Channel occupancy ratio based TCP congestion control in adhoc networks

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.