Adaptive popularity-driven replica placement in hierarchical data grids

Data grids support access to widely distributed storage for large numbers of users accessing potentially many large files. Efficient access is hindered by the high latency of the Internet. To improve access time, replication at nearby sites may be used. Replication also provides high availability, decreased bandwidth use, enhanced fault tolerance, and improved scalability. Resource availability, network latency, and user requests in a grid environment may vary with time. Any replica placement strategy must be able to adapt to such dynamic behavior. In this paper, we describe a new dynamic replica placement algorithm, Popularity Based Replica Placement (PBRP), for hierarchical data grids which is guided by file “popularity”. Our goal is to place replicas close to clients to reduce data access time while still using network and storage resources efficiently. The effectiveness of PBRP depends on the selection of a threshold value related to file popularity. We also present Adaptive-PBRP (APBRP) that determines this threshold dynamically based on data request arrival rates. We evaluate both algorithms using simulation. Results for a range of data access patterns show that our algorithms can shorten job execution time significantly and reduce bandwidth consumption compared to other dynamic replication methods.