Topology Optimization Algorithm Based On Optimally Rigid Graph For Wireless Sensor Network

With the development of sensor and communication technologies, wireless sensornetwork (WSN) has been widely used in many areas, which causes it is as a hot issue. Forthe energy-constrained WSN, the topology optimization algorithm can not only reduce theenergy consumption and extend the network lifetime, but also improve the efficiency ofMAC protocols and routing protocols. Thus, this thesis analyzes the drawbacks of theexisting topology optimization algorithm and investigates the WSN topology optimizationalgorithm based on the optimally rigid graph. The specific studies are as follows:(1) To solve the problem that the node degree of topology constructed by topologyoptimization algorithm based on node scheduling is too high, the node scheduling andpower control topology optimal algorithm is proposed. The optimally rigid graph isintroduced to optimize the topology formed by the active nodes and further decrease theenergy consumption. The theoretical analysis and the simulation results show that thetopology by this algorithm is connected and the average of node degree is bounded.(2) The node scheduling and power control topology optimization algorithm isextended to the heterogeneous wireless sensor networks. We design Optimally RigidGraph-based Geographical adaptive fidelity algorithm. Relying on the local information,nodes in heterogeneous wireless sensor networks construct the optimally rigid topology,thus it effectively reduces the information complexity while maintaining the topologyconnectivity. At last, we evaluate the algorithm by simulation experiment, which provesthat the algorithm ensure the reliability of information transmission. Besides, thisalgorithm has the capability of relieving power consumption while keeping the robustperformance.(3) To solve the problem that most of existing algorithms can not balance energyconsumption, the energy efficient distributed topology control algorithm based onoptimally rigid graph is presented. Through the link weight function reflecting both theenergy consumption and residual energy of two end nodes, it builds a dynamic networktopology that changes with the variation of node energy, and thus balances energy consumption of nodes. Furthermore, simulation results show that this algorithm canbalance energy consumption of nodes efficiently compared with other algorithms, therebyextend the lifetime of networks.