Abstract
Due to the lack of accurate evaluation of the transmission characteristics of the wireless communication links, routing algorithms in wireless sensor networks may result in poor network performance. This paper presents a link quality-based reliable routing algorithm. According to the link qualities evaluated by RSSI, neighbor nodes can be partitioned into different regions. First, based on a realistic link model and test results, an asymmetric link region is indicated, where selecting a neighboring node in this region as the next hop node will greatly degrade the transmission reliability. Based on this, the neighboring area of a node is divided into four regions, that is, connected, transitional, asymmetric, and disconnected regions. Then, route selection ways for different regions are presented, and different priorities of the nodes in different regions to be selected as the next hop node are assigned. Finally, the performance of the RSRE is tested in a real-world test-bed consists of 40 nodes, and compared with the Min-hop routing algorithm and the ETX based routing algorithm. The results show that the RSRE has better data transmission reliability, and hop distribution.
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References
Couto DSJD, Aguayo D, Bicket J, Morris R (2003) A high-throughput path metric for multihop wireless routing. In: Proceedings of the 9th annual international conference on mobile computing and networking (MobiCom 03). ACM, New York, pp 134–146
Kotz D, Newport C, Elliott C (2003) The mistaken axioms of wireless-network research. Technical Report TR2003-467, Department of Computer Science, Dartmouth College
Xu Y, Lee WC (2006) Exploring spatial correlation for link quality estimation in wireless sensor networks. In: Proceedings of the 4th annual IEEE international conference on pervasive computing and communication (PERCOM 06). IEEE Computer Society, Los Alamitos, pp 200–211
Kim KH, Shin KG (2006) On accurate measurement of link quality in multi-hop wireless mesh networks. In: Proceedings of the 12th annual international conference on mobile computing and networking (MobiCom 06). ACM, New York, pp 38–49
Lal D, Manjeshwar A, Herrmann F (2003) Measurement and characterization of link quality metrics in energy constrained wireless sensor networks. In: Proceedings of the IEEE global telecommunications conference (Globecom 03). IEEE, San Francisco, pp 446–452
Ganesan D, Krishnamachari B, Woo A, Culler D, Estrin D, Wicker S (2002) Complex behavior at scale: an experimental study of low-power wireless sensor networks. UCLA CS Technical Report UCLA/CSD-TR 02-0013
Zhao J, Govindan R (2003) Understanding packet delivery performance in dense wireless sensor networks. In: Sensys 03
Woo A, Tong T, Culler D (2003) Taming the underlying issues for reliable multi-hop routing in sensor networks. In: SenSys 03
Woo A, Culler D (2003) Evaluation of efficient link reliability estimators for low-power wireless networks. Technical report UCB/CSD-03-1270, EECS Department, University of California, Berkeley
Zhang H, Sang L, Arora A (2010) Comparison of data-driven link estimation methods in low-power wireless networks. IEEE Trans Mob Comput 9:1634–1648
Liu H, Li J, Xie Z, Lin S, Whitehouse K, Stankovic JA, Siu D (2010) Automatic and robust breadcrumb system deployment for indoor fire-fighter applications. In: Proceedings of the 8th international conference on mobile systems, applications, and services (MobiSys 10). ACM, New York, pp 21–34
Srinivasan K, Dutta P, Tavakoli A, Levis P (2006) Understanding the causes of packet delivery success and failure in dense wireless sensor networks. In: Proceedings of the 4th international conference on embedded networked sensor systems (SenSys 06). ACM, New York, pp 419–420
Srinivasan K, Dutta P, Tavakoli A, Levis P (2010) An empirical study of low-power wireless. ACM Trans Sens Netw 6:1–49
Wang Y, Martonosi M, Peh L-S (2007) Predicting link quality using supervised learning in wireless sensor networks. ACM SIGMOBILE Mob Comput Commun Rev 11(3):71–83
Senel M, Chintalapudi K, Lal D, Keshavarzian A, Coyle EJ (2007) A Kalman filter based link quality estimation scheme for wireless sensor networks. In: Proceedings of the IEEE global telecommunications conference (GLOBECOM 07). IEEE, New York, pp 875–880
Cerpa A, Wong JL, Potkonjak M, Estrin D (2005) Temporal properties of low power wireless links: modeling and implications on multihop routing. In: Proceedings of the 6th international symposium on mobile ad hoc networking and computing (MobiHoc 05). ACM, New York, pp 414–425
Fonseca R, Gnawali O, Jamieson K, Levis P (2007) Four bit wireless link estimation. In: Proceedings of the 6th international workshop on hot topics in networks (HotNets VI), ACM SIGCOMM
Baccour N, Koubaa A, Youssef H, Ben Jamaa M, Do Rosario D, Alves M, Becker LB (2010) F-LQE: a fuzzy link quality estimator for wireless sensor networks. In: Proceedings of the 7th European conference on wireless sensor networks (EWSN10). Springer, New York, 240–255
Puccinelli D, Haenggi M (2008) DUCHY: double cost field hybrid link estimation for low-power wireless sensor networks. In; Proceedings of the 5th workshop on embedded networked sensors (Hot EmNets08). ACM, New York
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Chen, Y., Yi, W., Wang, B., Qin, F. (2014). A Reliable Routing Algorithm Based on Link Quality Evaluation for Wireless Sensor Networks. In: Wang, X., Cui, L., Guo, Z. (eds) Advanced Technologies in Ad Hoc and Sensor Networks. Lecture Notes in Electrical Engineering, vol 295. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54174-2_10
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DOI: https://doi.org/10.1007/978-3-642-54174-2_10
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