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Performance Evaluation of Mobile Base Station under different Network Sizes on Cluster-Based Wireless Sensor Networks

Kadir Tohma*, İpek Abasıkeleş Turgut, Cuma Celal Korkmaz, Yakup Kutlu

DOI: 10.28978/nesciences.286025

Abstract

The position of the base station (BS) in wireless sensor networks (WSNs) has a significant impact on network lifetime. This paper suggests a mobile BS positioning algorithm for cluster-based WSNs, which considers both the location and the remaining energy level of the cluster heads in the network and evaluate the performance of the algorithm under different values of network sizes, including 100m x 100m, 200m x 200m and 300m x 300m. Simulations are conducted by using OMNeT++ and proposed method is compared with two different static BS positions, including central and external, on HEED protocol. The results show that mobile BS performs better than both central and external BS positions under all network sizes. Besides, the performance difference between the proposed method and the others increases as the size of the network increases, which demonstrates that the proposed mobile BS positioning also provides scalability.

Keywords

Wireless Sensor Networks, Dynamic Base Station, HEED

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References

• AbasıkeleÅŸ-Turgut, I. (2016). The Effect of the Position of BS and the Size of Network on the Decision of Implementing a Centralized or a Distributed Clustering in WSNs. Journal of Advances in Computer Networks (JACN), Vol.4, Issue 1, pp. 46-51, ISSN: 1793-8244.
• Cayirpunar, O., Urtis, E. K. & Tavli, B. (2013). Mobile base station position optimization for network lifetime maximization in wireless sensor networks. In Signal Processing and Communications Applications Conference (SIU), 21st (pp. 1-4). IEEE.
• Heinzelman, W. R., Chandrakasan, A. & Balakrishnan, H. (2000). Energy-efficient communication protocol for wireless microsensor networks. In System sciences Proceedings of the 33rd annual Hawaii international conference on (pp. 10-pp). IEEE.
• Liang, W., Luo, J. & Xu, X. (2010). Prolonging network lifetime via a controlled mobile sink in wireless sensor networks. In Global Telecommunications Conference, IEEE (pp. 1-6). IEEE.
• Luo, J. & Hubaux, J. P. (2005). Joint mobility and routing for lifetime elongation in wireless sensor networks. In INFOCOM 2005, 24th annual joint conference of the IEEE computer and communications societies. Proceedings IEEE (Vol. 3, pp. 1735-1746). IEEE.
• Mollanejad, A., Khanli, L. M. & Zeynali, M. (2010) DBSR: Dynamic base station Repositioning using Genetic algorithm in wireless sensor network. Computer Engineering and Applications (ICCEA), Second International Conference on IEEE.
• Salim, F. A. & Badran, A. A. (2015). Impact of using Mobile Sink on Hierarchical Routing Protocols for Wireless Sensor Networks. International Journal of Advanced Science and Technology, 77, 37-48.
• Tohma, K., Aydin, M. N. & AbasıkeleÅŸ-Turgut, I. (2015). Improving the LEACH protocol on wireless sensor network. In Signal Processing and Communications Applications Conference (SIU), 23th (pp. 240-243). IEEE.
• Tohma, K., AbasıkeleÅŸ-Turgut, I. & Kutlu, Y. (In Press). A Novel Dynamic Base Station Positioning Method For Wireless Sensor Networks. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi (In Press).
• Varga, H. A. (2001). The OMNeT++ discrete event simulation system. In Proceedings of the European simulation multi conference (Vol. 9, No. S 185, p. 65). sn.
• Wu, X. & Chen, G. (2007). Dual-sink: using mobile and static sinks for lifetime improvement in wireless sensor networks. In Computer Communications and Networks. ICCCN 2007. Proceedings of 16th International Conference on (pp. 1297-1302). IEEE.
• Younis, O. & Fahmy, S. (2004). HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. Mobile Computing, IEEE Transactions on, 3(4), 366-379.