Channel Occupancy Ratio Based TCP Congestion Control in Adhoc Networks
R. Jayaraj1, T.Suresh2
1R. Jayaraj , Assistant Professor, Department of CSE, Christ Institute of Technology, Pondicherry, India ,
2T.Suresh, Assistant Professor, Department of Computer Science and Engineering, Annamalai University, TamilNadu, India
Manuscript received on 01 August 2019 | Revised Manuscript received on 05 August 2019 | Manuscript published on 30 August 2019 | PP: 4427-4532 | Volume-8 Issue-10, August 2019 | Retrieval Number: J10790881019/19©BEIESP | DOI: 10.35940/ijitee.I1079.0881019
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Wireless Network is been used widely in the recent years due to its low-cost nature. More number of real time applications have been used by varied segments of users across the world. The advancements in the mobile technology have made ad hoc networks as important and active field of communication and networks. Most of the time the network cannot handle the traffic in the network which ultimately affects the Quality of Service (QoS). The conventional Transmission Control Protocol (TCP) cannot handle this huge volume of traffic and control the congestion in the network. This issue in the wireless network is been addressed by various researchers in the world but still the scope and need for improvements are more. This paper analyzes many TCP congestion control mechanisms and proposes an efficient approach for congestion control by estimating Channel Occupancy Ratio (COR). The COR is estimated based on machine learning algorithm which is trained using the historical data extracted from MAC layer. This cross layer based approach is found to be more efficient when compared to other methods proposed in the literature.
Keywords: Quality of service, transmission control protocol, channel occupancy ratio, machine learning.
Scope of the Article: Software & System Quality of Service