Research on Energy-Saving Algorithms with Migration Energy Consumption in Heterogeneous Cloud Environment

Abstract:

Cloud computing is a new emerging paradigm which delivers an infrastructure, platform and software as services in a pay-as-you-go model. However, with the development of cloud computing, the large-scale data centers consume huge amounts of electrical energy resulting in high operational costs and environment problem. Nevertheless, existing energy-saving algorithms based on live migration don’t consider the migration energy consumption, and most of which are designed for homogeneous cloud environment. In this paper, we take the first step to model energy consumption in heterogeneous cloud environment with migration energy consumption. Based on this energy model, we design energy-saving Best fit decreasing (ESBFD) algorithm and energy-saving first fit decreasing (ESFFD) algorithm. We further provide results of several experiments using traces from PlanetLab in CloudSim. The experiments show that the proposed algorithms can effectively reduce the energy consumption of data center in the heterogeneous cloud environment compared to existing algorithms like NEA, DVFS, ST (Single Threshold) and DT (Double Threshold).

• Periodical: Advanced Materials Research (Volumes 986-987)
• Pages: 1383-1386
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.986-987.1383
• Online since: July 2014
• Authors: Zhen Xing Yang*, He Guo, Yu Long Yu, Yu Xin Wang
• Keywords: Data Center, Energy-Saving, Heterogeneous Cloud, Migration Energy Consumption, Virtual Machine Migration

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