Abstract
In order to maximize the lifetime of a wireless sensor network (WSN), an improved free search (FS) approach, which is called free search with double populations (FSDP), is proposed in this paper. FSDP is a population-based approach which is applied to optimize the energy consumption of a wireless sensor network. A circular network model is adopted and FSDP obtains the optimal solution by finding an optimal transmission path from the nodes of outer girdle bands to the sink node. Simulation results obtained by FSDP show the effectiveness of the proposed optimization approach.
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References
Lewis, F.L.: Wireless Sensor Networks. Smart Environments: Technologies, Protocols, and Applications. John Wiley, New York (2004)
Arampatzis, T., Lygeros, J., Manesis, S.: A Survey of Wireless Sensors and Wireless Sensor Networks. In: Proceedings of IEEE International Symposium on Intelligent Control, pp. 719–724. IEEE Press, Limassol (2006)
Heinzelman, W.B., Chandrakasan, A.P., Balakrishnan, H.: An Application-Specific Protocol Architecture for Wireless Micro-sensor Networks. IEEE Trans. on Wireless Communications 1(4), 660–670 (2002)
Younis, O., Fahmy, S.: HEED: A Hybrid, Energy-Efficient, Distributed Clustering Approach for Ad-Hoc Sensor Networks. IEEE Trans. on Mobile Computing 3(4), 366–379 (2004)
Fariborzi, H., Moghavvemi, M.: EAMTR: Energy Aware Multi-Tree Routing for Wireless Sensor Networks. IET Communications on Wireless Ad-Hop Networks 3(5), 733–739 (2009)
Van Dam, T., Langendoen, K.: An Adaptive Energy Efficient MAC Protocol for Wireless Sensor Networks. In: Proceedings of 1st ACM Conference on Embedded Networked Sensor Systems, pp. 171–180. ACM Press, New York (2003)
Wang, X., Ma, J.J., Wang, S., Bi, D.W.: Distributed Particle Swarm Optimization And Simulated Annealing For Energy-Efficient Coverage In Wireless Sensor Networks. Sensors 7(5), 628–648 (2007)
Lin, C., Wu, G., Xia, F., Li, M., Yao, L., Pei, Z.: Energy Efficient Ant Colony Algorithms For Data Aggregation In Wireless Sensor Networks. Journal of Computer and System Sciences 78(6), 1686–1702 (2012)
Jin, S., Zhou, M., Wu, A.S.: Sensor Network Optimization Using A Genetic Algorithm. In: Proceedings of the 7th World Multi-Conference on Systemics, Cybernetics and Informatics, pp. 1–6. Int. Inst. Informatics & Systemics, Orlando (2003)
Kalin, P., Guy, L.: Free Search: A Novel Heuristic Method. In: Proceedings of the PREP 2003, pp. 133–134. PREP Press, Southampton (2003)
Kalin, P., Guy, L.: Free Search: A Comparative Analysis. Information Sciences 172(1-2), 173–193 (2005)
Zhou, Y., Medidi, M.: Sleep-based topology control for wakeup scheduling in wireless sensor networks. In: IEEE 4th Annual Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, pp. 304–403. IEEE Press, San Diego (2007)
Hu, X.M., Zhang, J.: Ant Routing Optimization Algorithm For Extending The Lifetime Of Wireless Sensor Networks. In: IEEE International Conference on Systems, Man and Cybernetics, pp. 738–744. IEEE Press, Istanbul (2010)
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Chen, Z., Wei, Y., Sun, Q. (2013). An Improved Free Search Approach for Energy Optimization in Wireless Sensor Networks. In: Liu, D., Alippi, C., Zhao, D., Hussain, A. (eds) Advances in Brain Inspired Cognitive Systems. BICS 2013. Lecture Notes in Computer Science(), vol 7888. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38786-9_2
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DOI: https://doi.org/10.1007/978-3-642-38786-9_2
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