Game-Theoretic Optimization of EnergyEfficient Multihop Routing and Clustering in Wireless Sensor Networks
Abstract
The lifespan of the Intelligent Transport System (ITS) nodes should be expanded, as overloaded nodes dying early affects existing hierarchical routing protocols, thus impacting the nodes lifetime. Inspired by this idea, an energy-efficient multipath routing method is proposed by utilizing adaptive clustering in wireless sensor networks (WSNs). A game-theoretic method for managing low energy multipath routing (LEMR-GT) in noncooperative games is developed to create energy-efficient network communication with equitable energy distribution. The utility function is based on the remaining power, amount of traffic, and number of links of nearby nodes. The contention radius for nodes is modified according to the topology and traffic load used to choose the cluster head. Then, the active nodes select the final cluster leader by assessing competitive parameters. Simulation results demonstrate that the proposed approach significantly outperforms conventional clustering protocols, such as Low-Energy Adaptive Clustering Hierarchy (LEACH) and Hybrid Energy-Efficient Distribute, in terms of network lifetime, energy efficiency, packet delivery ratio, and end-to-end delay. The LEMR-GT results indicate that our method achieves up to 38% improvement in energy savings, a 25% increase in network lifetime, and over 15% higher packet delivery ratio.
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