An efficient location tracking structure for wireless sensor networks

Object tracking is an important application in wireless sensor networks. Efficient detection and location monitoring are critical requirements for a wireless sensor network when used in object tracking. Object tracking is typically organized into a tree format to deliver a report or aggregate the messages when object movement is detected. This paper addresses object tracking issues based on the greedy method proposing an efficient tracking method, referred to as the “Large Frequency First Tree (LFFT)”. The proposed method is designed to track a large number of moving objects by efficiently collecting and aggregating all tracking information. We also propose the Tree Adaptation Procedure (TAP) to reduce the object tracking tree updating costs. We also propose a new location-selection policy, referred to as the “center of gravity policy”. The simulation results show that the update cost for certain tree construction algorithms can be improved using the center of gravity policy. The update cost for the object tracking tree will be reduced when TAP is performed. The simulation results show that LFFT achieves good performance when TAP is applied once.