传感网中带有可控阈值的优化协同覆盖算法

传统型的无线传感器网络(WSNs)覆盖受限于节点能量和数据冗余,迫使WSNs异常中断。为此,提出一种带有可控阈值的优化协同覆盖算法(OCC-CT)。该算法首先确定关注目标节点(FTNs)的位置信息,利用遗传算法(GA)给出了节点路径规划;其次,通过可控阈值参数和变异参数等特性对事件域节点成簇进行优化,使之节点成簇更为均匀,以减少节点能量的消耗,提升对全局目标节点的搜索能力;再次,利用适应函数对所覆盖目标位置及节点监测范围所形成的覆盖连续性进行优化,达到了提高网络覆盖率和延长网络生存周期的目的。最后,仿真实验结果表明,OCC-CT算法与其他三种算法相比在网络覆盖率、网络生存周期等方面平均提升了0.11、0.16,在网络能量开销方面提升了0.14,从而进一步验证了OCC-CT算法具有较强的稳定性和有效性。

Optimization Cooperative Coverage Algorithm with Controllable Threshold-Parameters in WSNs

The coverage of traditional wireless sensor networks(WSNs)is limited by node energy and data redundancy,forcing WSNs to be interrupted abnormally.To this end,a novel optimization cooperative coverage algorithm with controllable threshold-parameters(OCC-CT)is proposed.The algorithm first determines the location information of the focus target nodes(FTNs),and uses the genetic algorithm(GA)to give the node path planning.Second,the controllable threshold parameters and mutation parameters are used to control event domain nodes.Clustering is optimized to make the clustering of the nodes more uniform,so as to reduce the energy consumption of the nodes and improve the search ability of the global target nodes.Third,the adaptation function is used to cover the continuity of the covered target locations and the monitoring range of the nodes.Optimization is performed to achieve the goals of increasing network coverage and extending the network lifetime.Finally,simulation results show that the OCCCT algorithm,compared with other three algorithms in this paper,improves 0.11 and 0.16 on average in terms of network coverage,network lifetime,and 0.14 in terms of network energy overhead,thereby further verifying OCCCT algorithm has strong stability and effectiveness.