Abstract
Available congestion control schemes, for example transport control protocol (TCP), when applied to wireless networks results in a large number of packet drops, unfairness with a significant amount of wasted energy due to retransmissions. To fully utilize the hop by hop feedback information, a suite of novel, decentralized, predictive congestion control schemes are proposed for wireless sensor networks in concert with distributed power control (DPC). Besides providing energy efficient solution, embedded channel estimator in DPC predicts the channel quality. By using the channel quality and node queue utilizations, the onset of network congestion is predicted and congestion control is initiated. Stability of the hop by hop congestion control is demonstrated by using a Lyapunov-based approach. Simulation results show that the proposed schemes result in fewer dropped packets than a network without the hop-by-hop congestion control, better fairness index and network efficiency, higher aggregate throughput, and smaller end-to-end delays over the other available schemes like IEEE 802.11 protocol.
Recommended Citation
M. J. Zawodniok and J. Sarangapani, "Predictive Congestion Control MAC Protocol for Wireless Sensor Networks," Proceedings of the International Conference on Control and Automation, 2005. ICCA '05, Institute of Electrical and Electronics Engineers (IEEE), Jan 2005.
The definitive version is available at https://doi.org/10.1109/ICCA.2005.1528114
Meeting Name
International Conference on Control and Automation, 2005. ICCA '05
Department(s)
Electrical and Computer Engineering
Second Department
Computer Science
Sponsor(s)
National Science Foundation (U.S.)
Keywords and Phrases
Lyapunov Methods; Access Protocols; Channel Estimation; Wireless Sensor Networks; Predictive control; Queuing theory
Document Type
Article - Conference proceedings
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2005 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Jan 2005
Included in
Computer Sciences Commons, Electrical and Computer Engineering Commons, Operations Research, Systems Engineering and Industrial Engineering Commons