Location Of Wireless Sensor Network Based On Improved Quantum Genetic Algorithm

Wireless sensor network (WSN) is integrated multidisciplinary cutting-edge technology, soit has more advantage than other ordinary network and has very broad application prospects. Sofar, wireless sensors have been widely applied in areas such as deep sea exploration, aerospaceand anti-seismic disaster. With the development of Internet and wireless sensor technology,WSN will gradually enter into all kinds of areas of people’s life and production. And finally itwill become an indispensable part in our lives.Nodes positioning technology is a very important research directions in the area of WSN.Node localization problem is essentially one of seven mathematical problems of NP-completeproblems. Such problems often require modern intelligence such as genetic algorithms andParticle Swarm Optimization (PSQ) algorithm to solve, but these algorithms haveshortcomings.This article focuses on researching node positioning algorithm. First the classics locationalgorithms are analyzed. And then, aiming at the node self-location problem, this paperproposed two new localization algorithms for WSN which using the new results of thequantum-inspired evolutionary algorithm:1) This paper proposed a wireless sensor network node localization algorithm (WDQGA)which based on the double chain quantum genetic algorithm. The algorithm is a double chainquantum encoding scheme based on the quantum bit probability amplitude method. Theproposed algorithm overcomes the uncertainty and lessens the frequency while encodingbetween decimal and binary, so that makes each iteration to get two solutions can be updated atthe same time. Under the same conditions as population size, the proposed encoding method isable to accelerate the process of optimizing, extend the global optimal solution and enhance theglobal optimal solution of the probability of ascension. Analyzed the trends in the fitnessfunction in the search process when algorithm to determine the angle size. And then blend inthis information as a key element to the angle step function structure, so that makes eachquantum chromosome change according to its fitness value and can dynamically adjust thesearch process. The proposed algorithm improved the efficiency and accuracy of localization.Simulation and experimental results show that, the accuracy of localization is significantlyhigher than the classic algorithm of DV-Hop WDQGA in different network environments.2) This paper also proposed a wireless sensor networks localization algorithm based onquantum-inspired evolutionary algorithm (WBQEA). The algorithm used encoding methodbased on quantum-bit Bloch sphere coordinate and new quantum gate, so that makes everyquantum chromosome also represents three optimized solutions in the search space, thus increases the search speed effectively and the diversity of species, at the same time reduces thepossibilities of algorithm for Kentucky. Simulation experiments show that the proposedalgorithm is better than the traditional algorithms such as WDQGA and DV-Hop on obtainingpositioning accuracy.