Group Movement Pattern Mining Algorithm for Data Compression

To reduce the data volume, various algorithms have been proposed for data compression and data aggregation. In object tracking applications, natural phenomena show that many creatures form large social groups and move in regular patterns. However, the previous works do not address application level semantics, such as the group relationships and movement patterns, in the location data. In this paper, we first introduce an efficient distributed mining algorithm to approach the moving object clustering problem and discover group movement patterns. Afterward, we propose a novel compression algorithm, based on the discovered group movement patterns to overcome the group data compression problem. Our experimental results show that the proposed compression algorithm effectively and efficiently reduces the amount of delivered data and reduces energy consumption expense for data transmission in WSNs. Keywords--Data compression, data aggregation, distributed mining, object tracking ,energy consumption.