Simgrid: A Toolkit for the Simulation of Application Scheduling
CCGRID '01 Proceedings of the 1st International Symposium on Cluster Computing and the Grid
Handbook of Scheduling: Algorithms, Models, and Performance Analysis
Handbook of Scheduling: Algorithms, Models, and Performance Analysis
SimGrid: A Generic Framework for Large-Scale Distributed Experiments
UKSIM '08 Proceedings of the Tenth International Conference on Computer Modeling and Simulation
Perspectives on grid computing
Future Generation Computer Systems
Task scheduling with ANN-based temperature prediction in a data center: a simulation-based study
Engineering with Computers
Coordinated rescheduling of Bag-of-Tasks for executions on multiple resource providers
Concurrency and Computation: Practice & Experience
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Energy consumption in High Performance Computing (HPC) has become an important issue in the past few years. The performance gain obtained by these environments is matched by a proportional increase of energy use. Example of such environments are computational grids, which are used in several academic and enterprise projects. Given this scenario, researchers have been trying to reduce the energy consumption while minimizing performance loss at the same time. This work proposes the use of energy-aware scheduling for energy efficiency management in computational grids. Our solution exploits the main existing approaches in the literature to reduce energy consumption in HPC environments: management of idle resources and energy-aware scheduling algorithms. We evaluate our proposed approach in a simulation environment and the algorithm was compared to other five traditional scheduling algorithms that do not consider energy features. Results show an energy reduction of up to 182.90% combined with a performance loss up to 27.78% in the best cases.