Authors:
Javier Conejero
1
;
Omer Rana
2
;
Peter Burnap
2
;
Jeffrey Morgan
2
;
Carmen Carrion
1
and
Blanca Caminero
1
Affiliations:
1
University of Castilla-La Mancha, Spain
;
2
Cardiff University, United Kingdom
Keyword(s):
Cloud Computing, Power Consumption, Hadoop, OpenNebula, Social Media Analysis.
Related
Ontology
Subjects/Areas/Topics:
Big Data Cloud Services
;
Cloud Application Architectures
;
Cloud Applications Performance and Monitoring
;
Cloud Computing
;
Cloud Computing Enabling Technology
;
Monitoring of Services, Quality of Service, Service Level Agreements
;
Platforms and Applications
Abstract:
Energy efficiency is often identified as one of the key reasons for migrating to Cloud environments. It is often stated that a data centre hosting the Cloud environment is likely to achieve greater energy efficiency (at a reduced cost) compared to a local deployment. With increasing energy prices, it is also estimated that a large percentage of operational costs within a Cloud environment can be attributed to energy. In this work, we investigate and measure energy consumption of a number of virtual machines running the Hadoop system, over an OpenNebula Cloud. Our workload is based on sentiment analysis undertaken over Twitter messages. Our objective is to understand the tradeoff between energy efficiency and performance for such a workload. From our results we generalise and speculate on how such an analysis could be used as a basis to establish a Service Level Agreement with a Cloud provider – especially where there is likely to be a high level of variability (both in performance an
d energy use) over multiple runs of the same application (at different times).
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