Performance Analysis of Session-Level Load Balancing Algorithms

Load balancing (LB) is crucial for the efficient operation of big server clusters. In the past, many different LB strategies on the request level have been developed with great effectiveness in parallel applications. However, the LB problem is not yet solved completely; new applications and architectures require new features. In particular, secure environments require that LB is done at session level instead of request level; that is, once a session has been assigned to a server, all subsequent service requests are directed to the assigned server. Despite the fact that many commercial products have been brought to the market to implement LB at the session level, little insight has been obtained into the efficiency of such session-level LB algorithms, leaving ample room for performance improvement and optimization. Motivated by this, we study session-level LB with a focus on algorithms that are simple and easy to implement in real systems. The performance of the load balancer is highly dependent on the request profiles of the different sessions and the information that is available for decision making. Wemake this trade-off between the information that is available to the load balancer and the efficiency of the algorithm explicit by developing new algorithms, and compare their efficiency with existing algorithms. The algorithms are mainly based on the load of each server and the number of active sessions running on them. Extensive validation in an experimental setting shows that our algorithms outperform the existing ones, and as such, provide a simple, easy-toimplement yet effective means to improve the efficiency of large server clusters.