Latency-sensitive hashing for collaborative Web caching

Many geographically distributed proxies are increasingly used for collabora tive Web caching to improve performance. In hashing-based collaborative Web caching, the response times can be negatively impacted for those URL reque sts hashed into geographically distant or overloaded proxies. In this paper , we present and evaluate a latency-sensitive hashing scheme for collaborat ive Web caching. It takes into account latency delays due to both geographi cal distances and dynamic load conditions. Each URL request is first hashed into an anchor hash bucket, with each bucket mapping to one of the proxies . Secondly, a number of nearby hash buckets are examined to select the prox y with the smallest latency delay to the browser. Trace-driven simulations are conducted to evaluate the performance of this new latency-sensitive has hing. The results show that (1) with the presence of load imbalance due to skew in request origination or hot-spot references, latency-sensitive hashi ng effectively balances the load by hashing into geographically distributed proxies for collaborative Web caching, and (2) when the overall system is lightly loaded, latency-sensitive hashing effectively reduces latency delay s by directing requests to geographically closer proxies. (C) 2000 Publishe d by Elsevier Science B.V. All rights reserved.