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Authors
Advisor(s)
Abstract(s)
Empowered by virtualisation technology, cloud infrastructures enable the construction of flexi-
ble and elastic computing environments, providing an opportunity for energy and resource cost
optimisation while enhancing system availability and achieving high performance. A crucial re-
quirement for effective consolidation is the ability to efficiently utilise system resources for high-
availability computing and energy-efficiency optimisation to reduce operational costs and carbon
footprints in the environment. Additionally, failures in highly networked computing systems can
negatively impact system performance substantially, prohibiting the system from achieving its
initial objectives. In this paper, we propose algorithms to dynamically construct and readjust vir-
tual clusters to enable the execution of users’ jobs. Allied with an energy optimising mechanism
to detect and mitigate energy inefficiencies, our decision-making algorithms leverage virtuali-
sation tools to provide proactive fault-tolerance and energy-efficiency to virtual clusters. We
conducted simulations by injecting random synthetic jobs and jobs using the latest version of
the Google cloud tracelogs. The results indicate that our strategy improves the work per Joule
ratio by approximately 12.9% and the working efficiency by almost 15.9% compared with other
state-of-the-art algorithms.
Description
Keywords
scheduling energy-efficiency consolidation proactive fault-tolerance platform elasticity
Citation
Publisher
Future Generation Computer Systems - Elsevier