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Sustainability-based Framework for Virtual Machines Migration Among Cloud Data Centers - 2021

Research Area:  Cloud Computing

Abstract:

Cloud computing services have achieved great popularity and wide adoption thanks to their flexible operation on demand. These services are hosted in Cloud Data Centers that integrate thousands of computers, storage and communication networks whose use entails a high consumption of electrical energy. Renewable energy-based cloud data centers are replacing traditional energy power grids with sustainable energy sources such as wind or photovoltaic energy, for instance. In this respect, in Modular Data Centers the workload could be transferred to different nodes among different cloud data centers geographically distributed based on their access to renewable energy to allow its processing in those locations where renewable energy is available. In this sense, in order to take advantage of this concept of sustainable processing, in addition to efficient load and resource management, this paper presents a framework based on Cloudsim for sustainability-based system for the migration of virtual machines among cloud data centers which can be used in order to simulate different strategies and to make conclusions on its comparison. In addition, to test the behavior the proposed framework, an approach for migrations among datacenters has been tested in several victual machines migration scenarios, so that it is clearly shown how the proposed framework improves previous capabilities of Cloudsim, and shows how follows the renewable policies take advantage of renewable energy in terms of energy consumption, while preserving the QoS in terms of execution time.

Author(s) Name:  Doraid Seddiki; Sebastián García Galán; Enrique Muñoz Expósito; Manuel Valverde Ibañez; Tomasz Marciniak; Rocío J. Pérez De Prado

Journal name:  

Conferrence name:  2021 15th International Conference on Signal Processing and Communication Systems (ICSPCS)

Publisher name:  IEEE

DOI:  10.1109/ICSPCS53099.2021.9660237

Volume Information: