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

Abstract

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