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- W2184590476 abstract "In this work, we exploit the characteristics of group movements to discover the information about groups of moving objects in tracking applications. We propose a distributed mining algorithm, which consists of a local GMPMine algorithm and a CE algorithm, to discover group movement patterns. With the discovered information, we devise the 2P2D algorithm, which comprises a sequence merge phase and an entropy reduction phase. In the sequence merge phase, we propose the Merge algorithm to merge the location sequences of a group of moving objects with the goal of reducing the overall sequence length. In the entropy reduction phase, we formulate the HIR problem and propose a Replace algorithm to tackle the HIR problem. In addition, we devise and prove three replacement rules, with which they Replace algorithm obtains the optimal solution of HIR efficiently. Our experimental results show that the proposed compression algorithm effectively reduces the amount of Delivered data and enhances compressibility and, by extension, reduces the energy consumption expense for data transmission in WSNs. We are using these algorithms to find out the performances on the bases on time complexity and space complexity by using visualization technique." @default.
- W2184590476 created "2016-06-24" @default.
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- W2184590476 date "2012-01-01" @default.
- W2184590476 modified "2023-09-26" @default.
- W2184590476 title "Performances of Data Compression using CE, GMPMine and 2P2D Algorithms" @default.
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