2009/01/01 by Christian Vecchiola, Suraj Pandey, Rajkumar Buyya
Computer Science · Decision Sciences · #Cloud Computing and Resource Management #Cloud computing #Cloud computing security #Computer network #Computer science #Context (archaeology) #Data science #Database #Distributed and Parallel Computing Systems #Distributed computing #Operating system #Provisioning #Quality of service #Scientific Computing and Data Management #Service (business) #Utility computing #Variety (cybernetics) #Workflow #cs.DC
paper · pdf · doi:10.1109/i-span.2009.150
published as Proceedings of the 10th International Symposium on Pervasive Systems, Algorithms and Networks (I-SPAN 2009, IEEE CS Press, USA), Kaohsiung, Taiwan, December 14-16, 2009 · 13 pages, 9 figures, conference paper
openalex publication_date 2009/01/01 · arxiv created 2009/10/11 · arxiv updated 2016/11/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
Scientific computing often requires the availability of a massive number of computers for performing large scale experiments. Traditionally, these needs have been addressed by using high-performance computing solutions and installed facilities such as clusters and super computers, which are difficult to setup, maintain, and operate. Cloud computing provides scientists with a completely new model of utilizing the computing infrastructure. Compute resources, storage resources, as well as applications, can be dynamically provisioned (and integrated within the existing infrastructure) on a pay per use basis. These resources can be released when they are no more needed. Such services are often offered within the context of a service level agreement (SLA), which ensure the desired quality of service (QoS). Aneka, an enterprise cloud computing solution, harnesses the power of compute resources by relying on private and public clouds and delivers to users the desired QoS. Its flexible and service based infrastructure supports multiple programming paradigms that make Aneka address a variety of different scenarios: from finance applications to computational science. As examples of scientific computing in the cloud, we present a preliminary case study on using Aneka for the classification of gene expression data and the execution of fMRI brain imaging workflow.