F. Eichhorn, W. Dargie, Christoph Möbius, K. Rybina
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In reality, the workload of data centres fluctuates as a function of time and servers frequently experience both overloading and underutilised conditions. In this paper we introduce the HAECubie demonstrator we developed and deployed to experimentally evaluate the scope and usefulness of dynamic workload consolidation in a server cluster and to quantitatively analyse the relationship between energy/power consumption and the utility (performance) that can be achieved through workload consolidation. Our demonstrator is a video hosting platform and enables Internet users to stream videos of variable length. The number of users accessing the HAECubie as well as the duration of videos they stream are modelled as stochastic processes based on realistic estimation of the workload of existing video hosting platforms.","PeriodicalId":117136,"journal":{"name":"2015 24th International Conference on Computer Communication and Networks (ICCCN)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"HAECubie: A Highly Adaptive and Energy-Efficient Computing Demonstrator\",\"authors\":\"F. Eichhorn, W. Dargie, Christoph Möbius, K. Rybina\",\"doi\":\"10.1109/ICCCN.2015.7288415\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The amount of data that are computed, stored, and shared over the Internet is rising at an unprecedented scale. This has necessitated more servers to be deployed and drastic improvement in the capacity of individual servers. However, several independent studies also reveal that resources are not optimally utilised in most existing data centres and server clusters. Since the introduction of server virtualization and cloud computing, the research community has proposed several workload aggregation and dynamic consolidation techniques, however, most of these techniques are either theoretical and rely on simulation environments or use real servers but static workloads or benchmarks. In reality, the workload of data centres fluctuates as a function of time and servers frequently experience both overloading and underutilised conditions. In this paper we introduce the HAECubie demonstrator we developed and deployed to experimentally evaluate the scope and usefulness of dynamic workload consolidation in a server cluster and to quantitatively analyse the relationship between energy/power consumption and the utility (performance) that can be achieved through workload consolidation. Our demonstrator is a video hosting platform and enables Internet users to stream videos of variable length. 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HAECubie: A Highly Adaptive and Energy-Efficient Computing Demonstrator
The amount of data that are computed, stored, and shared over the Internet is rising at an unprecedented scale. This has necessitated more servers to be deployed and drastic improvement in the capacity of individual servers. However, several independent studies also reveal that resources are not optimally utilised in most existing data centres and server clusters. Since the introduction of server virtualization and cloud computing, the research community has proposed several workload aggregation and dynamic consolidation techniques, however, most of these techniques are either theoretical and rely on simulation environments or use real servers but static workloads or benchmarks. In reality, the workload of data centres fluctuates as a function of time and servers frequently experience both overloading and underutilised conditions. In this paper we introduce the HAECubie demonstrator we developed and deployed to experimentally evaluate the scope and usefulness of dynamic workload consolidation in a server cluster and to quantitatively analyse the relationship between energy/power consumption and the utility (performance) that can be achieved through workload consolidation. Our demonstrator is a video hosting platform and enables Internet users to stream videos of variable length. The number of users accessing the HAECubie as well as the duration of videos they stream are modelled as stochastic processes based on realistic estimation of the workload of existing video hosting platforms.