Abstract
Available congestion control schemes, for example transport control protocol (TCP), when applied to wireless networks, result in a large number of packet drops, unfair scenarios and low throughputs with a significant amount of wasted energy due to retransmissions. To fully utilize the hop by hop feedback information, this paper presents a novel, decentralized, predictive congestion control (DPCC) for wireless sensor networks (WSN). The DPCC consists of an adaptive flow and adaptive back-off interval selection schemes that work in concert with energy efficient, distributed power control (DPC). The DPCC detects the onset of congestion using queue utilization and the embedded channel estimator algorithm in DPC that predicts the channel quality. Then, an adaptive flow control scheme selects suitable rate which is enforced by the newly proposed adaptive backoff interval selection scheme. An optional adaptive scheduling scheme updates weights associated with each packet to guarantee the weighted fairness during congestion. Closed-loop stability of the proposed hop-by-hop congestion control is demonstrated by using the Lyapunov-based approach. Simulation results show that the DPCC reduces congestion and improves performance over congestion detection and avoidance (CODA) [3] and IEEE 802.11 protocols.
Recommended Citation
M. J. Zawodniok and J. Sarangapani, "Predictive Congestion Control Protocol for Wireless Sensor Networks," IEEE Transactions on Wireless Communications, Institute of Electrical and Electronics Engineers (IEEE), Nov 2007.
The definitive version is available at https://doi.org/10.1109/TWC.2007.051035
Department(s)
Electrical and Computer Engineering
Second Department
Computer Science
Keywords and Phrases
Lyapunov Stability; Congestion Control; Control-Lyapunov Functions; Wireless Sensor Network
International Standard Serial Number (ISSN)
1536-1276
Document Type
Article - Journal
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2007 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Nov 2007
Included in
Computer Sciences Commons, Electrical and Computer Engineering Commons, Operations Research, Systems Engineering and Industrial Engineering Commons