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Issue title: Soft Computing and Intelligent Systems: Techniques and Applications
Guest editors: Sabu M. Thampi, El-Sayed M. El-Alfy and Ljiljana Trajkovic
Article type: Research Article
Authors: Renugadevi, T.; * | Geetha, K.
Affiliations: School of Computing, SASTRA Deemed University, Thanjavur, Tamil Nadu, India
Correspondence: [*] Corresponding author. T. Renugadevi. E-mail: [email protected].
Abstract: Management of IT services is rapidly adapting to the cloud computing environment due to optimized service delivery models. Geo distributed cloud data centers act as a backbone for providing fundamental infrastructure for cloud services delivery. Conversely, their high growing energy consumption rate is the major problem to be addressed. Cloud providers are in a hunger to identify different solutions to tackle energy management and carbon emission. In this work, a multi-cloud environment is modeled as geographically distributed data centers with varying solar power generation corresponding to its location, electricity price, carbon emission, and carbon tax. The energy management of the workload allocation algorithm is strongly dependent on the nature of the application considered. The task deadline and brownout information is used to bring in variation in task types. The renewable energy-aware workload allocation algorithm adaptive to task nature is proposed with migration policy to explore its impact on carbon emission, total energy cost, brown and renewable power consumption.
Keywords: Sustainable data centers, carbon footprint, brownout, migration, green energy, workload allocation
DOI: 10.3233/JIFS-189887
Journal: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 5, pp. 5677-5689, 2021
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