Co-allocation in Data Grids: A Global, Multi-user Perspective

Several recent studies suggest that co-allocation techniques can improve user performance for distributed data retrieval in replicated grid systems. These studies demonstrate that co-allocation techniques can improve network bandwidth and network transfer times by concurrently utilizing as many data grid replicas as possible. However, these prior studies evaluate their techniques from a single user’s perspective and overlook evaluations of system wide performance when multiple users are using co-allocation techniques. In our study, we provide multi-user evaluations of a co-allocation technique for replicated data in a controlled grid environment. We find that co-allocation works well under low-load conditions when there are only a few users using co-allocation. However, co-allocation works very poorly for medium and high-load conditions since the response time for co-allocating users grows rapidly as the number of grid users increases. The decreased performance for co-allocating users can be directly attributed to the increased workload that their greedy retrieval technique places on the replicas in the grid. Overall, we determine that uninformed, blind utilization of greedy co-allocation techniques by multiple users is detrimental to global system performance.