Cloud elasticity also prevents you from having to pay for unused capacity or idle resources, meaning you won’t have to buy or maintain extra equipment. As an alternative to on-premises infrastructure, elastic computing offers greater efficiency. It is also typically automated and keeps services ru...
Elasticity depends on advanced tools that automatically adjust your resource levels, meaning your team needs the know-how to set up, monitor, and tweak these systems as needed. This requires a solid understanding of the technology and a readiness to dive into the nitty-gritty details of cloudres...
Therefore, in this paper, our aim is to guarantee the QoS by introducing the semantic meaning of the elasticity strategies in SLA. In this regard, we propose an ontology-based elasticity approach which allows getting an elastic cloud service by dynamically apply corrective actions. These corrective...
Cloud application elasticity is an active research domain, especially if we consider the need to handle the extended cloud computing, which includes fog and edge devices. Algorithms exploiting a range of techniques, from machine learning to control theory methods, have been developed, aiming to provi...
As regards elasticity control policies at the infrastructure level, it has been a hot research topic in cloud computing, as surveyed in [42,43]. Therefore, we review only some works that are most closely related to the RL-based approach we propose in Section 6. Threshold-based elasticity pol...