Improved Load Balancing Algorithm for Network Lifetime Enhancement in WSN
Keywords:
Wireless sensor networks, Load balancing algorithms, soft computing, fuzzy inference engine, cluster head selection, Sensor cloud, Cloud ComputingAbstract
Wireless sensor networks have been utilized and utilized for their enormous ability in the modern years, because they are perfect solutions for wireless networking applications in real time. Nodes, along with an effective routing scheme shape the back bone of the wireless sensor networks (WSN) determine the overall performance of the WSN. Recently work on load balancing algorithms has been studied as the existence of incoming traffic consisting of information packets is often stochastic and in essence unpredictable. Since the nodes are restricted by their power supply in the form of batteries that cannot be replaced regularly, they are vulnerable to overuse in transmitting all knowledge to a single or chosen node nearest to the base station resulting in rapid power supply drainage. Therefore it is important to provide an intelligent and effective load balancing system for sensor cloud to insure that the job load is spread in a more or less consistent manner resulting in perfect power savings at WSN and proper data deposition in cloud servers.
How to cite this article:
Kanshette S, Sangulagi P, Sutagundar A. Improved Load Balancing Algorithm for Network Lifetime Enhancement in WSN. J Adv Res Wire Mob Telecom 2021; 4(1): 11-19.
References
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2. Han Zhang, Liang Li, Xin-fang Yan and Xiang Li, "A Load-balancing Clustering Algorithm of WSN for Data Gathering," 2011 2nd International Conference on Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), Dengleng, 2011, pp. 915-918.
3. Ozdemir S, “Secure load balancing via hierarchical data aggregation in heterogeneous sensor networks.†J. Inf. Sci. Eng., vol. 25, no. 6, pp. 1691–1705, 2009.
4. Eghbali A N and M. Dehghan (2007), “Load-balancing using multi-path directed diffusion in wireless sensor networks,†Mobile Ad-Hoc and Sensor Networks, 44–55.
5. Meenakshi Diwakar, Sushil Kumar (2012), “An energy efficient level based Clustering routing protocol for wireless Sensor networks†International Journal Of Advanced Smart Sensor Network Systems, 2(2):55-65.
6. Low C P, C. Fang, J. M. Ng and Y. H. Ang, "Load-Balanced Clustering Algorithms for Wireless Sensor Networks," 2007 IEEE International Conference on Communications, Glasgow, 2007, pp. 3485-3490.
7. Robin Gulerial and Ankit Kumar Jain (2013), “Geographic load balanced routing in wireless sensor networkâ€, International journal of computer network and information security, 8:62 – 70.
8. Petrioli C, M. Nati, P. Casari, M. Zorzi and S. Basagni, "ALBA-R: Load-Balancing Geographic Routing Around Connectivity Holes in Wireless Sensor Networks," in IEEE Transactions on Parallel and Distributed Systems, vol. 25, no. 3, pp. 529-539, March 2014.
9. Younis O and S. Fahmy (2004), “HEED: A Hybrid, Energy- Efficient, Distributed Clustering Approach for Ad-hoc Sensor Networks,†IEEE Transactions on Mobile Computing, 3(4):366-379.
10. Sardor Q Hojiev and Dong Seong Kim (2015), “Dynamic load balancing algorithm based on users immigration in wireless LANâ€, Journal of advances in computer networks, 114 – 118.
11. Bejerano Y, S.-J. Han, and L. Li, “Fairness and load balancing in wireless LANs using association control,†IEEE/ACM Transactions on Networking, pp. 560–573, 2007.
12. Y Su Y, S. Zheng, S. Gamage and K. Li, "A Dynamic Load Balancing Routing Algorithm for Distributed Wireless Sensor Networks," 2007 International Conference on Wireless Communications, Networking and Mobile Computing, Shanghai, 2007, pp. 2625-2628.
13. Yan T., Bi Y., Sun L., Zhu H. (2005) Probability Based Dynamic Load-Balancing Tree Algorithm for Wireless Sensor Networks. In: Lu X., Zhao W. (eds) Networking and Mobile Computing. ICCNMC 2005. Lecture Notes in Computer Science, vol 3619. Springer, Berlin, Heidelberg
14. Ali Ghaffari and Vida AghakhanloyeTakanloo (2011), “QoS based routing protocol with load balancing for wireless multimedia sensor networks using genetic algorithmâ€, World applied sciences journal, 15(12): 1659 – 1666.
15. Arash Rahbari, Arash Ghorbannia Delavar (2016), “BCWSN: A dynamic load balancing algorithm for decrease in congestion cost in wireless sensor networkâ€, Journal of mathematics and computer science, 16:18-25.
16. Ren Song Ku and Chia Yi (2015), “A load balancing routing algorithm for wireless sensor networks based on domain decompositionâ€, Ad Hoc networks, 30: 63 – 83.
17. Eslami M, J. Vahidi, M. Askarzadeh, Designing and Implementing a Distributed Genetic Algorithm for Optimizing Work Modes in Wireless Sensor Network, J. math. comput. sci., 11 (2014), 291-299.
18. Raha, Arnab & Naskar, M & Paul, Avishek & Chakraborty, Arpita & Karmakar, Anupam (2013) “A Genetic Algorithm Inspired Load Balancing Protocol for Congestion Control in Wireless Sensor Networks using Trust Based Routing Framework (GACCTR)â€, International Journal of Computer Network and Information Security, 5: 9-20.
19. Castano F, A. Rossi, M. Sevaux, N. Velasco, On the use of multiple sinks to extend the lifetime in connected wireless sensor networks, Electron. Notes Discrete Math., 41 (2013), 77-84.
20. Modupe I A, O. O. Olugbara, A. Modupe, Minimizing Energy Consumption in Wireless Ad hoc Networks with Meta heuristics, ProcediaComput. Sci., 19 (2013), 106 - 115.
21. Mehmood A, Z. Lv, J. Lloret, and M. M. Umar, “ELDC: an artificial neural network based energy-efficient and robust routing scheme for pollution monitoring in WSNs,†IEEE Transactions on Emerging Topics in Computing, vol. 99, p. 1, 2017
22. Kacimi R, R. Dhaou, A. L. Beylot, Load balancing techniques for lifetime maximizing in wireless sensor networks, Ad Hoc Networks, vol 11,no8 (2013), 2172 - 2186.
23. E. Vishnupriya, T. Jayasankarand P. Maheswara Venkatesh ,SDAOR: Secure Data Transmission of Optimum Routing Protocol in Wireless Sensor Networks For Surveillance Applications, ARPN Journal of Engineering and Applied Sciences, 10- 16( 2015), 6917-6931.
24. K. VinothKumar, T. Jayasankar, M. Prabhakaran and V. Srinivasan, Fuzzy Logic based Efficient Multipath Routing for Mobile Adhoc Networks, Appl. Math. Inf. Sci. vol 11, no.2, (2017), 449–455
Published
2021-09-24
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