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Wireless Personal Communications
Published in: Wireless Personal Communications 3/2017

23-09-2016

Routing Technology in Wireless Sensor Network Based on Ant Colony Optimization Algorithm

Authors: Zheng Enxing, Liu Ranran

Published in: Wireless Personal Communications | Issue 3/2017

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Abstract

With rapid development of wireless communication, sensor, micro power system and electronic technology, the research on wireless sensor network has attracted more and more attention. The work proposed routing algorithm in wireless sensor network based on ant colony optimization by analyzing routing protocol and utilizing advanced idea. Ant colony optimization algorithm has advantages in implementing local work, supporting multiple paths and integrating link quality into pheromone formation. In routing selection, the work calculated probability that node is selected as the next hop according to pheromone concentration on the path. With characteristics including self-organization, dynamic and multipath, ant colony optimization algorithm is suitable for routing in wireless sensor network. With low routing cost, good adaptability and multipath, the algorithm balanced energy consumption to prolong network lifetime. In terms of simulation and experiments, ant colony algorithm was proved to be suitable for finding optimal routing in wireless sensor network, thus achieving design goal of routing algorithm.
previous article Reliable and Energy Efficient Communication Algorithm in Hierarchical Wireless Sensor Networks
next article Performance Optimization Based on Compressive Sensing for Wireless Sensor Networks

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Literature
1.
Jiming, C., Ruizhong, L., & Youxian, S. (2006). Communication system of WSN. Chinese Journal of Sensors and Actuators, 19(4), 1290–1295.
2.
Rongquan, W., & Liqun, Q. (2006). Summary of WSN. Pervasive Computing and New Software Technology—Third Yangtze River Delta Computer Technology Forum.
3.
Dongxin, L., Wenlong, X., & Licun, W. (2005). Wireless sensor network. Industrial Control Computer, 18(04), 24–26.
4.
Fang, D., & Peiliang, Q. (2009). Random routing protocol for wireless sensor network. Journal of Zhejiang University (Engineering Edition), 43(4), 621–625.
5.
Wei, K. (2005). Key technology and research difficulty of WSN. Telecommunication Science, 21(6), 9–12.
6.
Jianzhong, L. (2007). Preface of wireless sensor network. Journal of Software, 18(5), 1077–1079.
7.
Li, C., Hailing, J., Yong, M., et al. (2005). Research progress of wireless sensor network. Computer Research and Development, 42(1), 163–174.CrossRef
8.
Jianzhong, L., & Hong, G. (2008). Research progress of wireless sensor network. Computer Research and Development, 45(1), 11–15.
9.
Guangbin, W., & Changyin, L. (2004). Energy efficiency of wireless sensor network. Journal of Transducer Technology, 7, 74–76.
10.
Haibin, D. (2005). Principle and application of ant colony algorithm. Beijing: Science Press.
11.
Wu, Q., & Wang, L. (2004). Intelligent ant colony algorithm and its application. Shanghai: Shanghai Scientific and Technological Education Publishing House.
12.
Liu, Z., Kwiat kowska, M. Z., & Constantinou, C. (2004). A swarm intelligence routing algorithm for manets. In Proceedings of the IASTED international conference on communications internet and information technology, St. Thomas, USA.
13.
Liu, Z., Kwiat kowska, M. Z., & Constantinou, C. (2005). A biologically inspired congestion control routing algorithm for MANETs. In Third IEEE international conference on pervasive computing and communications workshops (pp. 226–231).
14.
Hussein, O., & Saadawi, T. (2003). Ant routing algorithm for mobile ad-hoc networks (ARAMA). In Proceedings of the 2003 IEEE international conference on performance, computing, and communications conference (pp. 281–290).
15.
Zhang, Q., Xie, Z., Ling, B., Sun, W., & Bole, S. (2005). Maximum lifetime data collection algorithm for wireless sensor networks. Journal of Software, 16(11), 1946–1957.CrossRef
16.
Yajie, M., Dasheng, Z., Yuming, W., & Jianhua, H. (2005). Sensor network life extension algorithm based on power control. Computer Engineering and Applications, 41(21), 4–7.
17.
Jianrong, L., & Yangli, W. (2005). Scalability implementation algorithm for wireless sensor networks. Electronic Science and Technology, 2, 26–29.
18.
Datta, A. (2005). A fault-tolerant protocol for energy efficient permutation routing in wireless networks. IEEE Transactions on Communications, 54(11), 22–31.
19.
Farivar, R., Fazeli, M., & Miremadi, S. G. (2005). Directed flooding: Fault-tolerant routing protocol for wireless sensor networks. In Proceedings of the 2005 systems communications (ICWOS).
20.
Hussein, O., & Saadawi, T. (2003). Ant routing algorithm for mobile ad-hoc networks (ARAMA). In Proceedings of the 2003 IEEE international conference on performance, computing, and communications conference (pp. 281–290).
21.
22.
Metadata
Title
Routing Technology in Wireless Sensor Network Based on Ant Colony Optimization Algorithm
Authors
Zheng Enxing
Liu Ranran
Publication date
23-09-2016
Publisher
Springer US
Published in
Wireless Personal Communications / Issue 3/2017
Print ISSN: 0929-6212
Electronic ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-016-3755-1

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