A Pattern Recognition Approach To Secure Cipher Documents
This work addresses data efficiency in wireless sensor networks, but appears incremental as it builds on existing pattern recognition and compression techniques.
The paper tackles the problem of reducing data transmission in wireless sensor networks by identifying group movement patterns and compressing the data, achieving a maximum compression ratio through optimal replacement rules.
Natural phenomena show that many creatures form large social groups and move in regular patterns. Previous In this paper, we first propose an efficient distributed mining algorithm to jointly identify a group of moving objects and discover their movement patterns in wireless sensor networks. Afterward, we propose a compression algorithm, called 2P2D, which exploits the obtained group movement patterns to reduce the amount of delivered data. The compression algorithm includes a sequence merge and an entropy reduction phases. we formulate a Hit Item Replacement (HIR) problem and propose a Replace algorithm that obtains the optimal solution. Moreover, we devise three replacement rules and derive the maximum compression ratio.