Efficient Congestion Control Mechanism and Handover Management Scheme for Performance Enhancement of TCP over IoT Network
International journal of intelligent engineering and systems · 2024
Transmission Control Protocol (TCP) used multipath for achievement of data instantaneously to improve its performance.Anyhow, the preceding TCP protocol in the Internet of Things (IoT) network experienced a struggle to transmit a superior number of subflows.The Bottleneck Bandwidth and Round-trip propagation time (BBR) generate a network path model by assessing the available bottleneck bandwidth and the minimal Round-Trip Time (RTT) to achieve the desired delivery rate, consequently reducing the latency.However, some research studies have indicated the presence of significant fairness issues related to RTT in the BBR algorithm.To overcome this issue, we proposed a New Enhanced Congestion Control (CC) mechanism referred to as Bottleneck Bandwidth and Round-trip propagation time (BBR-NEnh) which is cross-layer-based efficient congestion control in a 5G IoT heterogeneous network.The proposed work encloses three sequential processes including grid-based network construction, improved two-factor clustering, and Hybrid TCP congestion control.Initially, we perform network construction by grid-based to improve the information transfer rate and increase connectivity among devices.After that, IoT devices are clustered based on two factors congestion and buffer space using the Improved K-Medoids algorithm (IK-Med) by the edge server.Further, to enhance the efficiency of TCP, the proposed research adopts a BBR-NEnh by optimizing the congestion control parameters using the Adaptive Tunicate Swarm Optimization (ATSO) algorithm.Finally, the dynamic handover and adjustment of windows are performed based on the Fast Adaptation Technique (FAdT) which can send the data quickly without congestion.The implementation of the proposed research is carried out using NS-3.26 and the performance of the proposed BBR-NEnh model is evaluated using a variety of performance metrics, including goodput, delay, packet loss, queue length, transmission rate, and throughput.The performance of the proposed work is compared with IMPRTT (Improved RTT) and CW-IoT (Congestion Window Algorithm for the Internet of Things).The average throughput, goodput, and packet loss of the proposed work for 1500 packets size are 4, 0.9, and 10.3, and the average delay, transmission rate, and queue length over 150 seconds are 0.004, 2500, and 36.1, demonstrating that the proposed work outperforms earlier work like IMPRTT and CW-IoT.