一种引入单纯形法的能量均衡路由算法
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摘要
针对无线传感器网络中节点能量有限的问题,以及节点具有有限的计算和存储能力,提出一种引入单纯形法的能量均衡路由算法,延长网络有限的生存周期。综合遗传算法和单纯形算法的优势来寻找最优路径,改进了簇头选取方式,然后用特定簇头实现与基站的通信。该算法通过单纯形法的反射、扩张操作,不会陷入局部最优值,避免了遗传算法早熟的问题。同时结合遗传算法的全局寻优和单纯形法的局部寻优的特点,加快算法收敛的速度,路径优化的过程也在基站完成。仿真结果表明,在第一个节点出现死亡时,该算法的通信轮数达到遗传算法的130%,收敛速度提高了100%～150%,同时有效均衡了网络中的节点能量消耗。该算法在加快算法收敛性、降低网络能耗、提高网络生存周期方面具有很好的效果。
Aiming at the problem of limited energy of nodes in wireless sensor networks,and the limited computing and storage capacity of nodes,we propose an energy balance routing algorithm based on simplex method to extend the limited lifetime of networks. The method uses the advantages of genetic algorithm and simplex algorithm to find the optimal path and improves the way to select the cluster head which is applied to communicate with the sink node. Through reflection and expansion operations of the simplex method,this algorithm will not fall into the local optimal value,and avoid the premature of genetic algorithm. At the same time,the global optimization of genetic algorithm and the local optimization of simplex method are combined to speed up the convergence. The path optimization is completed in the base station. The simulation shows that at the death of the first node,the number of communication rounds of the algorithm reaches 130% compared with genetic algorithm. The convergence speed is improved by 100%～150%. And the energy consumption of nodes in the network is effectively balanced. Therefore,this algorithm has a better effect in accelerating the convergence of the algorithm,reducing the network energy consumption and improving the network life cycle.
Aiming at the problem of limited energy of nodes in wireless sensor networks,and the limited computing and storage capacity of nodes,we propose an energy balance routing algorithm based on simplex method to extend the limited lifetime of networks. The method uses the advantages of genetic algorithm and simplex algorithm to find the optimal path and improves the way to select the cluster head which is applied to communicate with the sink node. Through reflection and expansion operations of the simplex method,this algorithm will not fall into the local optimal value,and avoid the premature of genetic algorithm. At the same time,the global optimization of genetic algorithm and the local optimization of simplex method are combined to speed up the convergence. The path optimization is completed in the base station. The simulation shows that at the death of the first node,the number of communication rounds of the algorithm reaches 130% compared with genetic algorithm. The convergence speed is improved by 100%～150%. And the energy consumption of nodes in the network is effectively balanced. Therefore,this algorithm has a better effect in accelerating the convergence of the algorithm,reducing the network energy consumption and improving the network life cycle.
引文
[1] 任秀丽,王冲.基于节点邻域空间划分的无线传感网负载均衡路由协议[J].小型微型计算机系统,2016,37(6):1222-1227.
[2] 李浩宇,王洪超,杨冬, 等.基于Web的工业无线传感器网络图路由时隙调度[J].计算机技术与发展,2017,27(12):133-138.
[3] 李文艳,邵世祥.WSN中流量自适应的超低功耗MAC协议[J].计算机技术与发展,2017,27(3):113-116.
[4] KODALI R K,KIRAN A V S,BHANDARI S,et al.Energy efficient m-level LEACH protocol[C]//International conference on advances in computing,communications and informatics.Kochi,India:IEEE,2015:973-979.
[5] NEHRA V.PEGASIS-E:power efficient gathering in sensor information system extended[J].Global Journal of Computer Science & Technology,2013,13:15-18.
[6] 雷霖,李伟峰,王厚军.基于遗传算法的无线传感器网络路径优化[J].电子科技大学学报,2009,38(2):227-230.
[7] 张超群,郑建国,钱洁.遗传算法编码方案比较[J].计算机应用研究,2011,28(3):819-822.
[8] 曲良东,何登旭,黄勇.自适应改进和声-单纯形进化算法研究[J].计算机应用研究,2013,30(3):676-678.
[9] 葛斌,吴波,代陈.混沌蚁群算法在划分区域中能量均衡路由方法研究[J].电子测量与仪器学报,2017,31(5):786-793.
[10] 李玉霞,徐永鑫,何磊,等.基于GA和LEACH的WSN引入交通层路径优化算法[J].电子科技大学学报,2017,46(3):549-554.
[11] 刘帅,李正炜,吴元昊,等.基于能耗梯度的无线传感器网络路由算法[J].传感技术学报,2016,29(8):1247-1252.
[12] KUMAR V,KUMAR S.Energy balanced position-based routing for lifetime maximization of wireless sensor networks[J].Ad Hoc Networks,2016,52:117-129.
[13] 蒋畅江,石为人,唐贤伦,等.能量均衡的无线传感器网络非均匀分簇路由协议[J].软件学报,2012,23(5):1222-1232.
[14] 朱永红,丁恩杰,胡延军.PSO优化的能耗均衡WSNs路由算法[J].仪器仪表学报,2015,36(1):78-86.
[15] 高卉,冯友宏,王晓雨.认知无线传感网络中吞吐量能耗均衡研究[J].计算机技术与发展,2017,27(10):130-135.
[16] 董齐芬,张其前.基于Lyapunov优化的时变无线传感网路由研究[J].传感技术学报,2017,30(5):758-765.
[2] 李浩宇,王洪超,杨冬, 等.基于Web的工业无线传感器网络图路由时隙调度[J].计算机技术与发展,2017,27(12):133-138.
[3] 李文艳,邵世祥.WSN中流量自适应的超低功耗MAC协议[J].计算机技术与发展,2017,27(3):113-116.
[4] KODALI R K,KIRAN A V S,BHANDARI S,et al.Energy efficient m-level LEACH protocol[C]//International conference on advances in computing,communications and informatics.Kochi,India:IEEE,2015:973-979.
[5] NEHRA V.PEGASIS-E:power efficient gathering in sensor information system extended[J].Global Journal of Computer Science & Technology,2013,13:15-18.
[6] 雷霖,李伟峰,王厚军.基于遗传算法的无线传感器网络路径优化[J].电子科技大学学报,2009,38(2):227-230.
[7] 张超群,郑建国,钱洁.遗传算法编码方案比较[J].计算机应用研究,2011,28(3):819-822.
[8] 曲良东,何登旭,黄勇.自适应改进和声-单纯形进化算法研究[J].计算机应用研究,2013,30(3):676-678.
[9] 葛斌,吴波,代陈.混沌蚁群算法在划分区域中能量均衡路由方法研究[J].电子测量与仪器学报,2017,31(5):786-793.
[10] 李玉霞,徐永鑫,何磊,等.基于GA和LEACH的WSN引入交通层路径优化算法[J].电子科技大学学报,2017,46(3):549-554.
[11] 刘帅,李正炜,吴元昊,等.基于能耗梯度的无线传感器网络路由算法[J].传感技术学报,2016,29(8):1247-1252.
[12] KUMAR V,KUMAR S.Energy balanced position-based routing for lifetime maximization of wireless sensor networks[J].Ad Hoc Networks,2016,52:117-129.
[13] 蒋畅江,石为人,唐贤伦,等.能量均衡的无线传感器网络非均匀分簇路由协议[J].软件学报,2012,23(5):1222-1232.
[14] 朱永红,丁恩杰,胡延军.PSO优化的能耗均衡WSNs路由算法[J].仪器仪表学报,2015,36(1):78-86.
[15] 高卉,冯友宏,王晓雨.认知无线传感网络中吞吐量能耗均衡研究[J].计算机技术与发展,2017,27(10):130-135.
[16] 董齐芬,张其前.基于Lyapunov优化的时变无线传感网路由研究[J].传感技术学报,2017,30(5):758-765.