A Combined Method for Dynamic Routing in Mobile Ad-Hoc Networks
Subject Areas : Electronics EngineeringFatemeh Shabih 1 , Jalil azimpour 2 , Marziye Dadvar 3
1 - Master student of Computer Software Department, Bushehr Branch, Islamic Azad University, Bushehr, Iran
2 - Department of Computer Software, Bushehr Branch, Islamic Azad University, Bushehr, Iran
3 - Department of Artificial Intelligence, Bushehr Branch, Islamic Azad University, Bushehr, Iran
Keywords:
Abstract :
Wireless sensor networks are a large number of sensor nodes with limited energy in a scattered geographically limited area. Due to limited resources in wireless sensor networks, increasing the lifetime of the networks by reducing energy consumption is always considered. More nodes to send data to the central station energy consumption. Sequential routing based on clustering, this responsibility falls on the head, and this increases the energy consumption of cluster heads. In recent years later all the energy of cluster heads, routing protocols and a lot of clustering is proposed. The purpose of this study, the combination of clustering and routing in order to extend the lifetime of this type of network. For clustering of genetic algorithm with fixed and harmony search algorithm is used for routing. Customize search algorithm for routing in harmony, three criteria neighborhood, reducing energy consumption and proper distribution of energy consumption is taken into account. Harmony algorithm is proposed to establish a proper balance between the criteria listed will generate more efficient routes. Finally change the routing cluster heads in each round will be balancing energy consumption between nodes per cluster. The results of the tests show the superiority of 2.14% proposed increase in messaging as well as 24.84% Lifetime network protocol is DEEC.
1. Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). Wireless sensor networks: a survey. Computer networks, 38(4), pp. 393-422.
2. Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). A survey on sensor networks. IEEE Communications magazine, 40(8), pp. 102-114.
3. Bandyopadhyay, S., & Coyle, E. J. (2003, April). An energy efficient hierarchical clustering algorithm for wireless sensor networks. In INFOCOM 2003. Twenty-Second Annual Joint Conference of the IEEE Computer and Communications. IEEE Societies (Vol. 3, pp. 1713-1723).
4. Bao, X. R., Zhang, S., & Xue, D. Y. (2008, October). Research and Simulation on Genetic Ant Colony Routing in Wireless Sensor Network. In Wireless Communications, Networking and Mobile Computing, WiCOM'08. 4th International Conference on (pp. 1-5). IEEE.
5. Biradar, C., Sunilkumar, & Manvi, S. (2012). Neighbor supported reliable multipath multicast based genetic routing in MANETs. Network and Computer App, vol. 35, no. 3, pp. 1074-1085.
6. Chandra, M. L., Ravi Chandra, P., & Reddy, S. (2015). QFSRD: Orthogenesis Evolution based Genetic Algorithm for QoS Fitness Scope aware Route Discovery in Ad hoc Networks. Global Journal of Computer Science and Technology 15.3.
7. Chiang, C. (1997). Routing in Clustered Multihop, Mobile Wireless Networks with Fading Channel. Proc. IEEE SICON’97, pp.197-211.
8. Clausen, T., & Jacquet, P. (2003). Optimized Link State with genetic Routing Protocol (OLSR). IETF, RFC 3626.
9. Djukic, P., & Valaee, S. (2009). Delay aware link scheduling for multi-hop TDMA wireless networks. IEEE/ACM Transactions on Networking (TON), 17(3), pp. 870-883.
10. El-Rabbany, A. (2002). Introduction to GPS: the global positioning system. Artech house.
11. Geem, Z. W., Kim, J. H., & Loganathan, G. V. (2001). A new heuristic optimization algorithm: harmony search. Simulation, 76(2), pp. 60-68.
12. Heinzelman, W. R., Chandrakasan, A., & Balakrishnan, H. (2000, January). Energy-efficient communication protocol for wireless microsensor networks. In System sciences, Proceedings of the 33rd annual Hawaii international conference on (pp. 10-pp). IEEE.
13. Holland, J. H. (1992). Genetic algorithms. Scientific american, 267(1), pp. 66-72.
14. Jinhua, Z., & Xin Wang, X. (2012). Model and Protocol for Energy-Efficient Routing based genetic algorithm over Mobile Ad Hoc Networks. IEEE Trans.Mobile Computing, vol. 10, no. 11, pp. 2473 –2483.
15. Khan, M. I., Gansterer, W. N., & Haring, G. (2014). The influence of basic parameters on energy efficiency in wireless sensor networks. Vol. 36, no. 9, pp. 965–978.
16. Lee, K. S., & Geem, Z. W. (2015). A new meta-heuristic algorithm for continuous engineering optimization. harmony search theory and practice, Computer Methods in Applied Mechanics and Engineering, vol.194, no.36-38, pp.3902-3933.
17. Minhas, M. R., Gopalakrishnan, S., & Leung, V. C. (2008, November). Fuzzy algorithms for maximum lifetime routing in wireless sensor networks. In Global Telecommunications Conference, 2008. IEEE GLOBECOM 2008. IEEE (pp. 1-6). IEEE.
18. Nazir, B., & Hasbullah, H. (2010). Mobile Routing Protocol (MRP) for Prolonging Network Lifetime in Clustered Wireless Sensor Network. Computer Applications and Industrial Electronics, pp. 624 – 629.
19. Nehra, N. K., Kumar, M., & Patel, R. B. (2009, December). Neural network based energy efficient clustering and routing in wireless sensor networks. In Networks and Communications, 2009. NETCOM'09. First International Conference on (pp. 34-39). IEEE.
20. Niansheng, C., Zhi, L., Zongwu, K., & Xiaoshan, G. (2010, August). A QoS multicast routing algorithm based on genetic algorithm of game selection. In Distributed Computing and Applications to Business Engineering and Science (DCABES), 2010 Ninth International Symposium on (pp. 308-311). IEEE.
21. Qing, L., Zhu, Q., & Wang, M. (2006). Design of a distributed energy-efficient clustering algorithm for heterogeneous wireless sensor networks. Computer communications, 29(12), pp. 2230-2237
22. Shankar, T., & Shanmugavel, S. (2014). Energy optimization in cluster based wireless sensor networks. Journal of Engineering Science and Technology 9.2, pp.246-260.
23. Xu, X., Yuruk, N., Feng, Z., & Schweiger, T. A. (2007, August). Scan: a structural clustering algorithm for networks. In Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 824-833). ACM.
24. Xun-Xin, Y., & Rui-Hua, Z. (2013). An Energy-Efficient Mobile Routing Algorithm for Wireless Sensor Networks. Wireless Communications, Networking and Mobile Computing (WiCOM), pp. 1-4.
25. Yao, G. S., Dong, Z. X., Wen, W. M., & Ren, Q. (2016). A Routing Optimization Strategy for Wireless Sensor Networks Based on Improved Genetic Algorithm, 19(2), pp. 221-228.
26. Younis, O., & Fahmy, S. (2004). HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Transactions on mobile computing, 3(4), pp. 366-379.
27. Yuan, P., Ji, C., Zhang, Y., & Wang, Y. (2004, March). Optimal multicast routing in wireless ad hoc sensor networks. In Networking, Sensing and Control, 2004 IEEE International Conference on (Vol. 1, pp. 367-371). IEEE.
28. Yusuf, M., & Haider, T. (2005, September). Energy-aware fuzzy routing for wireless sensor networks. In Emerging Technologies, Proceedings of the IEEE Symposium on (pp. 63-69). IEEE.
29. باطنی, زهره؛ سمیرا بابالو و میثم وکیلی، ۱۳۹۲، کاهش مصرف انرژی در شبکههای حسگر بیسیم با استفاده از الگوریتمهای خوشهبندی، اولین همایش منطقهای شبکههای کامپیوتری، قم، دانشکده فنی و حرفهای سما واحد قم.
30. قره جانلو, مسعود؛ مسعود نصرتآبادی و محمدحسین یغمایی مقدم، ۱۳۸۸، ارائهی یک روش فازی جهت کاهش مصرف انرژی در پروتکلهای مسیریابی شبکههای حسگر بیسیم، پانزدهمین کنفرانس بینالمللی سالانه انجمن کامپیوتر ایران، تهران، انجمن کامپیوتر، مرکز توسعه فناوری نیرو.
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