Enhancement of Anticipative Recursively-Adjusting Mechanism for Redundant Parallel File Transfer in Data Grids

In data grid, co-allocation architecture can be used to enable parallel transferring of data file from multiple replicas which stored in the different grid sites. Some schemes base on co-allocation model were proposed and used to exploit the different transfer rates among various client-server network links and to adapt dynamic rate fluctuations by dividing data into fragment. These schemes showed the more fragments used the more performance conducted when data transfer in parallel with evidence. In our previous work, we propose a scheme named anticipative recursively-adjusting mechanism (ARAM) in previous research work. The best thing is performance tuning through the alpha value, it¿s rely on special feature to adapt different network situations in a data grid environment. In this paper, the TCP bandwidth estimation model (TCPBEM) is used to evaluate dynamic link state by detect TCP throughput and packet lost rate between grid nodes. We integrate the model into ARAM, called anticipative recursively-adjusting mechanism plus (ARAM+), that can be more reliable and reasonable then previous one. In the meanwhile, we also design a burst mode which could increase transfer rate of ARAM+. This approach not only adapts worst network link but also speedup the overall performance.