Data Compression Method Combining Properties of PPM and CTW

Okazaki, T.; Sadakane, Kunihiko; Imai, Hiroshi

doi:10.1007/3-540-45884-0_18

Cited by 3 publications

(1 citation statement)

References 7 publications

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“…A CTW Markov predictor for the binary sequence 010|11010100011 Figure 7. A sketch of the DeCTW Markov predictor for the sequence aabacbbabbacbbc work by Sadakane, Okazaki, and Imai (2000), which provided a very simple and practical implementation along with a technique for combining the prediction strength of PPM and CTW (Okazaki, Sadakane, & Imai, 2002).…”

Section: Application Fieldsmentioning

confidence: 99%

Information-Theoretic Methods for Prediction in the Wireless and Wired Web

Katsaros

2007

Web Data Management Practices

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Discrete sequence modeling and prediction is an important goal and a challenge for Web environments, both wired and wireless. Web client’s data request forecasting and mobile location tracking in wireless cellular networks are characteristic application areas of sequence prediction in such environments. Accurate data request prediction results in effective data prefetching which combined with a caching mechanism can reduce user-preceived latencies as well as server and network loads. Also, effective solutions to the mobility tracking/prediction problem can reduce the update and paging costs, freeing the network from exceesive signaling traffic. Therefore, sequence prediction comprises a very important study and development area . This article presents information-theoretic techniques for discrete sequence prediction. It surveys, classifies, and compares the state-of-the-art solutions, suggesting routes for further research by discussing the critical issues and challenges of prediction in wired and wireless networks

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Section: Application Fieldsmentioning

confidence: 99%

Information-Theoretic Methods for Prediction in the Wireless and Wired Web

Katsaros

2007

Web Data Management Practices

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Data Compression Method Combining Properties of PPM and CTW

Okazaki

Sadakane

Imai

2002

Progress in Discovery Science

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Information-Theoretic Methods for Prediction in the Wireless and Wired Web

Katsaros

Selected Readings on Telecommunications and Networking

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Discrete sequence modeling and prediction is an important goal and challenge for Web environments, both wired and wireless. Web clients’ datarequest forecasting and mobile location tracking in wireless cellular networks are characteristic application areas of sequence prediction in such environments. Accurate data-request prediction results in effective data prefetching, which combined with a caching mechanism can reduce userperceived latencies as well as server and network loads. Also, effective solutions to the mobility tracking and prediction problem can reduce the update and paging costs, freeing the network from excessive signaling traffic. Therefore, sequence prediction comprises a very important study and development area. This chapter presents information- theoretic techniques for discrete sequence prediction. It surveys, classifies, and compares the state-of-the-art solutions, suggesting routes for further research by discussing the critical issues and challenges of prediction in wired and wireless networks.

show abstract

Data Compression Method Combining Properties of PPM and CTW

Cited by 3 publications

References 7 publications

Information-Theoretic Methods for Prediction in the Wireless and Wired Web

Information-Theoretic Methods for Prediction in the Wireless and Wired Web

Data Compression Method Combining Properties of PPM and CTW

Information-Theoretic Methods for Prediction in the Wireless and Wired Web

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