ABSTRACT: Computing as a utility, that is, on-demand access to computing and storage
infrastructure, has emerged as the Cloud. In this model of computing, elastic resource allocation, i.e., the ability to scale resources, should be optimized to manage cost versus performance. Meanwhile, the wake of the information sharing/mining age is invoking a pervasive sharing of Web services and data sets in the Cloud, and at the same time, many data-intensive scientific applications are being expressed as these services. In this paper, we explore an approach to accelerate service processing in the Cloud. We have developed a cooperative scheme for caching data output from services for reuse. We propose algorithms for scaling our cache system up during peak querying times, and back down to save costs. Using the Amazon EC2 Cloud, a detailed evaluation of our system has
been performed, considering speed up and elastic scalability in terms resource
allocation and relaxation.
David Abramson (Chair) - Monash University
David Chiu - Washington State University Vancouver