The Influence of Different Workload Descriptions on a Heuristic Load Balancing Scheme
IEEE Transactions on Software Engineering
httperf—a tool for measuring web server performance
ACM SIGMETRICS Performance Evaluation Review
Server load balancing
Euro-Par '96 Proceedings of the Second International Euro-Par Conference on Parallel Processing-Volume II
Messaging on Gigabit Ethernet: Some Experiments with GAMMA and Other Systems
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
Performance comparison of middleware architectures for generating dynamic web content
Proceedings of the ACM/IFIP/USENIX 2003 International Conference on Middleware
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Clusters are a popular platform to build highly available and scalable service solutions. Usually, the front-end dispatcher distributes the load to the back-end servers in a round-robin fashion or according to current server load based on external load parameters. The use of server weights is very popular to improve the load balancing in case of heterogeneous server machines. Correctly determined weights are crucial to the quality of the distribution. While the determination of weights can be done in small and static environments, it can hardly be done in dynamic or heterogeneous environments. In this paper, we present a credit-based algorithm for server load balancing with a complexity of O(1) that adapts to heterogeneous environments without the need to specify server weights. This approach is able to self-adapt to heterogeneous servers and heterogeneous workloads. Credits are calculated by using available communication endpoints. We present simulation results as well as experimental results with our prototype where the update of credit information is done efficiently using the RDMA capabilities of InfiniBand.