caa a22 4500 606244859 CHVBK 20210128101332.0 cr unu---uuuuu 210128e20151201xx s 000 0 eng 10.1007/s10723-015-9349-4 doi (NATIONALLICENCE)springer-10.1007/s10723-015-9349-4 Lent Ricardo University of Houston, Texas, USA aut Grid Scheduling with Makespan and Energy-Based Goals [Elektronische Daten] [Ricardo Lent] The need for better energy efficiency in grid computing is significant given the massive amount of energy dissipated by large grids. We approximate the optimal allocation of compute nodes to a job stream, with each job consisting of multiple tasks, and while considering both the computing requirements and a desired balance of shorter makespans and lower energy consumption. The approach is widely applicable to many grid scenarios and does not require the scheduler to have administrative rights to change the workers' DVFS or hibernation state. A discrete particle swarm optimisation (PSO) determines the worker assignments based on estimations of the tasks' service times and energy consumption using an online learning process, and taking into account pending task executions from prior jobs. The performance of the proposed system is then evaluated through extensive Monte Carlo simulations using traces of real multi-threaded program executions on representative computer hardware. The results demonstrate the latent energy savings that are possible in grid computing through an energy-aware task scheduling. Springer Science+Business Media Dordrecht, 2015 Grid computing nationallicence Green computing nationallicence Particle swarm optimisation nationallicence Computer energy measurements nationallicence Journal of Grid Computing Springer Netherlands 13/4(2015-12-01), 527-546 1570-7873 13:4<527 2015 13 10723 https://doi.org/10.1007/s10723-015-9349-4 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s10723-015-9349-4 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Lent Ricardo University of Houston, Texas, USA aut NATIONALLICENCE 773 0- Journal of Grid Computing Springer Netherlands 13/4(2015-12-01), 527-546 1570-7873 13:4<527 2015 13 10723