[1]汤文兵,陈亚楠,张牧.一种引入单纯形法的能量均衡路由算法[J].计算机技术与发展,2019,29(03):55-59.[doi:10.3969/ j. issn.1673-629X.2019.03.011]
　TANG Wen-bing,CHEN Ya-nan,ZHANG Mu.An Energy Balanced Routing Algorithm with Simplex Method[J].,2019,29(03):55-59.[doi:10.3969/ j. issn.1673-629X.2019.03.011]
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一种引入单纯形法的能量均衡路由算法()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
29
期数:
2019年03期
页码:
55-59
栏目:
智能、算法、系统工程
出版日期:
2019-03-10

文章信息/Info

Title:
An Energy Balanced Routing Algorithm with Simplex Method
文章编号:
1673-629X(2019)03-0055-05
作者:
汤文兵; 陈亚楠; 张牧
安徽理工大学 计算机工程学院,安徽 淮南 232000
Author(s):
TANG Wen-bing; CHEN Ya-nan; ZHANG Mu
School of Computer Engineering,Anhui University of Science &Technology,Huainan 232000,China
关键词:
遗传算法; 单纯形算法; 路径优化; 能耗均衡
Keywords:
genetic algorithm; simplex method; path optimization; energy balance
分类号:
TP301.6
DOI:
10.3969/ j. issn.1673-629X.2019.03.011
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。
Abstract:
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.

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更新日期/Last Update: 2019-03-10