Abstract

Elasticity property allows cloud systems to adapt to their input workload by provisioning and deprovisioning resources as the demand grows and drops. However, due to the unpredictable nature of workload, providing accurate action plans to manage a cloud system's elasticity is a particularly challenging task. In this study, the authors propose a bigraphical reactive system-based approach to provide a formal modelling of cloud systems’ structure using bigraphs, and their elastic behaviours using bigraphical reaction rules. They introduce elasticity strategies to describe cloud systems’ auto-adaptation behaviours. One step further, they encode the bigraphical specifications into Maude language to enable an autonomic executability of the elastic behaviours and verify their correctness. Finally, they propose a queuing-based approach to discuss and analyse elasticity strategies in cloud systems through different simulated scenarios.

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