TY - GEN
T1 - Efficient algorithms for predicting requests to web servers
AU - Cohen, Edith
AU - Krishnamurthy, Balachander
AU - Rexford, Jennifer L.
PY - 1999
Y1 - 1999
N2 - Internet traffic has grown significantly with the popularity of the Web. Consequently user perceived latency in retrieving web pages has increased. Caching and prefetching at the client side, aided by hints from the server, are attempts at solving this problem. We suggest techniques to group resources that are likely to be accessed together into volumes, which are used to generate hints tailored to individual applications, such as prefetching, cache replacement, and cache validation. We discuss theoretical aspects of optimal volume construction, and develop efficient heuristics. Tunable parameters allow our algorithms to predict as many accesses as possible while reducing false predictions and limiting the size of hints. We analyze a collection of large server logs, extracting access patterns to construct and evaluate volumes. We examine sampling techniques to process only portions of the server logs while constructing equally good volumes. We show that it is possible to predict requests at low cost with a high degree of precision.
AB - Internet traffic has grown significantly with the popularity of the Web. Consequently user perceived latency in retrieving web pages has increased. Caching and prefetching at the client side, aided by hints from the server, are attempts at solving this problem. We suggest techniques to group resources that are likely to be accessed together into volumes, which are used to generate hints tailored to individual applications, such as prefetching, cache replacement, and cache validation. We discuss theoretical aspects of optimal volume construction, and develop efficient heuristics. Tunable parameters allow our algorithms to predict as many accesses as possible while reducing false predictions and limiting the size of hints. We analyze a collection of large server logs, extracting access patterns to construct and evaluate volumes. We examine sampling techniques to process only portions of the server logs while constructing equally good volumes. We show that it is possible to predict requests at low cost with a high degree of precision.
UR - http://www.scopus.com/inward/record.url?scp=0032626274&partnerID=8YFLogxK
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U2 - 10.1109/INFCOM.1999.749294
DO - 10.1109/INFCOM.1999.749294
M3 - Conference contribution
AN - SCOPUS:0032626274
SN - 0780354176
SN - 9780780354173
T3 - Proceedings - IEEE INFOCOM
SP - 284
EP - 293
BT - Proceedings - IEEE INFOCOM'99
T2 - 18th Annual Joint Conference of the IEEE Computer and Communications Societies: The Future is Now, IEEE INFOCOM'99
Y2 - 21 March 1991 through 25 March 1991
ER -