Abstract
In Cloud computing, energy consumption and resource utilization are strongly coupled. Specifically, resources with a low utilization rate still consume an unacceptable amount of energy compared to the energy consumption of a fully utilized or sufficiently loaded Cloud computing. To increase resource utilization, task consolidation is an effective technique, greatly enabled by virtualization technologies, which facilitate the concurrent execution of several tasks and, in turn, reduce energy consumption. The authors use two energy-conscious heuristics for task consolidation: MaxUtil, which aims to maximize resource utilization, and Energy-Conscious Task Consolidation (ECTC) which explicitly takes into account both active and idle energy consumption. ECTC computes the energy consumption based on an objective function derived from findings reported in the literature. The chapter deals with the Cloud computing, energy models, and task consolidation algorithms. It describes the complementarity approach and the related mathematical model. The chapter finally summarizes the simulation results and discussions.
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