Power Management using Neural Networks for Wireless Sensor Network

Shri Anil Dattatraya Nimbalkar *
Department of Electronics & Telecommunication Engineering, Kolhapur Institute of Technology's College of Engineering (Autonomous), Kolhapur, Maharashtra, India.
Periodicity:July - December'2021

Abstract

Intelligent analysis is used to process the structure of a wireless sensor network (WSN) and produce some information that can be used to improve the performance of the WSN's management applications. This paper introduces a new approach for wireless sensor networks which is based on neural networks. The presented work is an intelligent method based on the existing concept of multi-agent systems for WSN management. The proposed work shows a performance improvement. Wireless sensor networks need to be managed in different ways, e.g. power consumption of each sensor, efficient data routing without redundancy, control of data reading and sending intervals, etc. The random distribution of wireless sensors, the numerous variables that affect the operation of the WSN, and the uncertainty of various algorithms (for example, self-localization of sensors) make the WSN fuzzy. Given this fuzzy nature and numerous details, a neural network is an ideal tool to use to cover these details, which are so difficult to detect and explicitly, model. This paper presents a neural network-based approach, which results in more efficient routing path discovery and sensor power management.

Keywords

Wireless Sensor Network (WSN), Power Management, Routing, Neural Networks, Agents.

How to Cite this Article?

Nimbalkar, S. A. D. (2021). Power Management using Neural Networks for Wireless Sensor Network. i-manager’s Journal on Wireless Communication Networks, 10(1), 20-27.

References

[1]. Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). A survey on sensor networks. IEEE Communications Magazine, 40(8), 102-114. https://doi. org/10.1109/MCOM.2002.1024422
[2]. Al-Karaki, J. N., & Kamal, A. E. (2004). Routing techniques in wireless sensor networks: a survey. IEEE Wireless Communications, 11(6), 6-28. https://doi.org/10. 1109/MWC.2004.1368893
[3]. Biswas, S., & Morris, R. (2003). Opportunistic routing in multi-hop wireless networks. MIT Laboratory for Computer Science, (pp. 1-6).
[4]. Chang, J. H., & Tassiulas, L. (2000, March). Energy conserving routing in wireless ad-hoc networks. In Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No. 00CH37064) (Vol. 1, pp. 22-31). IEEE. https://doi.org/10.1109/INFCOM.2000.832170
[5]. Chong, C. Y., & Kumar, S. P. (2003). Sensor networks: evolution, opportunities, and challenges. Proceedings of the IEEE, 91(8), 1247-1256. https://doi.org/10.1109/ JPROC.2003.814918
[6]. Fok, C. L., Roman, G. C., & Lu, C. (2005, April). Mobile agent middleware for sensor networks: An application case study. In IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005. (pp. 382-387). IEEE. https://doi.org/10.1109/IPSN.2005. 1440953
[7]. Heinzelman, W. R., Chandrakasan, A., & Balakrishnan, H. (2000, January). Energy-efficient communication protocol for wireless microsensor networks. In Proceedings of the 33rd Annual Hawaii International Conference on System Sciences (pp. 10-pp). IEEE.
[8]. Hosseingholizadeh, A., & Abhari, A. (2009, March). A new agent-based solution for wireless sensor networks management. In Proceedings of the 2009 Spring Simulation Multiconference (pp. 1-6).
[9]. Hu, L., Li, Y., Chen, Q., Liu, J. Y., & Long, K. P. (2007, September). A new energy-aware routing protocol for wireless sensor networks. In 2007, International Conference on Wireless Communications, Networking and Mobile Computing (pp. 2444-2447). IEEE. https://doi.org/10.1109/WICOM.2007.609
[10]. Hussain, S., Shakshuki, E., & Matin, A. W. (2006, April). Agent-based system architecture for wireless sensor networks. In 20th International Conference on Advanced Information Networking and Applications-Volume 1 (AINA'06) (Vol. 2, pp. 5-pp). IEEE. https://doi.org/10.1109/ AINA.2006.76
[11]. Lim, H. B., Wang, B., Fu, C., Phull, A., & Ma, D. (2008, June). A middleware services simulation platform for wireless sensor networks. In 2008, The 28th International Conference on Distributed Computing Systems Workshops (pp. 168-173). IEEE. https://doi.org/10.1109/ ICDCS.Workshops.2008.101
[12]. Tynan, R., Marsh, D., O'kane, D., & O'Hare, G. M. (2005, June). Agents for wireless sensor network power management. In 2005, International Conference on Parallel Processing Workshops (ICPPW'05) (pp. 413-418). IEEE. https://doi.org/10.1109/ICPPW.2005.19
[13]. Ying, Z., & Debao, X. (2005, September). Mobile agent-based policy management for wireless sensor networks. In 2005, Proceeding of International Conference on Wireless Communications, Networking and Mobile Computing, (Vol. 2, pp. 1207-1210). IEEE. https://doi.org/10.1109/WCNM.2005.1544270
[14]. Zhang, Y., Ramkumar, M., & Memon, N. (2004, November). Information flow based routing algorithms for w i r e l e s s s e n s o r n e t w o r k s . I n I E E E G l o b a l Telecommunications Conference, 2004. GLOBECOM'04. (Vol. 2, pp. 742-747). IEEE. https://doi.org/10.1109/ GLOCOM.2004.1378059

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