Research Area:  Cloud Computing
This paper proposes a Cloud Infrastructure-as-a-Service (IaaS) framework that allows customers to have their high performance computing applications hosted efficiently and Cloud Service Providers (CSPs) to use their resources profitably. The solution introduces a distributed architecture that manages geographically distributed Data Centers (Geo-Data Centers) logically grouped in regions. This framework overcomes the challenges of traditional centralized provisioning approaches: (a) efficient provisioning of IaaS demand, (b) scale with respect to the growing number of IaaS requests, (c) guarantee of the stringent Quality of Service requirements of IaaS requests, and (d) efficient use of Cloud Geo-Data Center computing resources. Our architecture incorporates two decentralized approaches, hierarchical and distributed, that use auctions instead of a pay-as-you-go pricing scheme. The two approaches use a large-scale optimization technique for the allocation of Geo-Data Centers computing resources. The results of a simulation demonstrate an efficient use of computing resources and a significant reduction in computation time. This ensures adequate scalability to meet an exponential growth of IaaS demand. The auction-based approaches are also shown to provide monetary benefits to the participants.
Author(s) Name:  Khaled Metwally; Abdallah Jarray and Ahmed Karmouch
Journal name:   IEEE Transactions on Cloud Computing
Publisher name:  IEEE
Volume Information:  Volume: 8, Issue: 3, July-Sept. 1 2020,Page(s): 647 - 659
Paper Link:   https://ieeexplore.ieee.org/document/8300643