Assigning real-time tasks to heterogeneous processors by applying ant colony optimization

The problem of determining whether a set of periodic tasks can be assigned to a set of heterogeneous processors without deadline violations has been shown, in general, to be NP-hard. This paper presents a new algorithm based on ant colony optimization (ACO) metaheuristic for solving this problem. A...

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Bibliographic Details
Published in:	Journal of parallel and distributed computing Vol. 71; no. 1; pp. 132 - 142
Main Authors:	Chen, Hua, Cheng, Albert Mo Kim, Kuo, Ying-Wei
Format:	Journal Article
Language:	English
Published:	Amsterdam Elsevier Inc 2011 Elsevier
Subjects:	Algorithmics. Computability. Computer arithmetics Algorithms Ant colony optimization Applied sciences Colonies Computer science; control theory; systems Computer systems and distributed systems. User interface Energy of solution Energy use Exact sciences and technology Heterogeneous processors Language processing and microprogramming Mathematical models Multiprocessors Optimization Periodic tasks Power-aware computing Processors Prototypes Real-time systems Scheduling Searching Software Theoretical computing Heterogeneous processors Ant colony optimization Multiprocessors Power-aware computing Periodic tasks Scheduling Real-time systems Energy consumption Insecta Formicoidea Multiprocessor Space complexity Swarm intelligence Metamodel Aculeata Local search Deadline Periodicity Social insect Real time Computational complexity Processor scheduling Arthropoda Heuristic method NP hard problem Problem solving Hymenoptera Invertebrata Time complexity
ISSN:	0743-7315, 1096-0848
Online Access:	Get full text
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