Abstract: Natural phenomena show that many creatures form large social groups and move in regular patterns. To reduce the data an efficient distributed mining algorithms are used to jointly identify a group of moving objects and discover their movement patterns in wireless sensor networks. In object tracking applications, many natural phenomena show that objects often exhibit some degree of regularity in their movements. To reduce the data volume, various algorithms have been proposed for data compression and data aggregation. In this paper we have surveyed various research papers of movement pattern mining, clustering, and data compression techniques.