On Base Station Localization in Wireless Sensor Networks

Öz

Wireless sensor networks (WSN) has been a prominent topic for the past decade. WSN consist of multiple sensor nodes, which collect and convey data to the base station(s). Sensor nodes are expected to run on batteries, and it makes energy the scarce resource for sensor nodes. Energy expenditure of a sensor node mainly depends on data transmission, which is exponentially affected by transmission distance. Consequently, if sensor nodes forward their data to the base station directly, distant sensor nodes will exhaust quickly. On contrary, minimization of transmission distance for each sensor node, i.e., each node transmits its data to the closest sensor node on its path to the base station, depletes the energy of sensor nodes that are closer to the base station fast.  As a result, the flow balance in the network must be optimized. In this study, we investigate the effect of optimization of the base station location along with flow balance optimization. For this purpose, we compare five different localization methods on different topologies; three statically located linear programming approaches, a dynamically located nonlinear programming approach and a heuristic based hybrid approach. Experimental results indicate that lifetime improvement of up to 42% is possible in selected scenarios. 

Anahtar Kelimeler

• lifetime optimization,linear programming,wireless sensor networks

Kaynakça

1. M. A. Gray and P. N. Scherer, “Web services framework for wireless sensor networks,” in SERVICE COMPUTATION 2014: The Sixth International Conferences on Advanced Service Computing, IARIA, 2014, pp. 15–23.
2. S. Newberry and G. S. Gupta, “Wireless sensor based home automation as an educational springboard,” in Sensors Applications Symposium (SAS), 2015 IEEE. IEEE, 2015, pp. 1–6.
3. B. Rashid and M. H. Rehmani, “Applications of wireless sensor networks for urban areas: A survey,” Journal of Network and Computer Applications, vol. 60, pp. 192–219, 2016.
4. Z. Cheng, M. Perillo, and W. B. Heinzelman, “General network lifetime and cost models for evaluating sensor network deployment strategies,” IEEE Transactions on mobile computing, vol. 7, no. 4, pp. 484–497, 2008.
5. H. Subir, G. Amrita, S. Sanjib, D. Avishek, and D. Sipra, “A lifetime enhancing node deployment strategy in WSN,” in International Conference on Future Generation Information Technology. Springer, 2009, pp. 295–307.
6. X. Liu, “Sensor deployment of wireless sensor networks based on ant colony optimization with three classes of ant transitions,” IEEE Communications Letters, vol. 16, no. 10, pp. 1604–1607, 2012.
7. S. Singh, S. Chand, R. Kumar, and B. Kumar, “Optimal sensor deployment for WSNs in grid environment,” Electronics Letters, vol. 49, no. 16, pp. 1040–1041, 2013.
8. A. Efrat, S. Har-Peled, and J. S. Mitchell, “Approximation algorithms for two optimal location problems in sensor networks,” in Broadband networks, 2005. BroadNets 2005. 2nd international conference on. IEEE, 2005, pp. 714–723.

9. S. R. Gandham, M. Dawande, R. Prakash, and S. Venkatesan, “Energy efficient schemes for wireless sensor networks with multiple mobile base stations,” in Global telecommunications conference, 2003. GLOBECOM’03. IEEE, vol. 1. IEEE, 2003, pp. 377–381.
10. E. I. Oyman and C. Ersoy, “Multiple sink network design problem in large scale wireless sensor networks,” in Communications, 2004 IEEE International Conference on, vol. 6. IEEE, 2004, pp. 3663–3667.
11. H. Kim, Y. Seok, N. Choi, Y. Choi, and T. Kwon, “Optimal multi-sink positioning and energy-efficient routing in wireless sensor networks,” in International Conference on Information Networking. Springer, 2005, pp. 264–274.
12. E. Güney, N. Aras, İ. K. Altınel, and C. Ersoy, “Efficient integer programming formulations for optimum sink location and routing in heterogeneous wireless sensor networks,” Computer Networks, vol. 54, no. 11, pp. 1805–1822, 2010.
13. E. Güney, N. Aras, İ. K. Altınel, and C. Ersoy, “Efficient solution techniques for the integrated coverage, sink location and routing problem in wireless sensor networks,” Computers & Operations Research, vol. 39, no. 7, pp. 1530–1539, 2012.
14. R. K. Tripathi, Y. N. Singh, and N. K. Verma, “Two-tiered wireless sensor networks - base station optimal positioning case study,” IET Wireless Sensor Systems, vol. 2, no. 4, pp. 351–360, 2012.
15. M. M. Fouad, V. Snasel, and A. E. Hassanien, “Energy-aware sink node localization algorithm for wireless sensor networks,” International Journal of Distributed Sensor Networks, vol. 11, no. 7, 2015.
16. G. D. Corporation, “General Algebraic Modeling System (GAMS) Release 24.2.1,” Washington, DC, USA, 2013. [Online]. Available: http://www.gams.com/