Blacklist muti-objective genetic algorithm for energy saving in heterogeneous environments
| Autor: | Josep L. Lérida, Eloi Gabaldon, Fernando Guirado, Jordi Planes |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
020203 distributed computing
Job shop scheduling Computer science Distributed computing 020206 networking & telecommunications Symmetric multiprocessor system 02 engineering and technology Energy consumption Weighted blacklist Multi-objective optimization Blacklist Scheduling (computing) Theoretical Computer Science Genetic algorithm Hardware and Architecture 0202 electrical engineering electronic engineering information engineering Energy aware scheduling Software Information Systems |
| Zdroj: | Recercat. Dipósit de la Recerca de Catalunya instname Repositorio Abierto de la UdL Universitad de Lleida |
| Popis: | Reducing energy consumption in large-scale computing facilities has become a major concern in recent years. Most of the techniques have focused on determining the computing requirements based on load predictions and thus turning unnecessary nodes on and off. Nevertheless, once the available resources have been configured, new opportunities arise for reducing energy consumption by providing optimal matching of parallel applications to the available computing nodes. Current research in scheduling has concentrated on not only optimizing the energy consumed by the processors but also optimizing the makespan, i.e., job completion time. The large number of heterogeneous computing nodes and variability of application-tasks are factors that make the scheduling an NP-Hard problem. Our aim in this paper is a multi-objective genetic algorithm based on a weighted blacklist able to generate scheduling decisions that globally optimizes the energy consumption and the makespan. This research is partly supported by the European Union FEDER (CAPAP-H5 network TIN2014-53522-REDT) and MEyC-Spain under contract TIN2014-53234-C2-2-R and TIN2015- 71799-C2-2-P. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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