A Cross-Layer Congestion Control Algorithm Based on Traffic Prediction in Wireless Sensor Networks


Article Preview

Congestion in wireless sensor networks can affect the networks performance seriously,not only it has impact on data transmission and the quality of service, but also wastes energy and shortens the network lifetime. Aiming at this issue, this paper proposed a cross-layer congestion control algorithm based on traffic prediction (CCATP), it can take congestion mitigation measures in advance according to the prediction result. CCATP comprises three mechanisms: (i) congestion prediction; (ii) local congestion control mechanism based on backoff time adjustment; (iii) transmission route selection based global congestion control mechanism; Simulation experiment results show that CCATP can reduce the packet loss number and improve the energy efficiency significantly, so as to effectively improve the service performance of network.



Edited by:

Hongyang Zhao, Kun Liu and Xiaoguang Yu




Y. Sun et al., "A Cross-Layer Congestion Control Algorithm Based on Traffic Prediction in Wireless Sensor Networks", Applied Mechanics and Materials, Vols. 397-400, pp. 2641-2646, 2013

Online since:

September 2013





[1] L. Cui, H.L. Ju, Y. Miao, T.P. Li, W. Liu: Computer Research and Development, Vol. 42 (2005), pp.163-174(In Chinese).

[2] Y.P. Zhang, K. Liu, G.X. Wang: Acta Electronica Sinica, Vol. 39 (2011), pp.2258-2262(In Chinese).

[3] L.M. Sun, B. Li, X.Y. Zhou: Research and Development on Computer, Vol. 12 (2008), pp.63-72(In Chinese).

[4] Y. Sankarasubramaniam, O. Akan, and I. Akildiz: IEEE/ACM Transactions on Networking, Vol. 13 (2005), pp.177-188.

[5] C.Y. Wan, S.B. Eisenman, and A.T. Campbell, Congestion Detection and Avoidance in Sensor Networks, Proc. of Sensys (2003), pp.266-279.

[6] C Basaran, K.D. Kang, M.H. Suzer, Hop-by-hop Congestion Control and Load Balancing in Wireless Sensor Networks, Proceeding of LCN (2010), pp.448-455.

DOI: https://doi.org/10.1109/lcn.2010.5735758

[7] G.W. Wu, Y. Zhang: Computer Engineering, Vol. 36 (2010), pp.108-109(In Chinese).

[8] Y. Xu, The Application of ARIMA Model in Chinese Mobile User Prediction, Granular Computing (2010), pp.586-591.