Elastic Cloud Caches for Accelerating Service-Oriented Computations

Computing as a utility, that is, on-demand access to computing and storage infrastructure, has emerged in the form of the Cloud. In this model of computing, elastic resource allocation, i.e., the ability to scale resource allocation for specific applications, 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 a Cloud setting. 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 public Cloud, a detailed evaluation of our system has been performed, considering speed up and elastic scalability in terms resource allocation and relaxation.