An empirical evaluation of client-side server selection algorithms

Abstract

Efficient server selection algorithms reduce retrieval time for objects replicated on different servers and are an important component of Internet cache architectures. This paper empirically evaluates six client-side server selection algorithms. The study compares two statistical algorithms, one using median bandwidth and the other median latency, a dynamic probe algorithm, two hybrid algorithms, and random selection. The server pool includes a topologically dispersed set of United States state government Web servers. Experiments were run on three clients in different cities and on different regional networks. The study examines the effects of time-of day, client resources, and server proximity. Differences in performance highlight the degree of algorithm adaptability and the effect that network upgrades can have on statistical estimators. Dynamic network probing performs as well or better than the statistical bandwidth algorithm and the two probe bandwidth hybrid algorithms. The statistical latency algorithm is clearly worse, but does outperform random selection.