Please use this identifier to cite or link to this item: https://idr.l4.nitk.ac.in/jspui/handle/123456789/7572
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dc.contributor.authorAjaykrishnan, N.
dc.contributor.authorPrem, N.S.
dc.contributor.authorPrabhakaran, V.M.
dc.contributor.authorVaze, R.
dc.date.accessioned2020-03-30T10:02:31Z-
dc.date.available2020-03-30T10:02:31Z-
dc.date.issued2015
dc.identifier.citation2015 21st National Conference on Communications, NCC 2015, 2015, Vol., , pp.-en_US
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/7572-
dc.description.abstractReplicating or caching popular content in memories distributed across the network is a technique to reduce peak network loads. Conventionally, the performance gain of caching was thought to result from making part of the requested data available closer to end users. Recently, it has been shown that by using a carefully designed technique to store the contents in the cache and coding across data streams a much more significant gain can be achieved in reducing the network load. Inner and outer bounds on the network load v/s cache memory tradeoff were obtained in [1]. We give an improved outer bound on the network load v/s cache memory tradeoff. We also address the question of to what extent caching is effective in reducing the server load when the number of files becomes large as compared to the number of users. We show that the effectiveness of caching become small when the number of files becomes comparable to the square of the number of users. � 2015 IEEE.en_US
dc.titleCritical database size for effective cachingen_US
dc.typeBook chapteren_US
Appears in Collections:2. Conference Papers

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