EFFICIENT TCP PERFORMANCE IN AD-HOC NETWORKS USING NOVEL HYBRID AD HOC COLLECTIVE SPACE DIRECTION - GENETIC ALGORITHM

Ad-hoc networks are susceptible to several kinds of attacks and susceptible to congestion in underlying TCP. Hence it is necessary to improve the TCP performance and congestion control over Ad-Hoc networks to accomplish efficient and secure routing. This study aims to obtain an efficient route with minimum distance and maximum residual path by introducing Fitness Function - FF and by the use of the proposed novel hybrid AOCSD-GA. In addition, to improve congestion control so as to enhance the efficiency of the system. Initially, multiple routes are found using the proposed novel AOCSD. Then the route congestion is predicted, and genetic algorithm is initialized to estimate the objective function. Subsequently, a random selection process is implemented using elitism scheme. An efficient route with maximum residual path is selected by using the proposed novel hybrid AOCSD-GA. The proposed methodology is comparatively analysed with other traditional methods in terms of various metrics such as PDR expanded as Packet Delivery Ratio, hop counts to reach destination, End-to-End (E2E) delay, latency and network lifetime. The analytical results showed that the proposed system outperformed other traditional methods by enhancing TCP performance and efficient routing