Comparison of load balancing strategies on cluster-based web servers

Abstract

This paper focuses on an experimental analysis of the performance and scalability of cluster-based web servers. We carry out the comparative studies using two experimental platforms, namely, a hardware testbed consisting of sixteen PCs, and a trace-driven discrete-event simulator. Dispatcher and web server service times used in the simulator are determined by carrying out a set of experiments on the testbed. The simulator is validated against stochastic queuing models and the testbed. Experiments on the testbed are limited by the hardware configuration, but our complementary approach allows us to carry out scalability studies on the validated simulator. The three dispatcher-based scheduling algorithms analyzed are: round robin scheduling, least connected based scheduling, and least loaded based scheduling. The least loaded algorithm is used as the baseline (upper performance bound) in our analysis and the performance metrics include average waiting time, average response time, and average web server utilization. A synthetic trace generated by the workload generator called SURGE, and a public-domain France Football World Cup 1998 trace are used. We observe that the round robin algorithm performs much worse in comparison with the other two algorithms for low to medium workload. However, as the request arrival rate increases, the performance of the three algorithms converge with the least connected algorithm approaching the baseline algorithm at a much faster rate than the round robin. The least connected algorithm performs well for medium to high workload. At very low load, the average waiting time is two to six times higher than the baseline algorithm but the absolute value between these two waiting times is very small.