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Flexible self-adjustment of task deployment in dynamic environments

Flexible self-adjustment of task deployment in dynamic environments

Anthony, Richard (2006) Flexible self-adjustment of task deployment in dynamic environments. Multiagent and Grid Systems, 2 (1). pp. 61-87. ISSN 1574-1702

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Abstract

This paper presents an investigation into dynamic self-adjustment of task deployment and other aspects of self-management, through the embedding of multiple policies.
Non-dedicated loosely-coupled computing environments, such as clusters and grids are increasingly popular platforms for parallel processing. These abundant systems are highly dynamic environments in which many sources of variability affect the run-time efficiency of tasks. The dynamism is exacerbated by the incorporation of mobile devices and wireless communication.
This paper proposes an adaptive strategy for the flexible run-time deployment of tasks; to continuously maintain efficiency despite the environmental variability. The strategy centres on policy-based scheduling which is informed by contextual and environmental inputs such as variance in the round-trip communication time between a client and its workers and the effective processing performance of each worker.
A self-management framework has been implemented for evaluation purposes. The framework integrates several policy-controlled, adaptive services with the application code, enabling the run-time behaviour to be adapted to contextual and environmental conditions. Using this framework, an exemplar self-managing parallel application is implemented and used to investigate the extent of the benefits of the strategy

Item Type: Article
Uncontrolled Keywords: policy-based, self-management, parallel processing,
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
H Social Sciences > HD Industries. Land use. Labor
B Philosophy. Psychology. Religion > BF Psychology
Pre-2014 Departments: School of Computing & Mathematical Sciences
School of Computing & Mathematical Sciences > Computer & Computational Science Research Group
School of Computing & Mathematical Sciences > Department of Computer Systems Technology
Related URLs:
Last Modified: 14 Oct 2016 09:02
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/958

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