Published Paper Details:

In this study, effective distributed techniques for wireless network cost reduction are explored. We look at the difficulties of multi-hop data aggregation for correlated data in wireless sensor networks, specifically how to minimise energy consumption and maximise throughput. The proposed techniques make advantage of redundant information within a game-theoretic framework. Using optimum reaction dynamics to local data, routes are selected to reduce the network's overall energy consumption. Routing uses a cost function that considers several factors, including distance, interference, and data accumulation inside the network. The energy consumption of the network is drastically decreased by the suggested energy-efficient correlation-aware routing method, which converges in a bounded number of iterations. We optimize performance by constructing paths that minimize network-wide disturbance and maximize correlation between forwarded data. Each path's nodes are selected to optimize data gathering inside the network while reducing the potential for local interference. The method is guaranteed to converge in a limited number of steps thanks to optimal response dynamics, and the resultant network design optimizes global network throughput.