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Most existing traditional congestion control algorithms are difficult to adapt to the highly dynamic link environment of wireless Ad hoc network. In order to solve the above problem, this paper proposed a method of improving the performance of congestion control based on deep reinforcement learning, Enhanced-CC. It conducted a preliminary detection of the congestion window by using the traditional congestion control algorithm. On this basis, the method used deep reinforcement technology to learn the real-time optimal congestion window range of the link. When the congestion window calculated by the traditional congestion control algorithm was too large or too small, the method adjusted the congestion window, so that the sending rate could match the highly dynamic link bandwidth, and the method could improve the transmission performance of the traditional congestion control algorithm. The experimental results show that Enhanced-CC can significantly improve the performance of traditional congestion control algorithms such as BBR, CUBIC, Westwood, Reno, and is superior to the performance of fully learning based congestion control algorithms such as PCC and PCC Vivace, and the combination of deep reinforcement learning and traditional congestion control algorithms such as Orca and DeepCC. [ABSTRACT FROM AUTHOR]

Mobile ad hoc networks (MANETs) are applicable in an infrastructureless environment where the mobile devices act as routers and intermediate nodes are used to transfer segments to their final destination. As Transmission control protocol (TCP) was originated for Internet with fundamentally different properties, faces serious challenges when used in mobile ad hoc networks. TCP functionality degrades, due to special properties of MANET such as route failure because of significant change of network topology and link errors. TCP uses Congestion Control Algorithms; TCP Vegas is one of them which claim to have better throughput comparing with other TCP variants in a wired network. Fairness issues of TCP Variants in MANET including existing routing protocol are still unsolved. To determine the best TCP Variants in MANET environment over renowned routing protocol is the main objective of this paper. A Study on the throughput fairness of TCP Variants namely, Vegas, Reno, New Reno, SACK, FACK, and Cubic are performed via simulation experiment using network simulator (ns-2) over existing routing protocol, named, AODV, AOMDV, DSDV, and DSR. This fairness evaluation of TCP flows arranged a contrast medium for the TCP Variants using stated routing protocol in MANET. However, TCP Vegas obtain unfair throughput in MANET. The simulation results show that TCP Reno outperforms other TCP variants under DSDV routing protocol. [ABSTRACT FROM AUTHOR]