Energy-aware routing in wireless sensor networks: A complex networks based approach

被引:0
作者
Li X.H. [1 ]
Long D. [1 ]
Ding Y.M. [2 ]
机构
[1] College of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan
[2] College of Computer and Communication Engineering, Tianjin University of Technology, Tianjin
关键词
Betweenness centrality; Complex networks; Energy-aware routing; Node degree; Wireless sensor networks;
D O I
10.1504/IJWMC.2016.081158
中图分类号
学科分类号
摘要
Wireless Sensor Networks (WSNs) have practical application in various fields. Routing in WSNs focuses on reduction of energy consumption and extension of the network lifetime owing to the limited energy, storage space and computing ability. In recent years, complex network-based approaches, which attempt to exploit the structure of WSNs to make better routing decision, are becoming increasingly popular. Since data transmission in WSNs follows a multi-hop pattern, the selection of the best forwarding sensor node is very important in routing. In order to let all sensor nodes take part in routing as evenly as possible and extend the network lifetime of WSNs, an energy-aware routing strategy is proposed with the aid of complex network theory. The proposed routing algorithm introduces node degree deviation as an indicator of high- or low-degree nodes, and adopts a combination of the distance and consumed energy as the forwarding criterion. By shifting traffic from high-degree to low-degree nodes, the proposed routing algorithm extends the network lifetime and balances the energy consumption between the two node types. Simulation results show that the proposed algorithm dramatically extends the network lifetime and balances the network energy consumption compared with local betweenness centrality-based energy-aware routing algorithm and the shortest path routing algorithm. Copyright © 2016 Inderscience Enterprises Ltd.
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页码:182 / 189
页数:7
相关论文
共 23 条
[1]  
Adnan M.A., Razzaque M.A., Ahmed I., Isnin I.F., Bio-mimic optimization strategies in wireless sensor networks: A survey, Sensors, 14, 1, pp. 299-345, (2014)
[2]  
Albatha J., Thakurb M., Madriaa S., Energy constraint clustering algorithms for wireless sensor networks, Ad Hoc Networks, 11, 8, pp. 2512-2525, (2013)
[3]  
Anastasi G., Conti M., Francesco M.D., Passarella A., Energy conservation in wireless sensor networks: A survey, Ad Hoc Networks, 7, 3, pp. 537-568, (2009)
[4]  
Barabasi A.L., Albert R., Emergence of scaling in random networks, Science, 286, 5439, pp. 509-512, (1999)
[5]  
Huang H., Hu G., Yu F., Energy-aware geographic routing in wireless sensor networks with anchor nodes, International Journal of Communication Systems, 26, 1, pp. 100-113, (2013)
[6]  
Idzikowski F., Bonetto E., Chiaraviglio L., Cianfrani A., Coiro A., Dugue R., Trend in energy-aware adaptive routing solutions, IEEE Communications Magazine, 51, 11, pp. 94-104, (2013)
[7]  
Ishmanov F., Saeed Malik A., Kim S.W., Energy consumption balancing ECB issues and mechanisms in wireless sensor networks (WSNs): A comprehensive overview, European Transactions on Telecommunications, 22, 4, pp. 151-167, (2011)
[8]  
Jian Y., Liu E., Zhang Z., Qu X., Wang R., Zhao S., Liu F., Percolation and scale-free connectivity for wireless sensor networks, IEEE Communications Letters, Vo., 19, 4, pp. 625-628, (2015)
[9]  
Jiang Z.-Y., Ma J.-F., Jing X., Enhancing traffic capacity of scale-free networks by employing hybrid routing strategy, Physica A: Statistical Mechanics and Its Applications, 422, pp. 181-186, (2015)
[10]  
Larios D.F., Barbancho J., Rodriguez G., Sevillano J.L., Molina F.J., Energy efficient wireless sensor network communications based on computational intelligent data fusion for environmental monitoring, IET Communications, 6, 14, pp. 2189-2197, (2012)