In wireless sensor networks, if sink node is stationary, the nodes close to sink will deplete energy faster than those in other areas. The unbalanced energy consumption among the nodes will lead to the energy hole problem, which shortens the network lifetime. To solve the problem, evolutionary game–based trajectory design algorithm for mobile sink in wireless sensor networks is proposed in this article. In evolutionary game model, the average residual energy of each cluster, average intra-cluster energy consumption, and average inter-cluster energy consumption are used to design utility function. The sink will select the cluster with more utility value as its new location and move to the cluster head which has the largest residual energy and the shortest distance to other cluster heads. The simulation results show that the algorithm can effectively balance network load, reduce network energy consumption, prolong the network lifetime, and increase the number of data packets that sink receives.
A clustering routing algorithm using game theory is presented to extend the lifetime of wireless sensor networks. In the cluster building stage, the cluster head election model is established by the remaining energy of nodes and the energy expenditure of cluster heads. The optimal cluster heads are chosen by Nash equilibrium probability. In the inter-cluster routing stage, cluster heads set their own bidding price according to their remaining energy, energy consumption and distance to sink, and finally form the optimal path to sink through multi-round auction game among neighbour cluster heads. The experiment results show that the routing algorithm can effectively extend the network lifetime, balance the energy expenditure of nodes, and increase the number of packets arriving at sink.
In wireless sensor networks, data transmission quality and energy efficiency are closely related to link quality indicator. In order to improve the performance of Multipath Routing protocol, this paper proposes a LqiRings Routing protocol based on link quality and hops between nodes. In the routing discovery stage, LqiRings Routing does not take hops as the only factor in routing decision-making, but considers hops and link quality as two factors, and determines the optimal path by adjusting the weights between them. The LqiRings Routing protocol, Multipath Routing protocol and Hop Counts Routing protocol are simulated and analyzed in Castalia simulator. The experimental results show that the LqiRings Routing protocol proposed in this paper has higher packet delivery rate and lower average energy consumption under the same environment. 1
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