Title
Particle Swarm Optimization Scheduling for Energy Saving in Cluster Computing Heterogeneous Environments
Abstract
Reducing energy consumption in large-scale computing facilities has become a major concern in recent years. Most techniques have been 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. Those techniques have received little attention. The large number of computing nodes, heterogeneity and variability of application-tasks are factors that turn the scheduling into an NP-Hard problem. In this paper, we present a novel approach by using a Particle Swarm Optimization (PSO) based heuristic to generate scheduling decisions that minimize the overall energy consumption.
Year
DOI
Venue
2016
10.1109/W-FiCloud.2016.71
2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)
Keywords
Field
DocType
Particle Swarm Optimization,Energy Saving,Federated Clusters,Scheduling,Co-allocation
Particle swarm optimization,Mathematical optimization,Heuristic,Optimal matching,Scheduling (computing),Computer science,Multi-swarm optimization,Energy consumption,Computer cluster,Distributed computing
Conference
ISBN
Citations 
PageRank 
978-1-5090-3947-0
2
0.35
References 
Authors
16
4
Name
Order
Citations
PageRank
Eloi Gabaldon151.05
Fernando Guirado28912.69
Josep Lluis Lérida3293.28
Jordi Planes448631.38