Download e-book for iPad: 37.Multimedia by John G. Webster (Editor)

By John G. Webster (Editor)

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0 = heat( X ) ∗ (size( S X ,1 ) − DISK0 ( X )) + heat(Y ) ∗ (size( S Y ,1 ) − DISK0 (Y )) µ1 = heat( X ) ∗ (size( S X ,1 ) − DISK1 ( X )) + heat(Y ) ∗ (size( S Y ,1 ) − DISK1 (Y )) Thus, = heat( X ) ∗ δX + heat(Y ) ∗ δY = heat( X ) ∗ δX + heat(Y ) ∗ ( ABSENT( Z ) − δX ) = heat(Y ) ∗ ABSENT( Z ) + δX ∗ (heat( X ) − heat(Y )) Since heat(Y) ‫ ء‬ABSENT(Z) and (heat(X) Ϫ heat(Y)) are constants, in order to minimize ⌬, we can only vary ͳX (this impacts ͳY because ABSENT(Z) ϭ ͳX ϩ ͳY). , the object with higher heat(X) should not be replaced).

This can be achieved when many requests reference an identical CM object. The problem is, however, when these requests arrive in different time instances. In this section, we explain three approaches to hide the time differences among multiple requests referencing a single object: 1. Batching of requests (55–58): In this method, requests are delayed until they can be merged with other requests for the same video. These merged streams then form one physical stream from the disk and consume only one set of buffers.

If group G5 accesses cluster C2 during a time period, G5 would access C3 during the next time period. During a given time period, the requests occupying the slots of a group retrieve blocks that reside in the cluster that is being visited by that group. Therefore, if there are C clusters (or groups) in the system, and each cluster (or group) can support N simultaneous displays, then the maximum throughput of the system is m ϭ N ϫ C simultaneous displays. , playing musical chairs) with the C clusters using each for a Tp interval of time, and (2) at most, C Ϫ 1 failures might occur before a request can be activated (when the number of active displays is fewer than N ϫ C).

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