Articles

Lightweight Multi-agent Framework for a Cluster-based Wireless Sensor Network

Published:
August 4, 2018
Authors
View
Keywords
License

Copyright (c) 2018 by the authors

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How To Cite
Selected Style: APA
Bano, S., Afghan, S. A., Jokhio , S. H., Talpur, S., & Jokhio, I. A. (2018). Lightweight Multi-agent Framework for a Cluster-based Wireless Sensor Network. Recent Innovations in Mechatronics, 5(Special issue: "student papers"), 1-7. https://doi.org/10.17667/riim.2018.si/19.
Abstract

Sensor applications and wireless sensor networks (WSNs) are becoming a part of our everyday life. A number of network arrangements are used in WSN. In this paper, we focus on the cluster based network to help identify the issues associated with communication within such networks. We present a lightweight multi-agent routing framework for a cluster based WSN to resolve some issues associated with such networks. By using state- of-art protocol in a unique combination and categorizing cluster layers, we take full advantage of the properties of the selected protocols. The simulation results illustrate that the proposed method is light-weight in terms of energy consumption by the sensor nodes communicating information within a cluster based network. Nevertheless, high network throughput and robust data communication are also achieved.

References
  1. Li, C.; Zhang, H.X.; Hao, B.B.; Li, J.D. A survey on routing protocols for large-scale wireless sensor networks. Sensors 2011, 11, 34983526.
  2. Prasath, K.A.; Shankar, T., ”RMCHS: Ridge method based cluster head selection for energy efficient clustering hierarchy protocol in WSN,” in Smart Technologies and Management for Computing, Communication, Controls, Energy and Materials (ICSTM), 2015 International Conference on , vol., no., pp.64-70, 6- 8 May 201
  3. Wei, C.; Yang, J.; Gao, Y.; Zhang, Z. Cluster-Based Routing Protocols in Wireless Sensor Networks: A Survey. In Proceedings of 2011 In- ternational Conference on Computer Science and Network Technology, Harbin, China, 2426 December 2011; pp. 16591663
  4. Abdullah, J.; Zeni, S., ”Maximizing the network lifetime of clustered- based WSN using probability of residual energy,” in Control System, Computing and Engineering (ICCSCE), 2014 IEEE International Con- ference on , vol., no., pp.178-183, 28-30 Nov. 2014.
  5. Xu, D.; Gao, J. Comparison study to hierarchical routing protocols in wireless sensor networks. Procedia Environ. Sci. 2011, 10, 595600.
  6. Roslin, S.E., ”Genetic algorithm based cluster head optimization using topology control for hazardous environment using WSN,” in Innovations in Information, Embedded and Communication Systems (ICIIECS), 2015 International Conference on , vol., no., pp.1-7, 19-20 March 2015.
  7. Roy, S.; Kumar Das, A., ”Energy efficient cluster based routing pro- tocol (EECBRP) for Wireless Sensor Network,” in Networks and Soft Computing (ICNSC), 2014 First International Conference on , vol., no., pp.25-29, 19-20 Aug. 2014.
  8. Chakraborty, S.; Khan, A.K., ”A noble approach for self learning and cluster based routing protocol with power efficiency in
  9. WSN,” in Communications and Signal Processing (ICCSP), 2014 International Conference on , vol., no., pp.773-777, 3-5 April 2014.
  10. Haneef, M.; Deng, Z. Design challenges and comparative analysis of cluster based routing protocols used in wireless sensor networks for improving network life time. Adv. Inf. Sci. Serv. Sci. 2012, 4, 450459.
  11. Ishmanov, F.; Malik, A.S.; Kim, S.W. Energy consumption balancing (ECB) issues and mechanisms in wireless sensor networks (WSNs): A comprehensive overview. Eur. Trans. Telecommun. 2011, 22, 151167.
  12. Gemeda, K.A.; Gianini, G.; Libsie, M., ”The effect of node selfishness on the performance of WSN cluster-based routing algorithms,” in AFRICON, 2015 , vol., no., pp.1-5, 14-17 Sept. 2015.
  13. Abdulsalam, H.M.; Kamel, L.K. W-LEACH: Weighted Low Energy Adaptive Clustering Hierarchy aggregation algorithm for data streams in wireless sensor networks. In Proceedings of IEEE International Conference on Data Mining Workshops (ICDMW), Sydney, Australia,14 December 2010, pp. 18.
  14. Zeb, A.; Islam, A.K.M.M.; Komaki, S.; Baharun, S., ”Multinodes join- ing for dynamic cluster-based Wireless Sensor Network,” in Informatics, Electronics and Vision (ICIEV), 2014 International Conference on , vol., no., pp.1-6, 23-24 May 2014.
  15. Hong, J.; Kook, J.; Lee, S.; Kwon, D.; Yi, S. T-LEACH: The method of threshold-based cluster head replacement for wireless sensor networks. Inf. Syst. Front. 2009, 11, 513521
  16. Loscri, V. ; Morabito, G. ; Marano, S., A Two-Levels Hierarchy for Low-Energy Adaptive Clustering Hierarchy (TL-LEACH), Vehicular Technology Conference, 2005. VTC-2005-Fall. 2005 IEEE 62nd , pp 18. 1809 1813, 25-28 Sept., 2005
  17. Network simulator 2 (NS2), www.isi.edu/nsnam/ns/ [Last accessed 26- 20. 12-2017].
  18. Handy M. J.; Haase M.; Timmermann D.; Low Energy Adaptive Clus- tering Hierarchy with Deterministic Cluster-Head Selection, In Proc.4th International Workshop on Mobile and Wireless CommunicationsNet- work, USA, 2002, Vol. 1, pp. 368-372. 22.
  19. Heinzelman W. B.; Chandrakasan A. P.; Member S. and Balakrishnan H., An Application-Specific Protocol Architecture for Wireless
  20. Microsensor Networks, IEEE Transactions on Wireless Communications, vol. 1, no. 23. 4, pp. 660670, 2002.
  21. Lindsey S. and Raghavendra C., PEGASIS: Power-Efficient Gathering in Sensor Information Systems, In Proc. IEEE Aerospace Conference, USA, Montana, 2002, Vol. 3, pp. 1125-1130.
  22. Manjeshwar A. and Agrawal D. P., ”TEEN: a routing protocol for enhanced efficiency in wireless sensor networks,” Proceedings 15th International Parallel and Distributed Processing Symposium. IPDPS 26. 2001, San Francisco, CA, USA, 2001, pp. 2009-2015.
  23. Li Q.; Aslam J. and Rus D., Hierarchical Power-aware Routing in Sensor Networks, In Proc. DIMACS Workshop on Pervasive Networking, California, 2001, pp. 25-27
  24. Younis O. and Fahmy S., ”HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks,” in IEEE
  25. Transactions on Mobile Computing, vol. 3, no. 4, pp. 366-379, Oct.-Dec. 2004.
Database Logos