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Dynamic virtual machine consolidation using a multi-agent system to optimise energy efficiency in cloud computing

delete2020-07-01
delete22
PRE
AI
N
Nicola Mc Donnell *
E
Enda Howley
J
Jim Duggan
DOI:10.1016/j.future.2020.02.036delete
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摘要

摘要

En 中文
Cloud computing has seen rapid growth in the last decade, as a result of this there is an increasing concern about the energy requirement of cloud data centres. One approach to tackle this issue is dynamic virtual machine consolidation (DVMC) where virtual machines (VMs) are packed into fewer hosts, while hosts which have no VMs are placed into a hibernate mode. DVMC is traditionally solved with strategies that build on centralised topologies. One disadvantage of these solutions is that they don' t scale well in very large data centres as the manager node becomes a bottleneck and a single point of failure. The nature of the problem lends itself to a decentralised solution which is preferred over a centralised one when a problem is: inherently modular, large in scale, in a very dynamic environment, and when communication channels can experience message delays and loss. We propose Gossip Contracts (GC), a new multi-agent framework for crafting decentralised co-operation strategies. GC is inspired by the Gossip and Contract Net protocols. Using GC we developed a GC-based DVMC strategy and compared it to two popular strategies: Sercon, a centralised strategy, and ecoCloud, a distributed strategy. One of the comparison experiments uses Google cluster-usage traces; a dataset of real usage data from a Google data centre. The GC-based strategy performs best with respect to SLA Violations, and is similar to or outperforms other strategies with respect to power consumption. By its decentralised nature, GC does not have a single point of failure. (C) 2020 Published by Elsevier B.V.
Keyword:
Cloud computing
Energy efficiency
Dynamic Virtual Machine Consolidation
Decentralised Algorithm
Contract Net
Gossip
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期刊

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Future Generation Computer Systems-The International Journal of eScience
IF:
6.1
论文数:
6.9K
被引数:
2.3W

机构

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ollscoil na gaillimhe-university of galway
学者数:
1.1W
论文数: 8.7K
被引数: 5
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