Browse > Article
http://dx.doi.org/10.11627/jkise.2019.42.1.087

Ranking Artificial Bee Colony for Design of Wireless Sensor Network  

Kim, Sung-Soo (Department of Industrial Engineering, Kangwon National University)
Publication Information
Journal of Korean Society of Industrial and Systems Engineering / v.42, no.1, 2019 , pp. 87-94 More about this Journal
Abstract
A wireless sensor network is emerging technology and intelligent wireless communication paradigm that is dynamically aware of its surrounding environment. It is also able to respond to it in order to achieve reliable and efficient communication. The dynamical cognition capability and environmental adaptability rely on organizing dynamical networks effectively. However, optimally clustering the cognitive wireless sensor networks is an NP-complete problem. The objective of this paper is to develop an optimal sensor network design for maximizing the performance. This proposed Ranking Artificial Bee Colony (RABC) is developed based on Artificial Bee Colony (ABC) with ranking strategy. The ranking strategy can make the much better solutions by combining the best solutions so far and add these solutions in the solution population when applying ABC. RABC is designed to adapt to topological changes to any network graph in a time. We can minimize the total energy dissipation of sensors to prolong the lifetime of a network to balance the energy consumption of all nodes with robust optimal solution. Simulation results show that the performance of our proposed RABC is better than those of previous methods (LEACH, LEACH-C, and etc.) in wireless sensor networks. Our proposed method is the best for the 100 node-network example when the Sink node is centrally located.
Keywords
Wireless Sensor Network; Ranking Artificial Bee Colony(RABC); LEACH; LEACH-C;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Heinzelman, W.R., Chandrakasan, A., and Balakrishnan, H., An Application-Specific Protocol Architecture for Wireless Micro-sensor Networks, IEEE Transactions on Wireless Communications, 2002, Vol. 1, No. 4, pp. 660-670.   DOI
2 Heinzelman, W.R., Chandrakasan, A., and Balakrishnan, H., Energy-efficient communication protocol for wireless micro-sensor networks, in Proceedings of the Hawaii International Conference on System Sciences, 2000.
3 Hussain, S., Matin, A.W., and Islam, O., Genetic algorithm for hierarchical wireless sensor networks, Journal of Networks, 2007, Vol. 2, No. 5, pp. 87-97.
4 Ibriq, J. and Mahgoub, I., Cluster-based routing in wireless sensor network : Issues and Challenges, SPECTS' 04, 2004, pp. 759-766.
5 Jin, S., Zhou, M., and Wu, A.S., Sensor network optimization using a genetic algorithm, in Proceedings of the 7th world Muti-conference on Systems, Cybernetics and Informatics, 2003.
6 Kannan, A.A., Mao, G., and Vucetic, B., Simulated annealing based wireless sensor network localization, Journal of Computers, 2006, Vol. 1, No. 2, pp. 15-22.
7 Karaboga, D. and Akay, B., A comparative study of Artificial Bee Colony algorithm, Applied Mathematics and Computation, 2009, Vol. 214, No. 1, pp. 108-132.   DOI
8 Karaboga, D. and Basturk, B., A powerful and efficient algorithm for numerical function optimization : artificial bee colony algorithm, Journal of Global Optimization, Vol. 39, No. 3, 2007, pp. 459-471.   DOI
9 Karaboga, D. and Basturk, B., On the performance of artificial bee colony (ABC) algorithm, Applied Soft Computing, Vol. 8, No. 1, 2008, pp. 687-697.   DOI
10 Kim, S. and Byun, J., Harmony Search Clustering Design for Energy Efficiency in Wireless Sensor Network, Telecommunications Review, Vol. 23, No. 4, 2013, pp. 516-525.
11 Kim, S., Byeon, J., Lee, S., McLoone, S., and Liu, H., Cognitively Inspired Artificial Bee Colony Clustering for Cognitive Wireless Sensor Networks, Cognitive Computation, 2017, Vol. 9, pp. 207-224.   DOI
12 Kim, S., Jang, S., and Lee, K., Optimal Design and Performance in Clustering of Wireless Sensor Network using BPSO, Telecommunications Review, 2011, Vol. 21, No. 2, pp. 331-342.
13 Kulkarni, R.V., Forster, A., and Venayagamoorthy, G.K., Computational intelligence in wireless sensor networks : A Survey, IEEE Communications Surveys & Tutorials, 2011, Vol. 13, No. 1, pp. 68-96.   DOI
14 Latiff, N.M.A., Tsimenidis, C.C., and Sharif, B.S., Energy-aware Clustering for Wireless Sensor Networks using Particle Swarm Optimization, IEEE, PIMRC'07, 2007.
15 Yick, J., Mukherjee, B., and Ghosal, D., Wireless sensor network survey, Computer networks, Vol. 52, No. 12, 2008, pp. 292-233.   DOI