基于双重选举机制的无线传感器网络分簇算法

Dual Selection Mechanism-Based Clustering Algorithm for Wireless Sensor Networks

为了高效地利用无线传感器网络的能量,提出一种基于双重选举机制的分簇算法(DSMCA).DSMCA有效地结合了投票选举机制和定时驱动机制.在投票过程中,节点给每个比自己剩余能量大的邻居节点投票,所投票数取决于邻居节点的多属性综合评价值,其中属性权重系数的确定采用熵权系数法.投票结束后,节点利用一个转换函数将所得票数转换为一个定时长度参与簇头竞争,得票高的节点生成的定时长度短,从而优先当选为簇头节点.仿真结果显示DSMCA均衡了传感器节点间的能量消耗,有效延长了网络的生存时间.

In order to efficiently utilize the energy in wireless sensor networks,a dual selection mechanism-based clustering algorithm（DSMCA） effectively combining the voting mechanism with the time-driven one is proposed.In the voting process,a node casts a vote for each neighbor node with higher residual energy.The poll depends on the comprehensive evaluation value of the multiple attributes of neighbor nodes,and the weight coefficient of the multiple attributes is determined by means of the entropy weighting coefficient method.After the voting,each node maps its poll into a certain length of waiting time to participate in cluster head competition by using a conversion function.Moreover,a node with a higher poll produces a shorter time,thus being chosen as a cluster head prior to other nodes.Simulation results show that DSMCA balances the energy consumption among sensor nodes and effectively prolongs the lifetime of the sensor network.