JISE

Recent advancement in wireless sensor networks consider independent layer parameters jointly exploiting existing collaborative mechanism using cross layer design (CLD) optimization maximizing the overall network performance in terms of reduction of energy consumption, efficient routing, and lifetime enhancement. Integrating layer functionalities pose challenges on objective functions relating to complexity and non-linearity making it highly multimodal thus complicating the search boundaries. Due to flexibility and versatility, the computationally intelligent Bio-inspired swarm are very efficient in solving such non-linear design issues. The work introduces a hybrid approach using the minimum execution/completion time (MECT) scheduling and particle swarm optimization (PSO) scheme called MECT-PSO protocol to improve the performance of Routing protocol ensuring an optimal path and then minimizing the average energy loss (AEL) by localizing the intermediate nodes (IN’s) along the optimal route. The strategy of shortest path with minimum hop count is exploited by considering alternative routes from source to receiver and an optimal path is chosen based on MECT algorithm considering queue status and the node overheads. The optimal path length is reduced by localizing the IN’s to find the best positions under topological constraints using novel swarm approach. The self-organizing approach of nodes provides better connectivity, coverage and reliable paths. Analysis and evaluation of the proposed MECT-PSO protocol implemented using MATLAB platform showed significant improvement over existing algorithms in terms of residual energy, surviving nodes and coverage.