A probabilistic approach for predictive congestion control in wireless sensor networks

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...

Full description

Saved in:
Bibliographic Details
Published in:Frontiers of information technology & electronic engineering 2014-03, Vol.15 (3), p.187-199
Main Authors: Uthra, R. Annie, Kasmir Raja, S. V., Jeyasekar, A., Lattanze, Anthony J.
Format: Article
Language:English
Subjects:
Adaptive control
Channels
Collision avoidance
Communications Engineering
Computer Hardware
Computer Science
Computer Systems Organization and Communication Networks
Congestion
Control methods
Devices
Electrical Engineering
Electronics and Microelectronics
Instrumentation
Intervals
Networks
Predictive control
Probabilistic methods
Probability theory
Remote sensors
Traffic congestion
Wireless networks
Wireless sensor networks
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:1869-1951
2095-9184
1869-196X
2095-9230
DOI:10.1631/jzus.C1300175