Abstrait

Searching Application-Level Meaning for Data Compaction

L. Nagarajan

Natural developments show that many brutes form large social groups and move in regular forms. However, previous works focus on finding the motion forms of each single object or all objects. In this paper, we first propose an effective disseminated mining rule to jointly identify a group of acting objects and detect their motion forms in wireless sensor networks. Afterward, we propose a compaction rule, called 2 Samuel, which feats the received group motion forms to reduce the amount of delivered data. The compaction rule includes an episode unite and an information simplification phases. In the episode unite phase, we propose a unite rule to unite and compaction the localization data of a group of acting objects. In the information simplification phase, we develop a collision point Replacement (CPR) problem and propose an exchange algorithm that obtains the optimal solution. Moreover, we devise three replacing rules and gain the maximum compaction ratio. The experimental results show that the proposed compaction rule leverages the group motion forms to reduce the amount of delivered data in effect and efficiently.