An interoperable and self-adaptive approach for SLA-based service virtualization in heterogeneous Cloud environments |
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Affiliation: | 2. Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea;3. Department of Radiology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea;1. Key Laboratory of Earth and Planetary Physics, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, China;2. School of Mathematics and Computer Science, Ningxia University, Yinchuan, 750021, China;1. Institute for Problems in Mechanics, Russian Academy of Sciences, 101 Vernadsky Avenue, Bldg 1, Moscow 119526, Russia;2. Bauman Moscow State Technical University, 5 Second Baumanskaya Street, Moscow 105005, Russia;3. National Research Nuclear University MEPhI, 31 Kashirskoe Shosse, Moscow 115409, Russia;4. Cardiff University, Heath Park, Cardiff CF14 4XY, UK |
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Abstract: | Cloud computing is a newly emerged computing infrastructure that builds on the latest achievements of diverse research areas, such as Grid computing, Service-oriented computing, business process management and virtualization. An important characteristic of Cloud-based services is the provision of non-functional guarantees in the form of Service Level Agreements (SLAs), such as guarantees on execution time or price. However, due to system malfunctions, changing workload conditions, hard- and software failures, established SLAs can be violated. In order to avoid costly SLA violations, flexible and adaptive SLA attainment strategies are needed. In this paper we present a self-manageable architecture for SLA-based service virtualization that provides a way to ease interoperable service executions in a diverse, heterogeneous, distributed and virtualized world of services. We demonstrate in this paper that the combination of negotiation, brokering and deployment using SLA-aware extensions and autonomic computing principles are required for achieving reliable and efficient service operation in distributed environments. |
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