Dynamic Object Tracking Tree in Wireless Sensor Network

Recent advances in embedded microsensing technologies and low-energy cost sensors have made wireless sensor networks possible. Object tracking is an important research of wireless sensor networks. However, most object tracking tree is constructed based on a predefined mobility profile. When the real object movement behaviors are very different to the predefined mobility profile, the object tracking tree performance will become worse. In the paper, we will propose a dynamic adaptation mechanism, referred to as "Message-Tree Adaptive (MTA)" procedure, to improve the object tracking tree when the predefined mobility profiles do not match. From the simulation results, the performance of the object tracking tree can be significantly improved, when the MTA procedure is performed.