Research On Energy Efficiency Target Tracking In Wireless Sensor Networks

A wireless sensor networks (WSNs) has important applications such as remote environmental monitoring and target tracking. This has been enabled by the availability, particularly in recent years, of sensors that are smaller, cheaper, and intelligent. These sensors are equipped with wireless interfaces with which they can communicate with one another to form a network. The design of WSNs depends significantly on the application, and it must consider factors such as the environment, the application's design objectives, cost, hardware, and system constraints.Due to the reason that the Wireless Sensor Networks (WSNs) are more mobile than other networks, WSNs has been applied in many fields such as military target tracking, biomedical health monitoring, and hazardous environment exploration and so on. For the purpose of mobile target tracking, we can take advantage of WSNs. When it comes to energy consumption, there are prediction method and tracking mobile target method. Nowadays, many authors have been put attention on predicating the orbit of mobile target. When getting the location of mobile target in future, sensor nodes around the location can be awakened up to prepare for tracking task. When sensor nodes sense a mobile target, it will communicate with other sensor nodes which also sense the mobile target. After that, the location of mobile target can be acquired.We discuss tracking a mobile target. First, we introduce some predication methods including particle filter (PF), Kalman filter (KF) and Gaussian Mixture Model (GMM). Then we predict the location of mobile target based on GMM using speed, direction and accelerated velocity. Second, considering energy efficiency, we use sigmoid function to reduce the total number of sensor nodes when tracking a target. At the end, we exam our method on NS2 simulator. Experiment results show that our method provides a better tradeoff between energy efficiency and tracking qualities.