Paper Info
Title
Communication-aware task scheduling and voltage selection for total energy minimization in a multiprocessor system using Ant Colony Optimization.
Abstract
Energy consumption is a key parameter when highly computational tasks should be performed in a multiprocessor system. In this case, in order to reduce total energy consumption, task scheduling and low-power methodology should be combined in an efficient way. This paper proposes an algorithm for off-line communication-aware task scheduling and voltage selection using Ant Colony Optimization. The proposed algorithm minimizes total energy consumption of an application executing on a homogeneous multiprocessor system. The artificial agents explore the search space based on stochastic decision-making using global heuristic information with total energy consumption and local heuristic information with interprocessor communication volume. In search space exploration, both voltage selection and the dependencies between tasks are considered. The pheromone trails are updated by normalizing the total energy consumption. The pheromone trails represent the global heuristic information in order to utilize all entire energy consumption information from previous evaluated solutions. Experimental results show that the proposed algorithm outperforms traditional communication-aware task scheduling and task scheduling using genetic algorithms in terms of total energy consumption.
Year
DOI
Venue
2011
10.1016/j.ins.2011.04.037
Information Sciences
Keywords
Field
DocType
Task scheduling,Voltage selection,Ant Colony Optimization,Multiprocessor system,Low power
Ant colony optimization algorithms,Mathematical optimization,Heuristic,Multiprocessor scheduling,Scheduling (computing),Computer science,Multiprocessing,Energy consumption,Genetic algorithm,Energy minimization
Journal
Volume
Issue
ISSN
181
18
0020-0255
Citations 
PageRank 
References 
12
0.57
25
Authors
2
Name
Order
Citations
PageRank
Hyunjin Kim1424.84
Sungho Kang243678.44