Content sniffer based load distribution in a web server cluster

Abstract

Recently, layer-4 (L4) switches have been widely used as load balancing front-end routers for Web server clusters. The typical L4 switch attempts to balance load among the servers by estimating load using the load metrics measured in the front-end and/or the servers. However, insufficient load metrics, measurement overhead, and feedback delay often cause misestimate of server load. This may incur significant dynamic load imbalance among the servers particularly when the variation of requested content is high. In this paper, we propose a new content sniffer based load distribution strategy. By sniffing the requests being forwarded to the servers and by extracting load metrics from them, the L4 switch with our strategy more timely and accurately estimates server load without the help of back-end servers. Thus it can properly react to dynamic load imbalance among the servers under various workloads. Our experimental results demonstrate substantial performance improvements over other load balancing strategies used in the typical L4 switch.