Implementation Design and Performance Evaluation of Partial Recall Method for Accessing Large Size of Data by Utilizing Cloud on-Ramp

Abstract

Cloud storage becomes popular, but low data-access performance through WANs (wide area networks) is becoming an issue. We proposed a cloud-storage cache, called “cloud on-ramp” (CoR), located at remote offices and connected to the cloud storage at a data center. Users access the CoR, which stores frequently accessed data as a cache, through a LAN (local area network). In this way, the CoR can improve access performance in case of cache hits; however, delays due to cache misses are a challenge because the data need to be transferred through a WAN. To ensure that applications have reliable access to data even in the case of a cache miss, we also proposed a recall method called “partial recall”. After the CoR receives the predefined size of partial data, it returns the data to the client. In this paper, we propose an implementation design of the partial recall. The method is formulated by utilizing a stochastic Petri-net model, and a proper size of partial data is determined through Petri-net simulation. Also, its data access performance improvement is evaluated in comparison with a conventional method, and a limit performance of partial recall method is measured.