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Cache Management for Web-Powered Databases
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The Web has become the primary means for information dissemination. It is ideal for publishing data residing in a variety of repositories, such as databases. In such a multi-tier system (client - Web server - underlying database), where the Web page content is dynamically derived from the database (Web-powered database), cache management is very important in making efficient distribution of the published information. Issues related to cache management are the cache admission/replacement policy, the cache coherency and the prefetching, which acts complementary to caching. The present chapter discusses the issues, which make the Web cache management radically different than the cache management in databases or operating systems. We present a taxonomy and the main algorithms proposed for cache replacement and coherence maintenance. We present three families of predictive prefetching algorithms for the Web and characterize them as Markov predictors. Finally, we give examples of how some popular commercial products deal with the issues regarding the cache management for Web-powered databases.
Title: Cache Management for Web-Powered Databases
Description:
The Web has become the primary means for information dissemination.
It is ideal for publishing data residing in a variety of repositories, such as databases.
In such a multi-tier system (client - Web server - underlying database), where the Web page content is dynamically derived from the database (Web-powered database), cache management is very important in making efficient distribution of the published information.
Issues related to cache management are the cache admission/replacement policy, the cache coherency and the prefetching, which acts complementary to caching.
The present chapter discusses the issues, which make the Web cache management radically different than the cache management in databases or operating systems.
We present a taxonomy and the main algorithms proposed for cache replacement and coherence maintenance.
We present three families of predictive prefetching algorithms for the Web and characterize them as Markov predictors.
Finally, we give examples of how some popular commercial products deal with the issues regarding the cache management for Web-powered databases.
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