Abstract
Cloud computing has attracted great interest from both academic and industrial communities. Different paradigms, architectures and applications based on the concept of cloud have emerged. Although many of them have been quite successful, efforts are mainly focusing on the study and implementation of particular setups. However, a generic and more flexible solution for cloud construction is missing. In this paper, we present a composition-based approach for cloud computing (compositional cloud) using Imperial College Cloud (IC Cloud) as a demonstration example. Instead of studying a specific cloud computing system, our approach aims to enable a generic framework where various cloud computing architectures and implementation strategies can be systematically studied. With our approach, cloud computing providers/adopters are able to design and compose their own systems in a quick and flexible manner. Cloud computing systems will no longer be in fixed shapes but will be dynamic and adjustable according to the requirements of different application domains.
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Yi-Ke Guo graduated in computer science from Tsinghua University, PRC and received Ph.D. degree in computational logic and declarative programming at Imperial College London. He has been working in the area of data intensive analytical computing since 1995 when he was the technical director of Imperial College Parallel Computing Centre. He is currently a professor in computing science in the Department of Computing, Imperial College London, UK. During the last 10 years, he has been leading the data mining group of the department to carry out many research projects, including some major UK e-science projects such as discovery net on grid based data analysis for scientific discovery, MESSAGE on wireless mobile sensor network for environment monitoring, Biological Atlas of Insulin Resistance (BAIR) on system biology for diabetes study. He has been focusing on applying data mining technology to scientific data analysis in the fields of life science and healthcare, environment science and security.
His research interests include large scale scientific data analysis, data mining algorithms and applications, parallel algorithms, and cloud computing.
Li Guo received Ph.D. degree in artificial intelligence at the University of Edinburgh, UK. He has been working in the area of grid computing and cloud computing since 2006. He is currently a research associate in computing science in the Department of Computing, Imperial College London, UK. During the last 5 years, he has been involved in major grid and cloud related EU and UK projects. He is the chief architect of Imperial College Cloud platform.
His research interests include large scale distributed system, intelligent applications, and cloud computing.
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Guo, YK., Guo, L. IC cloud: Enabling compositional cloud. Int. J. Autom. Comput. 8, 269–279 (2011). https://doi.org/10.1007/s11633-011-0582-4
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DOI: https://doi.org/10.1007/s11633-011-0582-4