QoS-based Cloud Resources Partitioning Aware Networked Edge Datacenters
Résumé
This paper focuses on the resource allocation problem in the context of Cloud Computing. More specifically, this work considers the problem of optimizing the mapping cost of Infrastructure as Cloud Service (IaaS) onto a Networked Edge Data-Centers (DCs) with respect to Quality of Service (QoS) requirements. This work proposes to dynamically partition the networked DCs resources over IaaS requests belonging to different QoS classes. In literature, a number of works have proposed IaaS mapping approaches; however their focus was mainly on the cloud hosting requirements and do not take into account the dynamics of IaaS QoS requirements. Consequently, they may not offer QoS guarantees for accepted IaaS requests which may result in a higher customer dissatisfaction ratio. The originality of our work is in the forethought and the investigation of these issues. To do so, a column generation based-formulation is proposed coupled with the Branch and Bound technique in order to solve it efficiently. Doing so, this allows the Cloud Provider to: (i) minimize IaaS mapping cost, and (ii) calculate the optimal and dynamic partitioning of DCs resources to uphold QoS guarantees for IaaS requests.