Publication

Abstract : In mobile wireless sensor networks (MWSNs), achieving reliable and low-latency communication remains a significant challenge due to node mobility, congestion, and unpredictable link quality. In this paper, the author has suggested a cross-layer optimized communication protocol that is set to reduce the end to end latency at the same time maintain high packet delivery efficiency in dynamic environments. It implements improvements to the routing of AODV with the help of a latency-sensitive metrics, adaptive MAC scheduling, and energy-conscious mechanisms. Also, the metaheuristic tuning of routing parameters is performed using Ant Colony Optimization (ACO), and predictive handoff and fair queuing approaches permit the company to maintain performance when the node mobility is high. The NS-3 environment employs Gauss-Markov mobility model to simulate a real-world node dynamics and therefore the simulation is conducted in the NS-3 environment. The performance is compared to AODV and improved AODV protocols baselines in different network densities, node speeds, and traffic loads. It has been demonstrated that the proposed system can achieve a mean ratio of 93.2 delivered packets, latency cut by up to 45 %, and jitter cut by more than 50 % under various conditions. Moreover, smart sleep scheduling and energy conscious routing also cut down energy consumption by around 32%. The protocol can be applied in real time applications like vehicular sensor network, mobile health monitoring, and disaster surveillance. The proposed system has stronger performance, scalability, and resilience in the mobile environment due to the combination of cross-layer optimization and real-time monitoring and predictive control. Future work can incorporate edge AI to support traffic classification as well as deploy the framework on hardware using 6Gcompatible sensors to support ultra-reliable low-latency communication (URLLC).