一种新型的分布式弱栅栏构建与移动算法

Distributed Mobile Algorithm for the Weak Barrier Coverage

在传感器网络栅栏覆盖的研究中,针对如何减少移动节点带来的损耗,提出了一种全新的分布式弱栅栏覆盖算法KSDE(Kuhn Select-box Distribute Exponential-smoothing)。算法将弱栅栏覆盖中的栅栏模型转化成若干个槽位相连接的方式,引入图论学中的库恩匹配KM(Kuhn Munkras)方法,完成槽位和节点集合之间的最小路径匹配,从而选出参与匹配的节点,进行弱栅栏的构建。为了进一步优化栅栏的闭合性,通过仿真调整分区规模,找到最佳的分区方案。经大量实验验证,KSDE可以在保证一定闭合性的要求下,大幅减少节点的平均移动距离。

For the barrier coverage in sensor network,a new distributed weak barrier coverage algorithm（Kuhn Select-box Distribute Exponential-smoothing,KSDE）is proposed to reduce the moving cost caused by mobile nodes. The presented algorithm divides the barrier model into a number of connected slots. Inspiring from the Kuhn Matching（Kuhn. Munkras,KM）method in graph theory,the minimum path is completed guaranteeing the best match between the slots and the nodes set,through selecting the matched nodes to construct the weak barrier. In order to further optimize the closure of the barrier,the best partition scheme can be found by adjusting the size of the partition barrier in simulation. Through a large number of experimental analysis,KSDE can significantly reduce the average moving distance of nodes under the premise of ensuring a certain closure.