Performance Analysis of Congestion Reduction Routing in Wireless Sensor Networks
T. V.P. Sundararajan, Thiyaneswaran Manoharan and Abinaya Rajendran
DOI : 10.3844/jcssp.2011.1011.1019
Journal of Computer Science
Volume 7, Issue 7
Problem statement: Data generated in wireless sensor networks may not all be alike: some data may be more important than others and hence may have different delivery requirements, To solve this problem addressed a differentiated data delivery in the presence of congestion in wireless sensor networks and proposed a class of algorithms that enforce differentiated routing based on the congested areas of a network and data priority. Approach: The basic protocol, called Congestion-Reduction Routing (CRR), discovers the congested zone of the network that exists between high-priority data sources and the data sink and using simple forwarding rules, dedicates this portion of the network to forwarding primarily high-priority traffic. Since CRR requires some overhead for establishing the high-priority routing zone, it is unsuitable for highly mobile data sources. To accommodate all these things defined MAC-Enhanced CRR (MCRR), which includes MAC-layer enhancements and a protocol for forming high-priority paths on the fly for each burst of data. MCRR effectively handles the mobility of high-priority data sources, at the expense of degrading the performance of low-priority traffic and presented an extensive simulation results for CRR and MCRR and an implementation of MCRR on a 48-node testbed. Results: Proposed CRR and MCRR algorithms were implemented by using NS2 simulator and the QOS parameters on throughput, packet delivery ratio, delay and energy. All parameters were analyzed and compared with basic AODV mechanism. Conclusion/Recommendations: CRR is better suited for static networks with long-duration HP floods. For bursty HP traffic and/or mobile HP sources, MCRR is a better fit. Because of the lower delay, CRR and its variants appear suitable to real-time data delivery.
© 2011 T. V.P. Sundararajan, Thiyaneswaran Manoharan and Abinaya Rajendran. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.