Share This Article:

Topology Control and Routing in Large Scale Wireless Sensor Networks

Abstract Full-Text HTML Download Download as PDF (Size:1072KB) PP. 584-598
DOI: 10.4236/wsn.2010.28070    5,420 Downloads   9,975 Views   Citations

ABSTRACT

In this paper, a two-tiered Wireless Sensor Network (WSN) where nodes are divided into clusters and nodes forward data to base stations through cluster heads is considered. To maximize the network lifetime, two energy efficient approaches are investigated. We first propose an approach that optimally locates the base stations within the network so that the distance between each cluster head and its closest base station is decreased. Then, a routing technique is developed to arrange the communication between cluster heads toward the base stations in order to guaranty that the gathered information effectively and efficiently reach the application. The overall dynamic framework that combines the above two schemes is described and evaluated. The experimental performance evaluation demonstrates the efficacy of topology control as a vital process to maximize the network lifetime of WSNs.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

I. Slama, B. Jouaber and D. Zeghlache, "Topology Control and Routing in Large Scale Wireless Sensor Networks," Wireless Sensor Network, Vol. 2 No. 8, 2010, pp. 584-598. doi: 10.4236/wsn.2010.28070.

References

[1] Y. P. Chen, A. L. Liestman and J. Liu, “A Hierarchical Energy-Efficient Framework for Data Aggregation in Wireless Sensor Networks,” IEEE Transactions on Vehicular Technology, Vol. 55, No. 3, May 2006, pp. 789- 796.
[2] W. Rabiner Heinzelman, A. Chandrakasan and H. Balakrishnan, “Energy-Efficient Communication Protocol for Wireless Microsensor Networks,” Proceedings of the 33rd International Conference on System Sciences, Hawaii, January 2000, pp. 3005-3014.
[3] J. Pan, Y. Hou, L. Cai, Y. Shi and X. Shen, “Topology Control for Wireless Sensor Networks,” Proceeding of the 9th ACM Conference on Mobile Computing and Networking, San Diego, September 2003, pp. 286-299.
[4] C. Chen, J. Ma and K. Yu, “Designing Energy-Efficient Wireless Sensor Networks with Mobile Sinks,” Proceeding of ACM Sensys’06 Workshop WSW, Boulder, October 2006, pp. 1-9.
[5] I.Slama, B. Jouaber and D. Zeghlache, “Routing for Wireless Sensor Networks Lifetime Maximization under Energy Constraints,” The 3rd International Conference on Mobile Technology, Applications and Systems, Bangkok, October 2006, pp. 1-5.
[6] W. Heinzelman, A. Chandrakasan and H. Balakrishnan, “An Application-Specific Protocol Architecture for Wireless Microsensor Networks,” IEEE Transaction in Wireless Communications, Vol. 1, No. 4, October 2002, pp. 660-670.
[7] V. Mhatre, C. Rosenberg, D. Kofman, R. Mazumdar and N. Shroff, “A Minimum Cost Heterogeneous Sensor Network with a Lifetime Constraint,” IEEE Transaction on Mobile Computing, Vol. 4, No. 1, 2005, pp. 4-15.
[8] J. Luo and J.-P. Hubaux, “Joint Mobility and Routing for Lifetime Elongation in Wireless Sensor Networks,” Proceeding of IEEE INFOCOM, Miami, March 2005, pp. 1-10.
[9] Z. M. Wang, S. Basagni, E. Melachrinoudis and C. Petrioli, “Exploiting Sink Mobility for Maximizing Sensor Networks Lifetime,” Proceedings of the 38th Annual Hawaii International Conference on System Sciences, Washington, D.C., January 2005, p. 287.
[10] S. R. Gandham, M. Dawande, R. Prakash and S. Venka- tesan, “Energy Efficient Schemes for Wireless Sensor Networks With Multiple Mobile Base Stations,” Proceeding of IEEE GLOBECOM, San Francisco, 2003, pp. 377-381.
[11] H. Kim, Y. Seok, N. Choi, Y. Choi and T. Kwon, “Optimal Multi-Sink Positioning and Energy-Efficient Routing in Wireless Sensor Networks,” Lecture Notes in Computer Science, Vol. 3391, No. 11, pp. 264-274.
[12] Z. Vincze, K. Fodor, R. Vida and A. Vidacs, “Electrostatic Modelling of Multiple Mobile Sinks in Wireless Sensor Networks,” Proceeding of IFIP Networking Workshop on Performance Control in Wireless Sensor Networks, Coimbra, May 2006, pp. 30-37.
[13] G. Even, J. Naor, S. Rao and B. Schieber, “Fast Approximate Graph Partitioning Algorithms,” Proceeding of the 8th Annual ACM-SIAM Symposium on Discrete Algorithms, New Orleans, 1997, pp. 639-648.
[14] T. Ito, X. Zhou and T. Nishizeki, “Partitioning a Graph of Bounded Tree-Width to Connected Subgraphs of Almost Uniform Size,” Journal of Discrete Algorithms, Vo. 4, No. 1, March 2006, pp. 142-154.
[15] J. Chlebikova, “Approximability of the Maximally Balanced Connected Partition Problem in Graphs,” Information Processing Letters, Vol. 60, 1996, pp. 225-230.
[16] J. Luo, J. Panchard, M. Piorkowski, M. Grosglausser and J-P. Hubaux, “Mobiroute: Routing towards a Mobile Sink for Improving Lifetime in Sensor Networks”, Proceeding of the International Conference on Distributed Computing in Sensor Systems, San Francisco, June 2006.
[17] M. Chatterjee, S. K. Das and D. Turgut, “WCA: A Wei- ghted Clustering Algorithm for Mobile Ad Hoc Networks,” Journal of Cluster Computing, Special Issue on Mobile Ad Hoc Networking, Vol. 5, No. 2, 2002, pp. 193-204.
[18] M. Perillo and W. Heinzelman, “Optimal Sensor Management Under Energy and Reliability Constraints,” Proceedings of the IEEE Wireless Communications and Networking Conference, New Orleans, March 2003.
[19] D. B. Johnson and D. A. Maltz, “Dynamic Source Routing in Ad Hoc Wireless Networks,” Mobile Computing, Vol. 353, No. 5, pp. 153-181.

  
comments powered by Disqus

Copyright © 2019 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.