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Abstract:

With the rapid growth of the World Wide Web, demand for internet bandwidth has risen sharply [1]. This demand for data naturally creates network congestion and tends to increase retrieval latency. In order to reduce the demand for bandwidth and to improve retrieval latency, several agencies have begun to implement network caching for the internet (examples may be found in [2], [3], and [4]). The main idea in network caching is to create copies of network accessible documents which are "closer " (either physically, with respect to transmission cost, or with respect to latency) than the home location of the document. The current efforts have largely been based on demand placement techniques such as LRU. That is, when a user requests a document, a copy of that document is cached in the closest cache to the user. While this may be the proper approach for moderate size data objects such as a typical HTML document, a more conservative approach may be warranted for large objects such as video data. Indeed, in this work, the authors propose an algorithm for allocating network storage and communication resources for large multimedia objects. The size of an object is significant for two related reasons. The first reason is that miscaching a large object incurs a greater real cost than caching a smaller object. When one considers that a real cost is associated with disk space ($/MB/month), the penalty incurred by miscaching a gigabyte size object becomes obvious. The second reason is that

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