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Make Web Caching Pay Off August 23, 1999 By Gregory Yerxa Buying in bulk is a fitting analogy for Web caching. Rather than dragging yourself to Best Buy or surfing to an online store every time you need a new Palm Pilot stylus, you can visit a warehouse with the ultimate in buy-one-get-very-many-free sales. Just like those shopping trips, each trip that a Web browser takes on your network fulfills a future need. Multiply this possibility by the number of commonly browsed Web pages and suddenly it's easy to quantify the amount of Web traffic on your LAN that you can eliminate with a Web cache. The theory behind Web caching is simple: When users on your network request Web objects, the cache makes the request on behalf of the client to the origin server. In turn, the origin server sends the requested Web objects to the cache along with header information, such as whether the object can be cached and for how long. If the content can be cached, the Web cache stores it on your LAN for subsequent requests. When the new requests come in, the Web cache can glean the age and accuracy of the cached content based on the original header information, and check with the origin server to determine if the older Web objects have changed since prior requests. The entire process must occur quickly to prevent end users from experiencing a noticeable delay.
Clearly, Web caching is a practical, efficient concept, but before you shell out big bucks to implement it on your network, there are some issues you'll need to address. How will this new technology affect your network configuration? How do you address a new point of failure? Can you expect the same trouble-free Web surfing that you already experience? Are other value-added services available in conjunction with Web caching?
The Issues
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Worldwide, caching has caught on--estimates of cacheable content online are now near 80 percent--but that doesn't translate directly into bandwidth savings. Members of the Web Polygraph team (polygraph. ircache.net) use a 55 percent hit ratio when they run caching bake-off performance tests. That number is derived from real-life caches that reveal hit ratios varying from 30 percent to 70 percent. Caching vendors' hit ratio claims are occasionally higher than these conservative estimates because some do not add prefetched documents into their hit ratio calculations.









