Cross-Layer based TCP Performance Enhancement in IoT Networks

Transmission Control Protocol (TCP) used multiple paths for performing transmission of data simultaneously to improve its performance. However, previous TCP protocols in Internet Things (IoT) networks experienced difficulty transmit a greater number subflows. To overcome the above issues, we introduced cross-layer framework perform efficient packet scheduling and congestion control increasing performance IoT networks. Initially, proposed network is constructed based on grid topology using Manhattan distance which improves scalability flexibility network. After construction, performed by considering numerous parameters such as bandwidth, delay, buffer rate, etc., fitness proportional fair (FPF) algorithm selecting best subflow reduce delay. The scheduled sent over an optimal path throughput goodput. scheduling, cooperative constraint approximation 3+ (CoCoA3+-TCP) three stages are employed namely detection, fast retransmission, recovery. detection TCP-IoT environment several cat mouse-based optimization (CMO) utilized adaptively estimate retransmission timeout (RTO) reducing delay improving convergence during retransmission. Fast recovery adjusting window size thereby avoiding congestion. simulation approach carried out simulator (NS-3.26) results show that work outperforms high terms throughput, goodput, loss, jitter, size.