基于最优簇数和改进引力搜索的WSN路由算法

doi:10.11772/j.issn.1001-9081.2017.12.3374

计算机应用 ›› 2017, Vol. 37 ›› Issue (12): 3374-3380.DOI: 10.11772/j.issn.1001-9081.2017.12.3374

基于最优簇数和改进引力搜索的WSN路由算法

李新春¹, 高佰胜²

1. 辽宁工程技术大学电子与信息工程学院, 辽宁葫芦岛 125105;
2. 辽宁工程技术大学研究生院, 辽宁葫芦岛 125105

收稿日期:2017-06-15 修回日期:2017-08-27 出版日期:2017-12-10 发布日期:2017-12-18
通讯作者: 高佰胜
作者简介:李新春(1963-),男,辽宁朝阳人,高级工程师,硕士,主要研究方向:无线传感器网络;高佰胜(1992-),男,辽宁铁岭人,硕士研究生,主要研究方向:无线传感器网络。

WSN routing algorithm based on optimal number of clusters and improved gravitational search

LI Xinchun¹, GAO Baisheng²

1. School of Electronics and Information Engineering, Liaoning Technical University, Huludao Liaoning 125105, China;
2. School of Graduate, Liaoning Technical University, Huludao Liaoning 125105, China

Received:2017-06-15 Revised:2017-08-27 Online:2017-12-10 Published:2017-12-18

摘要/Abstract

摘要： 为了提高无线传感器网络（WSN）的能量利用效率，提出一种基于最优簇数和改进引力搜索的WSN路由算法（ONCIGS）。首先，根据非均匀分簇的思想计算最优簇数，并采用改进的凝聚嵌套（AGNES）算法实现网络的合理分簇；其次，将反向学习机制和精英策略思想引入到引力搜索算法中，并基于种群密度对作用力进行自适应调整，以提高搜索精度，加快收敛；然后，将簇头剩余能量的标准差作为目标函数，搜索能量均衡的簇间数据转发路径。实验结果表明，相比低功耗自适应集簇分层型（LEACH）路由算法和分布式能量均衡非均匀成簇（DEBUC）路由算法，ONCIGS在100 m×100 m网络规模下将网络生命周期分别延长41.94%和5.77%，在200 m×200 m网络规模下分别延长76.60%和7.82%。ONCIGS能够有效地延长网络寿命，提高能量效率。

关键词: 无线传感器网络, 非均匀分簇, 引力搜索, 网络能耗, 生命周期

Abstract: In order to improve the energy efficiency of Wireless Sensor Network (WSN), a WSN routing algorithm based on Optimal Number of Clusters and Improved Gravitational Search (ONCIGS) was proposed. Firstly, the optimal number of clusters was calculated according to the idea of uneven clustering, and the improved AGglomerative NESting (AGNES) algorithm was adopted to realize the reasonable clustering of network. Secondly, reverse learning mechanism and elite strategy were introduced into the gravitational search algorithm, and the force was adjusted adaptively based on population density to improve the search precision and speed up the convergence. Then, the standard deviation of residual energy of cluster heads was taken as the objective function to search the energy-balanced inter-cluster data forwarding path. The experimental results show that, compared with the Low Energy Adaptive Clustering Hierarchy (LEACH) routing algorithm and Distributed Energy Balanced Unequal Clustering (DEBUC) routing algorithm, the network life cycle of the proposed ONCIGS is prolonged by 41.94% and 5.77% respectively under the network scale of 100 m×100 m, and it is prolonged by 76.60% and 7.82% respectively under the network scale of 200 m×200 m. The proposed ONCIGS can effectively prolong network lifetime and improve energy efficiency.

Key words: Wireless Sensor Network (WSN), uneven clustering, gravitational search, network energy consumption, life cycle

中图分类号:

TP393.04

李新春, 高佰胜. 基于最优簇数和改进引力搜索的WSN路由算法[J]. 计算机应用, 2017, 37(12): 3374-3380.

LI Xinchun, GAO Baisheng. WSN routing algorithm based on optimal number of clusters and improved gravitational search[J]. Journal of Computer Applications, 2017, 37(12): 3374-3380.

参考文献

[1] 徐晶晶,张欣慧,许必宵,等.无线传感器网络分簇算法综述[J].计算机科学,2017,44(2):31-37.(XU J J, ZHANG X H, XU B X, et al. Survey of clustering algorithms for wireless sensor networks[J]. Computer Science, 2017, 44(2):31-37.)
[2] HEINZELMAN W B, CHANDRAKASAN A, BALAKRISHAM H. Energy-efficient communication protocol for wireless microsensor networks[C]//Proceedings of the 33rd Annual Hawaii International Conference on System Sciences. Piscataway, NJ:IEEE, 2000:3005-3014.
[3] 李成法,陈贵海,叶懋,等.一种基于非均匀分簇的无线传感器网络路由协议[J].计算机学报,2007,30(1):27-36.(LI C F, CHEN G H, YE M, et al. An uneven cluster-based routing protocol for wireless sensor networks[J]. Chinese Journal of Computers, 2007, 30(1):27-36.)
[4] 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.(JIANG C J, SHI W R, TANG X L, et al. Energy-balanced unequal clustering routing protocol for wireless sensor networks[J]. Journal of Software, 2012, 23(5):1222-1232.)
[5] XU Z Y, YIN Y, WANG J, et al. A game-theoretic approach for efficient clustering in wireless sensor networks[J]. International Journal of Hybrid Information Technology, 2014, 7(1):67-80.
[6] 翟春杰,徐建闽,刘永桂.基于分区的能耗均衡路由协议[J].传感技术学报,2016,29(1):80-87.(ZHAI C J, XU J M, LIU Y G. Energy-consumption balancing routing protocol based on regions[J]. Chinese Journal of Sensors and Actuators, 2016, 29(1):80-87.)
[7] 李双双,杨文忠,吴向前.基于非均等分区的无线传感器网络路由协议[J].计算机应用,2016,36(11):3010-3015.(LI S S, YANG W Z, WU X Q. Routing protocol based on unequal partition area for wireless sensor network[J]. Journal of Computer Applications, 2016, 36(11):3010-3015.)
[8] 吴标,崔琛,余剑,等.基于非均匀成簇的无线传感器网络多跳路由算法[J].计算机科学,2017,44(2):157-162.(WU B, CUI C, YU J. et al. Multi-hop routing algorithm for wireless sensor networks based on uneven clustering[J]. Computer Science, 2017, 44(2):157-162.)
[9] 冯建平,李华.随机虚拟骨干树结合改进BDCP的无线传感器网络多级路由算法[J].计算机应用研究,2016,33(8):2454-2457,2461.(FENG J P, LI H. Multi-level routing algorithm of WSN based on fusion of random virtual backbone trees and backoff distributed clustering[J]. Application Research of Computers, 2016, 33(8):2454-2457, 2461.)
[10] 颜然,杨云,史庭俊,等.一种基于节点位置和密度的非均匀分簇路由算法[J].计算机科学,2015,42(8):65-69.(YAN R, YANG Y, SHI T J, et al. Uneven cluster routing algorithm based on node location and node density[J]. Computer Science, 2015, 42(8):65-69.)
[11] ZHANG D G, WANG X, SONG X D, et al. A new clustering routing method based on PECE for WSN[J]. EURASIP Journal on Wireless Communications and Networking, 2015, 2015(1):162.
[12] HEINZELMAN W B, CHANDRAKASAN A P, BALAKRISHNAN H. An application-specific protocol architecture for wireless microsensor networks[J]. IEEE Transactions on Wireless Communications, 2002, 1(4):660-670.
[13] 周志华.机器学习[M].北京:清华大学出版社,2016:214-215.(ZHOU Z H. Machine Learning[M]. Beijing:Tsinghua University Press, 2016:214-215.)
[14] 尚凤军,任东海.无线传感器网络中分布式多跳路由算法研究[J].传感技术学报,2012,25(4):529-535.(SHANG F J, REN D H. A distributed multi-hop routing algorithm in wireless sensor networks[J]. Chinese Journal of Sensors and Actuators, 2012, 25(4):529-535.)
[15] RASHEDI E, NEZAMABADI-POUR H, SARYAZDI S. GSA:a gravitational search algorithm[J]. Information Sciences, 2009, 179(13):2232-2248.
[16] TIZHOOSH H R. Opposition-based learning:a new scheme for machine intelligence[C]//Proceedings of the 2005 International Coference on Computational Intelligence for Modeling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce. Washington, DC:IEEE Computer Society, 2005:695-701.

基于最优簇数和改进引力搜索的WSN路由算法

WSN routing algorithm based on optimal number of clusters and improved gravitational search

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

[1]	孙环, 陈宏滨. 基于萤火虫算法的无线传感器网络节点重部署策略[J]. 计算机应用, 2021, 41(2): 492-497.
[2]	胡润彦, 李翠然. 基于模糊控制的自供能无线传感器网络分簇算法[J]. 计算机应用, 2020, 40(9): 2691-2697.
[3]	韩雨涝, 房鼎益. 基于链路交点相对位置信息的轻量级覆盖空洞检测算法[J]. 计算机应用, 2020, 40(9): 2698-2705.
[4]	韩雨涝, 房鼎益. 联合无线充电与数据收集的移动充电装置多目标路径规划算法[J]. 计算机应用, 2020, 40(6): 1745-1750.
[5]	卢光跃, 周亮, 吕少卿, 施聪, 苏可可. 基于图信号处理的无线传感器网络异常节点检测算法[J]. 计算机应用, 2020, 40(3): 783-787.
[6]	任秀丽, 陈洋. 无线传感网中数据传输延时优化的路由协议[J]. 计算机应用, 2020, 40(1): 196-201.
[7]	吴三柱, 李鹏, 吴三斌. 移动无线传感器网络中抑制病毒传播模型[J]. 计算机应用, 2020, 40(1): 129-135.
[8]	董发志, 丁洪伟, 杨志军, 熊成彪, 张颖婕. 基于遗传算法和模糊C均值聚类的WSN分簇路由算法[J]. 计算机应用, 2019, 39(8): 2359-2365.
[9]	何庆, 徐钦帅, 魏康园. 基于改进正弦余弦算法的无线传感器节点部署优化[J]. 计算机应用, 2019, 39(7): 2035-2043.
[10]	柳玉东, 王绪安, 涂广升, 王涵. 全生命周期的云外包数据安全审计协议[J]. 计算机应用, 2019, 39(7): 1954-1958.
[11]	钱开国, 卜春芬, 王玉见, 申时凯. 基于可靠信标和节点度估计距离的无线传感器网络定位算法[J]. 计算机应用, 2019, 39(3): 817-823.
[12]	任晓奎, 李锋, 程琳. 基于动态损耗因子和权重的改进质心定位算法[J]. 计算机应用, 2019, 39(3): 824-828.
[13]	汪汉新, 洪思琴. 基于环分块的能耗均衡分簇路由算法[J]. 计算机应用, 2019, 39(1): 251-255.
[14]	党小超, 邵晨光, 郝占军. 半径可调的无线传感器网络三维覆盖算法[J]. 计算机应用, 2018, 38(9): 2581-2586.
[15]	王国玲, 杨文忠, 张振宇, 夏扬波, 殷亚博, 杨慧婷. 移动传感网中基于虚拟货币的路由策略[J]. 计算机应用, 2018, 38(9): 2587-2592.