Data storage and transmission, task scheduling, and network construction used for that. The authors have proposed a clustering algorithm to find the group relationships for query and data aggregation efficiency. This paper are as follows: First, since the clustering algorithm itself is a centralized algorithm, in this paper, they further consider systematically combining multiple local clustering results into a consensus to improve the clustering quality and for use in the update-based tracking network. Second, when a delay is tolerant in the tracking application, a new data management approach is required to offer transmission efficiency, which also motivates this study. They thus define the problem of compressing the location data of a group of moving objects as the group data compression problem.