A prediction-based and cost-based replica replacement algorithm research and simulation

For the high latencies of the Internet, it becomes a big challenge to access such large and widely distributed data fast and efficiently on data grids. To address this challenge, large amounts of data need to be replicated in multiple copies at several distributed sites. However, the number and size of storage are limited. So a good replacement algorithm is important to the performance and efficiency of replication technologies. In this paper, we introduce a new replica replacement algorithm that combines prediction factors and replacement cost factors together. Through predicting the popularity of replica in future time windows, hot spot replica is kept to improve mean job time. Cost factors are most concerned about replica replacement cost such as network latency and bandwidth, replica size and system reliability. We present a PC-based replacement algorithm that achieves a good balance between mean job time and bandwidth resource consumption. By using OptorSim simulator to compare our PC-based algorithm with traditional replacement algorithm, we find the results show that our PC-based algorithm improves performance and efficiency of the data access within the overall data grid.