Realizing Optimization Opportunities for Distributed Applications in the Middleware Layer by Utilizing InDiGO Framework

InDiGO framework provides an infrastructure to develop generic but customizable middleware services. It also provides tools to customize the middleware algorithms for specific applications. Such customization allows one to optimize algorithms by removing communication which is redundant in the context of a specific application. In this paper, we apply InDiGO framework to study a class of bidding distributed applications. In particular, we will study how optimization level is affected by varying several application parameters, such as number of clusters, number of components per cluster, number of clusters with local ordering and number of components per process. The results of this study will help us to answer questions like: What type of application information is useful for optimization in InDiGO framework? or How does the application structure or its size affect the level of optimization? We present experimental results to demonstrate the optimizations when our infrastructure is utilized.