Latency-Sensitive Hashing for Collaborative Web Caching

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 bucket 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.