Optimization And Application Of Geometric Constraint In WSNs Localization

In recent years, with the rapid development of micro-electromechanicalsystems, low-power embedded technology, wireless communication, system on chipand low multifunction sensor technology, wireless sensor networks technologygradually come into our horizon. Due to its low power consumption cost and itscharacteristics of distributed and self-organization, wireless sensor networks bring arevolution to us that in the field of information perception. Wireless sensor networkshas become a popular and promising applications of technology, and it has beenconcerned by majority of researchers in military, medical, aerospace and other fields.Locating technology is one of the key supporting technologies of wireless sensornetworks, because the data from equipments is meaningless if the nodes can not bedetermined their location. Therefore, the merits of the locating technology impactswireless sensor networks directly in practical applications.Based on the development of the locating technology, we research on thefree-range locating algorithms which have many features like self-organizing, lowpower consumption, flexible of network layout. We are trying to pioneer itshigh-speed, high-accuracy and scalability to make a new prospect of locatingtechnology, and it can also offer new ideas and new insights to the research in thefuture. In this paper, we use geometric constraints concepts into wireless sensornetwork localization to solve the problem that come from locating. We propose twoimproved algorithms named Convex-Circle in Shadow algorithm and Virtual NodesCorrection algorithm. Moreover, we use formulas and simulations to improve them,and it has a good theoretical basis and practical value. The main innovations andresearch results as follows:1．Discuss the convex algorithms to find its shortage which cause the lowaccuracy of locating. Then, we propose an improved algorithm to solve the problemwith the geometric constraints. The improved algorithm can reduce the error oflocating with the low power consumption. 2． Based on the theoretical principles of centroid algorithm, we propose animproved algorithm to solve the inadequacy of the centroid algorithm with thegeometric constraint. The improved algorithm also can reduce the error of locatingwith the low power consumption.