A Swarm-inspired Technique for Self-Organizing and Consolidating Data Centre Servers

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Ionut Anghel
Cristina Bianca Pop
Tudor Cioara
Ioan Salomie
Iulia Vartic


This paper proposes a swarm-inspired data centre self-organizing and consolidation technique which aims at reducing the power demand in data centres while ensuring the workload execution within the established performance parameters. Each data centre server is managed by an intelligent agent that implements a bird's migration-inspired behaviour to decide on the appropriate server consolidation actions. The selected actions are executed to achieve an optimal utilization of server computing resources thus lowering power demand. The data centre servers self-organize in logical clusters according to the birds V-formation self-organizing migration model. The results are promising showing that by using the proposed swarm-inspired solution, the data centre Deployed Hardware Utilization Ratio Green Indicator increases compared to the widely used Fit First consolidation algorithm. The average power saving of the proposed technique is around 40% of the power demanded by the data centre computing resources and about 16% of its total power demand including the IT facility, when comparing to OpenNebula Fit First consolidation technique. This paper is an extended version of the one published in WIMS'12 proceedings showing more details about the swarm-inspired consolidation technique and the defined algorithms.

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