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2013 IEEE 5th International Conference on Cloud Computing Technology and Science (2013)
Bristol, United Kingdom United Kingdom
Dec. 2, 2013 to Dec. 5, 2013
pp: 80-87
Cloud computing has enabled a wide array of applications to be exposed as elastic cloud services. While the number of such services has rapidly increased, there is a lack of techniques for supporting cross-layered multi-level monitoring and analysis of elastic service behavior. In this paper we introduce novel concepts, namely elasticity space and elasticity pathway, for understanding elasticity of cloud services, and techniques for monitoring and evaluating them. We present MELA, a customizable framework, which enables service providers and developers to analyze cross-layered, multi-level elasticity of cloud services, from the whole cloud service to service units, based on service structure dependencies. Besides support for real-time elasticity analysis of cloud service behavior, MELA provides several customizable features for extracting functions and patterns that characterize that behavior. To illustrate the usefulness of MELA, we conduct several experiments with a realistic data-as-a-service in an M2M cloud platform.
Elasticity, Monitoring, Topology, Extraterrestrial measurements, Throughput, Runtime,elasticity analysis, elastic computing, cloud service, elasticity monitoring
Daniel Moldovan, Georgiana Copil, Hong-Linh Truong, Schahram Dustdar, "MELA: Monitoring and Analyzing Elasticity of Cloud Services", 2013 IEEE 5th International Conference on Cloud Computing Technology and Science, vol. 01, no. , pp. 80-87, 2013, doi:10.1109/CloudCom.2013.18
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