Distributed Routing Protocol in Wireless Sensor Networks through Mimetic Algorithm and Time-Sharing Approach to Select Cluster Head
الموضوعات : Majlesi Journal of Telecommunication Devices
Sahar Nassirpour
1
(
Department of Computer Engineering, Zahedan Branch, Islamic Azad University, Zahedan, Iran.
)
Shayesteh Tabatabaei
2
(
Department of Computer Engineering, Higher Educational Complex of Saravan, Saravan, Iran.
)
الکلمات المفتاحية: Clustering, IEEE 802.15.4 Standard, Time-division multiple access, Memetic Algorithm, Wireless Sensor Network,
ملخص المقالة :
Wireless sensor networks include sensor nodes communicating each other through wireless links for effective data collection and routing. These wireless nodes are of limited processing power, memory, communication range, channel band width, and battery capacity, from among which the most important is limited capacity of batteries which are unchangeable, under many conditions. The limitation encourages designing efficient protocols in terms of energy consumption. Using clustering is one of the methods to optimize energy consumption. On the other hand, a technical challenge in successful expansion of wireless sensor networks and their exploitation is effective usage made of limited channel band width. To overcome the challenge, one of the methods is dividing schedule of channel usage through TDMA method (Time-Division Multiple Access) so that each cluster head node creates a schedule for transmission of data from member nodes of the cluster through TDMA. Accordingly, in the paper, a distributed routing protocol based on clustering through usage of mimetic algorithm and time-sharing approach is proposed; and, it is capable of optimizing energy consumption and throughput rate, as well as reducing delay. The simulation results are indicative of better performance of proposed method, compared to IEEE 802.15.4 Standard.
[1] Heinzelman, W. B., Chandrakasan, A. P., & Balakrishnan, H. (2002). An application-specific protocol architecture for wireless microsensor networks. IEEE Transactions on wireless communications, 1(4), 660-670.
[2] Akkaya, K., & Younis, M. (2005). A survey on routing protocols for wireless sensor networks. Ad hoc networks, 3(3), 325-349.
[3] Younis, M., Youssef, M., & Arisha, K. (2003). Energy-aware management for cluster-based sensor networks. Computer networks, 43(5), 649-668.
[4] Dasgupta, K., Kalpakis, K., & Namjoshi, P. (2003, March). An efficient clustering-based heuristic for data gathering and aggregation in sensor networks. In 2003 IEEE Wireless Communications and Networking, 2003. WCNC 2003. (Vol. 3, pp. 1948-1953). IEEE.
[5] Kwon, T., & Gerla, M. (1999, November). Clustering with power control. In MILCOM (Vol. 2, pp. 1424-1428).
[6] Zeng, B., & Dong, Y. (2016). An improved harmony search based energy-efficient routing algorithm for wireless sensor networks. Applied Soft Computing, 41, 135-147.
[7] Gajjar, S., Sarkar, M., & Dasgupta, K. (2016). FAMACROW: Fuzzy and ant colony optimization based combined mac, routing, and unequal clustering cross-layer protocol for wireless sensor networks. Applied Soft Computing, 43, 235-247.
[8] An, J., Qi, L., Gui, X., & Peng, Z. (2017). Joint design of hierarchical topology control and routing design for heterogeneous wireless sensor networks. Computer Standards & Interfaces, 51, 63-70.
[9] Ardakani, S. P., Padget, J., & De Vos, M. (2016). CBA: A cluster-based client/server data aggregation routing protocol. Ad Hoc Networks, 50, 68-87.
[10] Meng, X., Shi, X., Wang, Z., Wu, S., & Li, C. (2016). A grid-based reliable routing protocol for wireless sensor networks with randomly distributed clusters. Ad Hoc Networks, 51, 47-61.
[11] Mohemed, R. E., Saleh, A. I., Abdelrazzak, M., & Samra, A. S. (2017). Energy-efficient routing protocols for solving energy hole problem in wireless sensor networks. Computer Networks, 114, 51-66.
[12] Zahedi, Z. M., Akbari, R., Shokouhifar, M., Safaei, F., & Jalali, A. (2016). Swarm intelligence based fuzzy routing protocol for clustered wireless sensor networks. Expert Systems with Applications, 55, 313-328.
[13] Li, C., Bai, J., Gu, J., Yan, X., & Luo, Y. (2018). Clustering routing based on mixed integer programming for heterogeneous wireless sensor networks. Ad Hoc Networks, 72, 81-90.
[14] Liu, T., Li, Q., & Liang, P. (2012). An energy-balancing clustering approach for gradient-based routing in wireless sensor networks. Computer Communications, 35(17), 2150-2161.
[15] Ducrocq, T., Hauspie, M., & Mitton, N. (2013). Balancing energy consumption in clustered wireless sensor networks. ISRN Sensor Networks, 2013.
[16] Banimelhem, O., & Khasawneh, S. (2012). GMCAR: Grid-based multipath with congestion avoidance routing protocol in wireless sensor networks. Ad Hoc Networks, 10(7), 1346-1361.
[17] Bozorgi, S. M., Rostami, A. S., Hosseinabadi, A. A. R., & Balas, V. E. (2017). A new clustering protocol for energy harvesting-wireless sensor networks Computers & Electrical Engineering., 64, 233-247.
