| Wireless sensor network (WSN) is composed of a large number of wireless senor nodes which can communicate with each other and possess computing capabilities. These nodes are deployed in the target area to complete the assigned task. So the WSN is a self-organizing, autonomous, adaptive multi-hop network. Because of the WSN's mobility, it enables its superiority and broad application. On the other hand, since WSN usually works in the field and its main energy source is provided by the battery, the mobility also led to the limitation of the energy supplying. Because of the multi-hop and energy limitation, routing search algorithms and energy optimization are two current hot issues in WSN. Quantum genetic algorithm (QGA) is a new random search optimization algorithm, which is combined by traditional genetic algorithm and quantum computing theory. QGA does not only inherit the advantages of parallel and high-performance of traditional genetic algorithm, but also has a small population size, a high search capability, rapid convergence and a high stability optimal solution. Therefore QGA can show superior performance to solve combinatorial optimization problems.Firstly, the advantages and disadvantages of genetic algorithm were analyzed and the theory of quantum computing was introduced. Then the QGA's two key elements, quantum bit (qubit) encoding and qubit updating, were analyzed in detail. At last the salient features of QGA were summarized. The routing search concrete implementation of WSN, based on QGA, was described. And the relevant performance of routing search of QGA was analyzed by comparing to the particle swarm optimization (PSO) algorithm. Based on the model of WSN routing search with QGA, an energy-saving strategy was proposed. The strategy can balance the energy consumption speed of each node and improve the network performance.In large-scale sensor network, the computational complexity of the traditional encoding QGA is too high because of the large-scale nodes. For this reason, an improved encoding for reducing the encoding length is proposed. And it can solve the problem that traditional routing search algorithm could not meet the requirements of the large-scale routing search and the network real-time.To implement the simulation of WSN system, Visual C++6.0 is used as the mainly programming tool and MATLAB is used to plotting. The results show as follows.(1) To WSN path search, QGA has faster convergence and better path searching results than PSO algorithm.(2) After using the energy-ranking strategy, the nodes which are close to the fusion center have been balanced the energy consumption, and the network lifetime has been increased greatly. Meanwhile, a reasonable grade of energy ranks can improve the network lifetime and meet the requirements of real-time routing search.(3) The improved encoding QGA solved the best routing search problem in large-scale WSN, and optimized the energy efficiency with energy-saving strategy to improve the network performance. |
