The Design and Performance of an Adaptive CORBA Load Balancing Service

CORBA is increasingly popular as distributed object computing middleware for systems with stringent quality of service (QoS) requirements, including scalability and dependability. One way to improve the scalability and dependability of CORBA-based applications is to balance system processing load among multiple server hosts. Load balancing can help improve system scalability by ensuring that client application requests are distributed and processed equitably across a group of servers. Likewise, it can help improve system dependability by adapting dynamically to system configuration changes that arise from hardware or software failures. This paper presents four contributions to research on CORBA-based load balancing. First, we describe deficiencies with common load-balancing techniques, such as introducing unnecessary overhead or not adapting dynamically to changing load conditions. Second, we present a novel adaptive load balancing service that can be implemented efficiently using standard CORBA features. Third, we describe the key design challenges we faced when adding this load balancing service to our CORBA ORB (TAO) and outline how we resolved the challenges by applying patterns. Finally, we present the results of benchmark experiments that evaluate the pros and cons of different load balancing strategies empirically by measuring the overhead of each strategy and showing how well each strategy balances system load.

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