A DETAILED SUMMARY OF OPTIMIZATION ALGORITHMS FOR MOBILE-WSN
Keywords:
Heuristic Algorithm, Mobile Wireless Sensor Network, Cross layer Routing
Abstract
Mobile wireless sensor networks (MWSN) are a result of recent advancements in wireless telecommunications. The sensor nodes that make up these networks are mobile in addition to being inexpensive and having a short battery life. Numerous applications have been developed for these networks because of their inherent properties. Rescue efforts in the impacted areas, surveillance, and surveillance systems are all possible with it. Traffic signals are transmitted using it. Movable equipment that has energy limits and is energy-conserving is a considerable tool in its design. According to the needs of the aforementioned applications and taking into consideration the wireless sensor nodes. The MWSN allows the sensor nodes to move autonomously and communicate with one another, doing away with the need for centralised control. These networks can outperform static wireless sensor networks due to their longer network lifetime, reduced power consumption, more bandwidth availability, and better targeted capabilities. Given that the sensor nodes in MWSN are resource-constrained, low-cost mobile devices, the routing process is frequently challenging in mobile networks. Many problems, including maintaining network access, reducing energy consumption, and providing enough sensing coverage, to name a few, remain unresolved despite the development of a variety of efficient routing techniques for MWSNs as a consequence of contemporary research. This paper presents the sophisticated routing protocols in the MWSN, which addresses many routing issues. The communication network, information state, power proficiency, and mobility of the routing protocols are categorised. The categorization shown here encompasses the core components of a number of theories that have been proposed in the literature for efficient routing in MWSN and also sheds light on potential upgrades to the existing routing protocols.
References
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32. J. Shi, X. Wei, W. Zhu, “An efficient algorithm for energy Management in Wireless Sensor Networks via employing multiple mobile sinks”, International Journal of Distributed Sensor Networks, Article ID 3179587, 2016.
33. Y. Yue, J. Li, H. Fan, Q. Qin, “Optimization-based artificial bee Colony algorithm for data collection in large-scale mobile wireless sensor networks”, Journal of Sensors, p Article ID 7057490, 2016.
34. S. Deng, J. Li, L. Shen L, “Mobility-based clustering protocol for wireless sensor networks with mobile nodes”, IET Wireless Sensor Systems, vol. 1, issue 1, pp. 39-47, 2011.
35. R. Velmani, B. Kaarthick, “An efficient cluster-tree based data collection scheme for large mobile wireless sensor networks”, IEEE Sensors Journal, vol. 15, issue 4, pp.2377-2390, 2015.
2. G. Anastasi, M. Conti, M. Di Francesco, and A. Passarella, “Energy conservation in wireless sensor networks: a survey”, Ad Hoc Networks, vol. 7, pp. 537–568, 2009.
3. B. Liu, P. Brass, O. Dousse, P. Nain, and D. Towsley, “Mobility improve coverage of sensor networks”, In Proc. of ACM MobiHoc, 2005.
4. S. Chellappan, X. Bai, B. Ma, D. Xuan, and C. Xu, “Mobility limited flip-based sensor networks deployment”, IEEE Transactions on Parallel and Distributed Systems, vol. 18, Issue 2, pp.199–211, 2007.
5. S. Chellappan, X. Bai, B. Ma, D. Xuan and C. Xu, “Mobility limited flip-based sensor networks deployment”, IEEE Transactions on Parallel and Distributed Systems, vol. 18, no. 2, pp.199–211, 2007.
6. K. Dantu, M. H. Rahimi, H. Shah, S. Babel, A. Dhariwal, and G.S. Sukhatme, “Robomote: enabling mobility in sensor networks”, In Proceedings of IPSN 2005, pp. 404–409, 2005.
7. U. Lee, E.O. Magistretti, B.O. Zhou, M. Gerla, P. Bellavista, and A. Corradi, “Efficient data harvesting in mobile sensor platforms”, In Proceedings of PerCom workshops, pp. 352–356, 2006.
8. R. Kuntz, J. Montavont, and T. Noël, “Improving the medium access in highly mobile wireless sensor networks”, Telecommunication Systems. doi:10.1007/s11235-011-9565-6, 2011.
9. R. Sharma, “Energy Holes Avoiding Techniques in Sensor Networks: A survey”, International Journal of Engineering Trends and Technology, vol. 20, no.4, pp. 204-208, 2015.
10. R. Sharma, D.K. Lobiyal, “Proficiency Analysis of AODV, DSR and TORA Ad-hoc Routing Protocols for Energy Holes Problem in Wireless Sensor Networks”, Elsevier Procedia Computer Science, vol. 57, pp.1057-1066, 2015.
11. R. Sharma, D.K. Lobiyal, “Multi-Gateway-Based Energy Holes Avoidance Routing Protocol for WSN”, Informatics , vol. 3, no. 5,pp. 1-26, 2016.
12. K.-H. Chen, J.-M. Huang and C.-C Hsiao, “CHIRON: an energy efficient chain based hierarchical routing protocol in wireless sensor networks”. In Proceedings of wireless telecommunications symposium (WTS’09) pp. 1–5, 2009.
13. R. Sharma, D.K. Lobiyal, “Dual Transmission Power and Ant Colony Optimization Based Lifespan Maximization Protocol for Sensor Networks”, International Journal of Business Data Communications and Networking, vol. 11 Issue 1, pp. 1-14, 2015.
14. D.Gavidia and M.Van Steen, “A probabilistic replication and storage scheme for large wireless networks of small devices”, In Proceedings of 5th IEEE int’l conf. mobile and ad hoc sensor systems (MASS). New York: IEEE Press, 2008.
15. H. Hatime, K. Namuduri, and J.M. Watkins, “OCTOPUS: an on-demand communication topology updating strategy for mobile sensor networks”, IEEE Sensors Journal, vol. 11, issue 4, pp.1004–1012, 2011.
16. J. N. Al-Karaki, and A.E. Kamal, “Routing techniques in wireless sensor networks: a survey” In IEEE Wireless Communication, pp. 6–28, 2004.
17. S.Hooda, K. Bhatia, R. Sharma, “Enrichment of Life span of Sensor Networks through BCO and Gateway Node”, International Journal of Research in Information Technology, vol. 4, Issue 5, pp. 9-20, 2016.
18. P. Chhillar, K. Bhatia, R. Sharma, “Spiral Based Sink Mobility Method Aiming Lengthening of Lifetime of Sensor Networks”, International Research Journal of Engineering and Technology, vol. 3, issue 5, 2016.
19. D. Kim, and Y. Chung, Y, “Self-Organization Routing Protocol Supporting Mobile Nodes for Wireless Sensor Network”, In Proc. of the 1st international multi-symposiums on Computer and Computational Sciences (IMSCCS’06). pp.622-626, 2006.
20. Y. Han, and Z. Lin., Z, “A geographically opportunistic routing protocol used in mobile wireless sensor networks”,, In Proc. of the 9th IEEE international conference on Networking, Sensing and Control (ICNSC). pp.216-221, 2012.
21. A. Aronsky and A. Segall, “A multipath routing algorithm for mobile Wireless Sensor Networks”, In Proc. of the 3rd Joint IFIP Wireless and Mobile Networking Conference. pp.1-6, 2010.
22. T. Hayes and F. Ali “Robust Ad-hoc Sensor Routing (RASeR) Protocol for Mobile Wireless Sensor Networks”, Elsevier Ad Hoc Networks, vol. 50, issue 1, pp. 128-144, 2016.
23. T. Hayes and F. Ali, “Location Aware Sensor Routing (LASeR) Protocol for Mobile Wireless Sensor Networks.”, IET Wireless Sensor Systems, vol. 6, issue 2, pp. 49-57, 2016.
24. A. Rana, K. Bhatia, R. Sharma, “ETM: a survey on energy, thermal and mobility efficient routing protocols for wireless body area sensor network”, International Research Journal of Commerce , Arts and Science, vol. 8, Issue 4, pp. 28-40, 2017.
25. R. Sharma and D.K. Lobiyal, “Intelligent Water Drop Based Coverage- Connectivity and Lifespan Maximization Protocol for Wireless Sensor Networks”, Recent Patents on Computer Science, vol. 13, issue 3, pp. 261-273, 2019.
26. Kamakshi, Princy, K. Bhatia, S. Bhadola, R. Sharma, “Development of A-Leach Protocol for WSN”, International Journal of Innovative Research in Computer and Communication Engineering, vol. 8, Issue 7, pp. 2778-2785, 2020.
27. Y. Gu, L. Zhao, D. Jing, “A novel routing protocol for mobile nodes in WSN”, in: Proceeding of the 2012 International Conference on Control Engineering and Communication Technology (ICCECT); 7-9 December 2012; Liaoning. China: IEEE; 2013. pp. 624-627, 2012.
28. G. S. Kumar, PVM Vinu, K.P. Jacob, Mobility metric based LEACH-mobile protocol. in: proc. of the 16th International Conference on Advanced Computing and Communications, 2008 (ADCOM 2008); 14-17 December 2008; Chennai. India: IEEE; 2009. pp. 248-253, 2008.
29. Z. Qi, Y. Mini Y, “A routing protocol for mobile sensor network based on LEACH”, in: proc. of the 10th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM 2014); 26-28 September 2014; Beijing. China: IET, 473-477, 2014.
30. O. Mezghani, M. Abdellaoui, “Improving network lifetime with mobile LEACH protocol for wireless sensors network”, in: proc. of the 15th International Conference on Sciences and Techniques of Automatic Control & Computer Engineering-STA’2014; December 21-23; Hammamet. Tunisia: IEEE; 2014. pp. 613-619, 2014.
31. B. Nazir, H. Hasbullah, “Mobile sink based routing protocol (MSRP) for prolonging network lifetime in clustered wireless sensor network”. in: proceeding of the 2010 International Conference on Computer Applications and Industrial Electronics (ICCAIE 2010); 5-7 December 2010; Kuala Lumpur. Malaysia: IEEE; 2010, pp. 624-629, 2010.
32. J. Shi, X. Wei, W. Zhu, “An efficient algorithm for energy Management in Wireless Sensor Networks via employing multiple mobile sinks”, International Journal of Distributed Sensor Networks, Article ID 3179587, 2016.
33. Y. Yue, J. Li, H. Fan, Q. Qin, “Optimization-based artificial bee Colony algorithm for data collection in large-scale mobile wireless sensor networks”, Journal of Sensors, p Article ID 7057490, 2016.
34. S. Deng, J. Li, L. Shen L, “Mobility-based clustering protocol for wireless sensor networks with mobile nodes”, IET Wireless Sensor Systems, vol. 1, issue 1, pp. 39-47, 2011.
35. R. Velmani, B. Kaarthick, “An efficient cluster-tree based data collection scheme for large mobile wireless sensor networks”, IEEE Sensors Journal, vol. 15, issue 4, pp.2377-2390, 2015.
Published
2023-05-31
How to Cite
Ranjan, R., & Dalal, S. (2023). A DETAILED SUMMARY OF OPTIMIZATION ALGORITHMS FOR MOBILE-WSN. CENTRAL ASIAN JOURNAL OF MATHEMATICAL THEORY AND COMPUTER SCIENCES, 4(5), 154-163. https://doi.org/10.17605/OSF.IO/GCHBV
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