Latency-sensitive hashing for collaborative Web caching

Abstract

Many geographically distributed proxies are increasingly used for collaborative Web caching to improve performance. In hashing-based collaborative Web caching, the response times can be negatively impacted for those URL requests hashed into geographically distant or overloaded proxies. In this paper, we present and evaluate a latency-sensitive hashing scheme for collaborative Web caching. It takes into account latency delays due to both geographical distances and dynamic load conditions. Each URL request is first hashed into an anchor hash bucket, with each mapping to one of the proxies. Secondly, a number of nearby hash buckets are examined to select the proxy with the smallest latency delay to the browser. Trace-driven simulations are conducted to evaluate the performance of this new latency-sensitive hashing. The results show that (1) with the presence of load imbalance due to skew in request origination or hot-spot references, latency-sensitive hashing 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 delays by directing requests to geographically closer proxies.