Maximum lifetime genetic routing algorithm in wireless sensor networks

被引：6

作者：

Tang W. ^{[1
]}

Guo W. ^{[1
]}

机构：

[1] National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China

来源：

Ruan Jian Xue Bao/Journal of Software | 2010年 / 21卷 / 07期

关键词：

Genetic algorithm; Gradient algorithm; Network lifetime; Routing algorithm; Wireless sensor network;

D O I：

10.3724/SP.J.1001.2010.03601

中图分类号：

学科分类号：

摘要：

Wireless sensor networks (WSNs) consist of low-power and energy-constrained sensor nodes, and a fundamental challenge in the design of such networks is to maximize the network lifetime. In WSNs, data collected by adjacent sensor nodes usually have spatial-temporal correlations, and data aggregation technique is often used as an effective approach to remove data redundancy. Efficient usage of data aggregation technique can significantly reduce the amount of data delivery, lower the cost of overall power consumption of the network, hence increase the network lifetime. This paper studies the optimal data delivery in WSNs that takes advantage of data aggregation and nodal power control, and presents a novel routing algorithm that maximizes the network lifetime. The algorithm uses genetic algorithm (GA) to achieve an optimal selection of aggregation points, and gradient algorithm is also used to further optimize the result. The algorithm balances the power consumption of sensor nodes, and maximizes the network lifetime. Numerical results show that the proposed approach has substantially improved the network lifetime. © by Institute of Software, the Chinese Academy of Sciences. All rights reserved.

引用

页码：1646 / 1656

页数：10

共 22 条

[1]

Chong C.Y., Kumar S.P., Sensor networks: Evolution, opportunities, and challenges, Proc. of the IEEE, 91, 8, pp. 1247-1256, (2003)

[2]

Chen Y., Zhao Q., On the lifetime of wireless sensor networks, IEEE Communications Letters, 9, 11, pp. 976-978, (2005)

[3]

Ok C., Mitra P., Lee S., Kumara S., Distributed energy-adaptive routing for wireless sensor networks, Proc. of the IEEE Conf. on Automation Science and Engineering, pp. 905-910, (2007)

[4]

Fan Z., Chen Y.P., Zhou H., An aggregator deployment protocol for energy conservation in wireless sensor networks, Proc. of the IEEE Int'l Conf. on Networking: Sensing and Control, pp. 1019-1024, (2008)

[5]

Pantazis N.A., Vergados D.D., A survey on power control issues in wireless sensor networks, IEEE Communications Surveys & Tutorials, 9, 4, pp. 86-107, (2007)

[6]

Simic L., Berber S.M., Sowerby K.W., Partner choice and power allocation for energy efficient cooperation in wireless sensor networks, Proc. of the IEEE Int'l Conf. on Communications, pp. 4255-4260, (2008)

[7]

Panichpapiboon S., Ferrari G., Tonguz O.K., Optimal transmit power in wireless sensor networks, IEEE Trans. on Mobile Computing, 5, 10, pp. 1432-1447, (2006)

[8]

Krishnamachari B., Estrin D., Wicker S., The impact of data aggregation in wireless sensor networks, Proc. of the Int'l Conf. on Distributed Computing Systems Workshops, pp. 575-578, (2002)

[9]

Oh H., Chae K., An energy-efficient sensor routing with low latency, scalability in wireless sensor networks, Proc. of the Int'l Conf. on Multimedia and Ubiquitous Engineering, pp. 147-152, (2007)

[10]

Misra R., Mandal C., Ant-Aggregation: Ant colony algorithm for optimal data aggregation in wireless sensor networks, Proc. of the IFIP Int'l Conf. on Wireless and Optical Communications Networks, (2006)

← 1 2 3 →