Optimizing Image Content-Based Query Applications over High Latency Communication Media

One of the earliest applications that explored the power and flexibility of the grid computing paradigm was medical image matching. A typical characteristic of such applications is the large communication overheads due to the bulk of data that have to be transfered to the compute nodes. In this paper we study the problem of optimizing such applications under a broad model that incorporates not only communication overheads but also the existence of local data caches that could exist as a result of previous queries. Our analytical approach is not only complimented by a theorem that shows how to arrange the sequence of operations in order to minimize the overall cost, but also yields closed-form solutions to the partitioning problem. For the case where large load imbalances (due to big differences in cache sizes) prevent the calculation of a closed-form solution, we propose an algorithm for optimizing load redistribution. The paper is concluded by a simulation study that evaluates the impact of our analytical approach