An energy consumption model and analysis tool for Cloud computing environments
- Authors: Chen, Feifei , Schneider, Jean-Guy , Yang, Yun , Grundy, John , He, Qiang
- Date: 2012
- Type: Text , Conference paper
- Relation: 2012 First International Workshop on Green and Sustainable Software (GREENS) : Part of the 34th International Conference on Software Engineering (ICSE) p. 45-50
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- Description: Cloud computing delivers computing as a utility to users worldwide. A consequence of this model is that cloud data centres have high deployment and operational costs, as well as significant carbon footprints for the environment. We need to develop Green Cloud Computing (GCC) solutions that reduce these deployment and operational costs and thus save energy and reduce adverse environmental impacts. In order to achieve this objective, a thorough understanding of the energy consumption patterns in complex Cloud environments is needed. We present a new energy consumption model and associated analysis tool for Cloud computing environments. We measure energy consumption in Cloud environments based on different runtime tasks. Empirical analysis of the correlation of energy consumption and Cloud data and computational tasks, as well as system performance, will be investigated based on our energy consumption model and analysis tool. Our research results can be integrated into Cloud systems to monitor energy consumption and support static or dynamic system-level optimisation.
Automated analysis of performance and energy consumption for cloud applications
- Authors: Chen, Feifei , Grundy, John , Schneider, Jean-Guy , Yang, Yun , He, Qiang
- Date: 2014
- Type: Text , Conference paper
- Relation: Proceedings of the 5th ACM/SPEC international conference on Performance engineering p. 39-50
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- Description: In cloud environments, IT solutions are delivered to users via shared infrastructure. One consequence of this model is that large cloud data centres consume large amounts of energy and produce significant carbon footprints. A key objective of cloud providers is thus to develop resource provisioning and management solutions at minimum energy consumption while still guaranteeing Service Level Agreements (SLAs). However, a thorough understanding of both system performance and energy consumption patterns in complex cloud systems is imperative to achieve a balance of energy efficiency and acceptable performance. In this paper, we present StressCloud, a performance and energy consumption analysis tool for cloud systems. StressCloud can automatically generate load tests and profile system performance and energy consumption data. Using StressCloud, we have conducted extensive experiments to profile and analyse system performance and energy consumption with different types and mixes of runtime tasks. We collected fine-grained energy consumption and performance data with different resource allocation strategies, system configurations and workloads. The experimental results show the correlation coefficients of energy consumption, system resource allocation strategies and workload, as well as the performance of the cloud applications. Our results can be used to guide the design and deployment of cloud applications to balance energy and performance requirements.