Optimizing Distributed System Performance via Adaptive Middleware Load Balancing

Load balancing middleware is used extensively to improve scalability and overall system throughput in distributed systems. Many load balancing middleware services are simplistic, however, since they are geared only for specific usecases and environments. These limitations make it hard to use the same load balancing service for anything other than the distributed application it was designed for originally. This lack of generality forces continuous re-development of application-specific load balancing services. Not only does re-development increase deployment costs of distributed applications, but it also increases the potential of producing nonoptimal load balancing implementations since proven load balancing service optimizations cannot be reused directly. This paper presents a set of load balancing service features that address many existing middleware load balancing service inadequacies, such as lack of server-side transparency, centralized load balancing, sole support for stateless replication, fixed load monitoring granularities, lack of fault tolerant load balancing, non-extensible load balancing algorithms, and simplistic replica management. All the capabilities described in this paper are currently under development for the next generation of middleware-based load balancing service distributed with our CORBA-compliant ORB (TAO).