Sensor Network Target Tracking Algorithm

With the development of communication technologies, embedd technologies and microelectronic technologies, wireless sensor networks (WSNs) have been applied and studied extensively in the recent years. WSNs can be widely used in many areas, such as national military, environment monitoring, health and medical community, smart home, taget tracking and so on. In this thesis, we research into the taget tracking, cluster head electing, and joins queries technologies for WSNs. The main contributions of this thesis are as follows.1. In order to maximize the lifetime of each cluster in hierarchy sensor networks, a cluster-head selecting algorithm based on Linear Programming (LPCHS) and a cluster-head scheduling algorithm based on cluster-head ratio (CHSA) are proposed in this paper. LPCHS first constructs a LP equation which maximizes the lifecycle of a cluster based on the data flow conservation constraint, energy constraint, link capacity constraint as well as other constraints, and then obtains the lifecycle of a cluster, the time of a node in this cluster being cluster-head and the cluster-head ratio correspondingly. Furthermore, CHSA can fulfill the data forwarding among clusters by Multi-path routing technology, and obtain a cluster-head scheduling scheme based on the cluster-head ratio. Experimental results indicate that the algorithms proposed can improve the networks throughput and prolong the networks lifecycle effectively.2. Aiming at the problem of target tracking in wireless sensor networks, an energy efficient algorithm for mobile targets prediction and tracking is proposed in this paper. Sleep scheduling mechanism is used to reduce the energy consumption, as well as to guarantee the real-time tracking. During the process of prediction and tracking of the moving targets, LPCHS and CHSA are used to maximize the network lifecycle, a cluster is considered as the unit to predict the trajectory of the target with the Markov Chain theory, and the sleeping nodes within the predicted area will be waked up to monitor the targets. In order to predict the target accurately, a location algorithm based on distance vector is triggered to run to estimate its position. While the clusters initiative to sleep to conserve energy when they do not be involved in the sensing task. Simulations results and experimental results in real sensor networks indicate that the proposed algorithms can accurately describe the target trajectory, and efficiently reduce the network energy consumption.3. Aiming at the query sent by users during the taget tracking in sensor networks, a problem of single-join query based on caching is defined and is proved to be a NP-complete problem. Then a polynomial approximate algorithm is given to solve the problem so that the energy consumption is minimized. According to the approximate algorithm for single-join query, an energy efficient two-phase multi-join algorithm based on caching for multi-join query is proposed in this paper. It takes the cost of multiple joins into account, and can reduce the response time of query, minimize the energy consumption. Theoretical analyze and experimental result indicate that the proposed algorithms can reduce the energy cost, prolong the network lifetime, and improve the efficiency of query efficiently.