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Copyright © 2015
M. S. Thirumalai
Application Level Semantics for
Compressing Group Movement Patterns in
Wireless Sensor Networks
J. Biju, M.E.
This paper proposes an efficient distributed mining algorithm to jointly identify a group of moving objects and discover their movement patterns in wireless sensor networks. Then propose a compression algorithm, called two–phase and two-dimensional algorithm, which exploits the obtained group movement patterns to reduce the amount of delivered data. The compression algorithm includes a sequence merge phase and an entropy reduction phase. In the sequence merge phase, propose a merge algorithm to merge and compress the location data of a group of moving objects. In the entropy reduction phase, formulate a Hit Item Replacement (HIR) problem and propose a replace algorithm that obtains the optimal solution. Then devise three replacement rules and derive the maximum compression ratio. The experimental results show that the proposed compression algorithm leverages the group movement patterns to reduce the amount of delivered data effectively and efficiently.
Keywords: mining algorithm, wireless sensor, compression leverages
Recent advances in location-acquisition technologies, such as global positioning systems (GPSs) and wireless sensor networks (WSNs), have fostered many novel applications like object tracking, environmental monitoring, and location-dependent service. These applications generate a large amount of location data, and thus, lead to transmission and storage challenges, especially in resource constrained environments like WSNs. To reduce the data volume, various algorithms have been proposed for data compression and data aggregation.
However, the above works do not address application-level semantics, such as the group relationships and movement patterns, in the location data. In object tracking applications, many natural phenomena show that objects often exhibit some degree of regularity in their movements.
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J. Biju, M.E.
Department of Computer Science
Theni Kammavar Sangam College of Technology
Theni 625 534