Abstract
In recent years, energy efficiency has emerged as one of the most important design requirements for modern computing systems, ranging from single servers to data centers and Clouds, as they continue to consume an enormous amount of electrical power. Cloud computing can be used to achieve energy efficiency through efficient task scheduling in the distributed environment. This efficient task scheduling helps to improve resource utilization, which, in turn, helps to minimize energy consumption. In this paper, we work toward minimizing energy of directed acyclic graph-structured applications on heterogeneous cloud system. The paper also combines power-aware list-based scheduling algorithm with dynamic voltage and frequency scaling (DVFS) technique for real-time tasks (PL-DVFS) to maintain the quality of service while considering tasks deadlines. The goal of the approach is to improve performance and overall reduced energy consumption comprising CPU energy (busy and idle) and communication energy. Experiments conducted with synthetic workflow graphs clearly demonstrate the advantage of the proposed approach.
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Safari, M., Khorsand, R. PL-DVFS: combining Power-aware List-based scheduling algorithm with DVFS technique for real-time tasks in Cloud Computing. J Supercomput 74, 5578–5600 (2018). https://doi.org/10.1007/s11227-018-2498-z
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DOI: https://doi.org/10.1007/s11227-018-2498-z