业学院;
【基金】：国家自然科学基金(31371525)资助项目河南省教育厅科学技术研究重点(14A520067)资助项目河南省信息技术教育研究重点(ITE12037)资助项目河南省教育厅人文社会科学研究(2014-gh-245)资助项目 2014年河南科技学院教育教学改革研究重点(2014PUZD08)资助项目
【分类号】：TP212.9;TN929.5

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