Abstract
Without congestion control techniques specifically designed for sensor network applications, the system may not function properly due to data transmission failure. Moreover, most many-to-one communication schemes adopted by sensor network applications cause a practical congestion problem called the funneling effect. With this problem, the hottest area is confined to the connection between the sink and its neighbors. In order to solve the bottleneck problem, we propose a congestion-control technique which uses adaptive time-slot scheduling and a service-differentiated technique. The simulation results show that the proposed method outperforms the conventional technique.
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References
Akylidiz, I.F., Su, W., Sankarasubaramaniam, Y., Cayrici, E.: A Survey on Sensor Networks. IEEE Communication Magazine 40, 102–114 (2002)
Tilak, S., Abu-Ghazaleh, N.B., Heinzelman, W.: Infrastructure Tradeoffs for Sensor Networks. In: The 1st ACM International Workshop on Wireless Sensor Networks and Applications (WSNA), Atlanta, pp. 49–58 (2002)
Jung, W., Shin, S., Pink, C.S., Cha, H.: Reducing Congestion in Real-Time Multi-party- tracking Sensor Network Applications. In: The 1st International Workshop on RFID and Ubiquitous Sensor Network, Nagasaki, pp. 1191–1200 (2005)
Wan, C., Eisenman, S.B., Campbell, A.T.: CODA: Congestion Detection and Avoidance in Sensor Networks. In: Proc. of ACM SenSys 2003, Los Angeles, pp. 266–279 (2003)
Sankarasubramaniam, Y., Akan, O.B., Akyildiz, I.F.: ESRT: Event-to-Sink Reliable Transport in Wireless Sensor Networks. In: Proc. of MobiHoc 2003, Annapolis, Maryland, pp. 177–189 (2003)
Hull, B., Jamieson, K., Balakrishnan, H.: Mitigating Congestion in Wireless Sensor Networks. In: Proc. of ACM SenSys 2004, Baltimore, pp. 134–147 (2004)
Kang, J., Zhang, Y., Nath, B., Yu, S.: Adaptive Resource Control Scheme to Alleviate Congestion Control in Sensor Networks. In: Proc. of the 1st Workshop on Broadcast Advanced Sensor Networks (BASENETS), San Jose (2004)
Ee, C.T., Bajcsy, R.: Congestion Control and Fairness for Many-to-one routing in Sensor Networks. In: Proc. of ACM SenSys 2004, Baltimore, pp. 148–161 (2004)
Wan, C., Eisenman, S.B., Campbell, A.T., Crowcroft, J.: Siphon: Overload Traffic Management Using Multi-radio Virtual Sinks in Sensor Networks. In: Proc. of ACM SenSys 2005, San Diego, pp. 116–129 (2005)
Karenos, K., Kalogeraki, V., Krishnamurthy, S.V.: Cluster-Based Efficient Routing in Wireless Sensor Networks. In: IEEE Workshop on Embedded Networked Sensor (EmNets 2005), Sydney, pp. 107–114 (2005)
MoteIV. Tmote-sky-datasheet, http://www.moteiv.com/products/docs/tmote-sky-datasheet.pdf
Levis, P., Madden, S., Polastre, J., Szewczyk, R., Whitehouse, K., Woo, A., Fay, D., Hill, J., Welsh, M., Brewer, E., Culler, D.: TinyOS: An Operating System for Sensor Networks. In: Ambient Intelligence, pp. 115–148. Springer, Berlin (2005)
Levis, P., Lee, N., Welch, M., Culler, D.: TOSSIM: Accurate and Scalable Simulation of Entire TinyOS Applications. In: ACM SenSys, pp. 126–137 (2003)
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Moon, S., Lee, S., Cha, H. (2006). A Congestion Control Technique for the Near-Sink Nodes in Wireless Sensor Networks. In: Ma, J., Jin, H., Yang, L.T., Tsai, J.JP. (eds) Ubiquitous Intelligence and Computing. UIC 2006. Lecture Notes in Computer Science, vol 4159. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11833529_50
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DOI: https://doi.org/10.1007/11833529_50
Publisher Name: Springer, Berlin, Heidelberg
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