Research On Technologies Of Coverage Optimization And Control For Wireless Sensor Networks

Wireless sensor network has been widely used in national defense, traffic control, precision agriculture fields, smart home, medical health and even space exploration. The optimization of wireless sensor network coverage and associated control technology is the basis for sensor network of perception, transmission, processing, and etc., undertaking a critical mission from the information perceiving phase to the information processing phase. The hot and difficult issues are network coverage optimization and control technology such as how to ensure coverage and minimize nodes consumption, improve balance, and prolong the survival time of the network. The main work of this paper as follows:1. Different two-dimensional plane scenarios focus on the different WSN coverage optimization targets, including many aspects such as coverage (optimizing precision), the number of convergence, convergence time, which proposes two coverage optimization strategies, laying emphasis on optimizing coverage and reducing convergence times respectively. (1) About the high coverage precision problem in some two-dimensional deterministic deployment scenarios, combined with the phenomenon of solution lost during the process of optimizing particle swarm optimization algorithm, the by-dimensional coverage optimization method (JV-PSO-DD) is proposed to determine the particle fitness value, which can solve the problem of optimal solution lost caused by the fitness evaluation that conducts until the information of all dimensions has been updated, and improve the accuracy of solution. Simulation shows that this algorithm is better than comparison algorithm in optimize coverage indicators, up to 97% under the same environment. (2) About the issues of high demand for numbers of convergence algorithm in the scenarios of some two-dimensional deterministic deployment, combined with the knowledge of geometry, the coverage optimization algorithm is proposed based on the directional movement of the node (COMDH). Take heterogeneous sensor network simulation contrast as example, simple four iterations of the algorithm can ensure high coverage, which is suitable for large-scale deterministic deployment of sensor network nodes.2. From two-dimensional plane to three-dimensional space and then the three-dimensional waters, the restrictions of certainty deploy are increasingly harsh. The enhanced hierarchical underwater space coverage algorithm (UHSCA) is proposed to against problems existing in underwater WSN coverage method, such as low coverage rate, too large energy consumption of node mobility and big energy consumption difference problem caused by node mobility, combined with the existing underwater coverage strategy. Theoretical analysis and simulation results show that the coverage optimization effect of the strategy for the certainty deployment of underwater nodes is obvious, which balances the energy generated by node mobility and provides effective program support for the coverage deployment of underwater space nodes, such as underwater reconnaissance, hydrological monitoring.3. A strategy that control node state by introducing a quantized sleep latency is proposed to solve the problems of energy waste, coverage holes, and poor balance of nodes energy consumption and so on, appearing in the random deployment methods under the complex and hazardous scenes, in order to lower the high cost and high risk made by secondary and even multiple layout. The quantization of sleep latency mainly refers to two conditions including the number of nodes around and residual energy of the node. The value of the simulation based on the indicators as survival time, the equilibrium value of energy consumption and mortality of nodes prove that the new control strategy has significant equilibrium effect on energy consumption and can optimize network lifetime more than 20%.4. In response to node covering shrinkage problems arising under random node deployment method when executed the state control strategy, combined with’ border effect’ phenomenon, the hybrid network control method by the boundary region’s moving and complementary is proposed. By observing the sample diagram of network nodes, the distribution uniformity of dead node is proved good. Calculating statistics and comparative analysis on the indicators of death number of node and the value of energy variance prove that the control strategy can effectively improve’border effect’ problem that exists in random deployment scenarios.