Optimizing Wireless Sensor Networks Based On Game Theory

As a new type of wireless network, wireless sensor network is widely applied in the industrial, commercial, military and medical. In many applications, the high performance of the wireless sensor network is required. Therefore, it is essential to ensure the excellent performance of the wireless sensor network with a limited resource supply. The researches on traditional ad hoc networks focus on better service quality and higher throughput while efficient communication strategies with low energy consumption are required in sensor network. We make the following contributions to the filed of wireless sensor network.(1) Focussing on clustering network structure, we provide an election mechanism of wireless sensor network. Randomly selected a node that service to gather information that the residual energy of each node, eliminate the node that residual energy is not enough to sustain the next round’s normal operation and selected the node that with the highest residual energy as cluster head of the next round. Based on the idea of evolutionary game theory, we assume that nodes are bounded rationality, and design incentive mechanism to make nodes report their energy information honestly. Thus, optimize the energy consumption of whole network.(2) For the transmission problems in data collection applications, we designed the routing mechanism for communication across the network. Nodes that want to transmit data make a broadcast between neighbor nodes within the cluster, and nodes that want to forward data declare its cost. Select the node with lowest cost statement and form a Lowest Cost Path (LCP) Path while other nodes have to form the None-LCP Path. Experimental results prove that nodes in LCP path can obtain more benefit when reduce forwarding cost. However, nodes that in the None-LCP Path will obtain less benefit when reduce forwarding cost. So the node will continue to reduce the forwarding cost to obtain the maximum benefit.(3) We provide a adaptive algorithm to optimize energy consumption, and use data weighting algorithm to improve the performance of wireless sensor network (WSN). An adaptive algorithm was proposed to reduce the number of nodes to optimize the energy consumption. Under the premise of basic network latency needs, maintain a minimum number of nodes to listen to the environment. Data weighting algorithm mechanism was provided to guarantee that important data will be transmitted and processed first. We assumed that information that contains task reach the base station or sink node fleetly is a sign of superior performance. Weight w is proposed to measure the importance of data, and determine the order that data through the Access Point (AP).