Abstract
To maximize network lifetime when node transmission power is fixed in wireless sensor networks, power control routing algorithm for maximizing lifetime (PCRAML) is proposed. The algorithm analyzes the constraint conditions such as node transmission rate constraint, link maximum transmission rate constraint and node energy constraint. Then, network optimization model is established. Subgradient algorithm is used to solve the network optimization model. It can obtain maximum network lifetime and node data transmission rate when node transmission power is determined by genetic algorithm. Genetic algorithm is used to iteratively select, cross and mutate the power populations. Finally node optimal transmission power, maximum network lifetime and optimal routing scheme are obtained. Simulation results show that PCRAML can obtain the optimal scheme of routing and node transmission power, balance network load and maximize network lifetime. Under certain conditions, PCRAML outperforms subgradient algorithms with fixed transmission power.
Keywords
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Akyildiz, I.F., Su, W.L.: A survey on sensor networks. IEEE Communications Magazine 40, 2–116 (2002)
Xu, N., Cassandras, C.G.: A maximum time optimal control approach to routing in sensor networks. In: 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference, Shanghai, P.R. China, pp. 3757–3762 (2009)
Gomez, J., Campbell, A.T.: Variable-range transmission power control in wireless Ad hoc networks. IEEE Transactions on Mobile Computing 6, 87–99 (2007)
Madan, R., Lall, S.: Distributed algorithms for maximum lifetime routing in wireless sensor network. IEEE Transactions on Wireless Communications 5, 2185–2193 (2006)
Gatzianas, M.A., Georgiadis, L.G.: A distributed algorithm for maximum lifetime routing in sensor networks with mobile sink. IEEE Transactions on Wireless Communications 7, 984–994 (2007)
He, Y.F., Lee, I., Guan, L.: Distributed algorithms for network lifetime maximization in wireless visual sensor networks. IEEE Transactions on Circuits and System for Video Technology 19, 704–718 (2009)
Jadbabaie, A., Ozdaglar, A., Zargham, M.: A distributed Newton method for network optimization. In: 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference, Shanghai, P.R. China, pp. 2736–2741 (2009)
Gomez, J., Campbell, A.T.: Variable-range transmission power control in wireless Ad hoc networks. IEEE Transactions on Mobile Computing 6, 87–99 (2007)
Wen, K., Guo, W., Huang, G.J.: A power control algorithm based on position of node in the wireless Ad hoc networks. Journal of Electronics and Information Technology 31, 201–205 (2009)
Kubisch, M., Karl, H., Wolisz, A., et al.: Distributed algorithms for transmission power control in wireless sensor networks. In: Proceedings of IEEE Wireless Communications and Networking Conference, pp. 132–137. IEEE, New Orleans (2003)
Li, L., Halpern, J.Y., Bahl, P., et al.: A cone-based distributed topology control algorithm for wireless multi-hop networks. IEEE/ACM Transactions on Networking 13, 147–159 (2005)
Chen, Y.R., Yu, L., Dong, Q.F., Hong, Z.: Power control in wireless sensor network based on nearest-neighbor algorithm. Journal of Zhejiang University (Engineering Science) 44, 1321–1326 (2010)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chen, Y., Hu, X., Yang, H., Ge, L. (2013). Power Control Routing Algorithm for Maximizing Lifetime in Wireless Sensor Networks. In: Jin, D., Lin, S. (eds) Advances in Mechanical and Electronic Engineering. Lecture Notes in Electrical Engineering, vol 178. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31528-2_22
Download citation
DOI: https://doi.org/10.1007/978-3-642-31528-2_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31527-5
Online ISBN: 978-3-642-31528-2
eBook Packages: EngineeringEngineering (R0)