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CLC number: TP393

On-line Access: 2014-03-05

Received: 2013-06-28

Revision Accepted: 2013-12-06

Crosschecked: 2014-02-19

Cited: 3

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Citations:  Bibtex RefMan EndNote GB/T7714

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Journal of Zhejiang University SCIENCE C 2014 Vol.15 No.3 P.187-199

10.1631/jzus.C1300175


A probabilistic approach for predictive congestion control in wireless sensor networks


Author(s):  R. Annie Uthra, S. V. Kasmir Raja, A. Jeyasekar, Anthony J. Lattanze

Affiliation(s):  Department of Computer Science and Engineering, SRM University, Tamil Nadu 6003203, India; more

Corresponding email(s):   annieuthra@yahoo.com, svkr@yahoo.com, ajeyasekar@yahoo.com, lattanze@cs.cmu.edu

Key Words:  Congestion, Rate allocation, Congestion control, Packet loss, Back-off interval, Rate control


R. Annie Uthra, S. V. Kasmir Raja, A. Jeyasekar, Anthony J. Lattanze. A probabilistic approach for predictive congestion control in wireless sensor networks[J]. Journal of Zhejiang University Science C, 2014, 15(3): 187-199.

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author="R. Annie Uthra, S. V. Kasmir Raja, A. Jeyasekar, Anthony J. Lattanze",
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volume="15",
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pages="187-199",
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publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.C1300175"
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%A R. Annie Uthra
%A S. V. Kasmir Raja
%A A. Jeyasekar
%A Anthony J. Lattanze
%J Journal of Zhejiang University SCIENCE C
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%I Zhejiang University Press & Springer
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T1 - A probabilistic approach for predictive congestion control in wireless sensor networks
A1 - R. Annie Uthra
A1 - S. V. Kasmir Raja
A1 - A. Jeyasekar
A1 - Anthony J. Lattanze
J0 - Journal of Zhejiang University Science C
VL - 15
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.C1300175


Abstract: 
Any node in a wireless sensor network is a resource constrained device in terms of memory, bandwidth, and energy, which leads to a large number of packet drops, low throughput, and significant waste of energy due to retransmission. This paper presents a new approach for predicting congestion using a probabilistic method and controlling congestion using new rate control methods. The probabilistic approach used for prediction of the occurrence of congestion in a node is developed using data traffic and buffer occupancy. The rate control method uses a back-off selection scheme and also rate allocation schemes, namely rate regulation (RRG) and split protocol (SP), to improve throughput and reduce packet drop. A back-off interval selection scheme is introduced in combination with rate reduction (RR) and RRG. The back-off interval selection scheme considers channel state and collision-free transmission to prevent congestion. Simulations were conducted and the results were compared with those of decentralized predictive congestion control (DPCC) and adaptive duty-cycle based congestion control (ADCC). The results showed that the proposed method reduces congestion and improves performance.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

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