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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 3, 2017.
Abstract: In recent past, the current Internet architecture has many challenges in supporting the magnificent network traffic. Among the various that affect the quality of communication in the massive architecture the challenge in maintaining congestion free flow of traffic is one of the major concerns. In this paper, we propose a novel technique to address this issue using cross layer paradigm based on stochastic approach with extended markovian model. The cross layer approach will bridge the physical layer, link layer, network layer and transport layer to control congestion. The resource provisioning operation will be carried out over link layer and the mechanism of exploring the congestion using stochastic approach will be implemented over the network layer. The Markov modeling is adopted to identify the best routes amidst of highly congested paths and it is carried out at the transport layer. An analytical research methodology will be adopted to prove that it is feasible to develop a technique that can identify the origination point of congestion and share the same with the entire network. It is found that this approach for congestion control is effective with respect to end to end delay, packet delivery ratio and processing time.
Selvarani R and Vinodha K, “Congestion Control using Cross layer and Stochastic Approach in Distributed Networks” International Journal of Advanced Computer Science and Applications(IJACSA), 8(3), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080328
@article{R2017,
title = {Congestion Control using Cross layer and Stochastic Approach in Distributed Networks},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.080328},
url = {http://dx.doi.org/10.14569/IJACSA.2017.080328},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {3},
author = {Selvarani R and Vinodha K}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.