The Network Clustering Optimization Algorithm of Wireless Sensor Network with Energy Replenishment
The Network Clustering Optimization Algorithm of Wireless Sensor Network with Energy Replenishment
复制标题
能量补充的无线传感器网络网络分簇优化算法
DOI：
10.1166/sl.2016.3777
复制
发表时间：
2016-12
期刊：
影响因子：
--
通讯作者：
Zhang Qiuyu
中科院分区：
文献类型：
--
作者：
Peng Duo;Li Suoping;Zhang Qiuyu
在此，我们提出了一种改进的二进制粒子群优化算法（SOL-BPSO）。通过建立数学模型，将网络聚类问题转化为组合优化问题。此外，粒子的搜索空间被构造为作为簇头的二进制N维空间。粒子的搜索速度决定了节点成为簇头的概率。同时，设计了能量补充情况下的适应度函数。参数调整提高了节点的能量效率，保持了分簇的负载均衡，使得能量收集能力强的节点优先成为簇首。最后，通过多次迭代确定最优簇头，既保证了分簇的完成，又节省了簇头能量，平衡了节点负载。仿真结果表明，在考虑能量补充的同时，SOL-BPSO算法有效地平衡了节点的能量消耗，延长了网络的生命周期。因此，SOL-BPSO算法的网络生命周期比PHC算法长12.5%。
Herein, we propose an improved cluster-formation algorithm of binary particle swarm optimization (SOL-BPSO). Through the establishment of mathematic models, network clustering problems are transformed into combination optimization ones. Additionally, the search space of particles is constructed as the binary N-dimensional space that works as cluster heads. The search speed of particles decides the probability that nodes become cluster heads. Meanwhile, a fitness function is designed under the situation of energy replenishment. Parameter adjustment increases the energy efficiency of nodes and maintains the loading balance of clustering, which makes the nodes whose energy harvesting ability is high become cluster heads with a priority. Finally, optimal cluster heads will be decided through multiple iterations, which stands for the accomplishment of clustering and saves cluster-head energy and balances node loading. The simulation results show that SOL-BPSO algorithm effectively balances the energy consumption of nodes and extends the life cycle of network while energy replenishment is considered. Therefore, the network life cycle of SOL-BPSO algorithm is 12.5% longer than that of PHC algorithm.