Virtual Machine Planning for Cloud Brokering Considering Geolocation and Data Transfer
Javier Alsina, Santiago Iturriaga, Sergio Nesmachnow, Andrei Nikolaevitch Tchernykh, Bernabè Dorronsoro · 2016
This article addresses a virtual machine (VM) allocation problem that appears in a novel business model for cloud computing. In this model, a cloud service broker owns a number of cloud reserved instances that outsources to its customers as cheap as on-demand VMs. The objective of the broker is to efficiently manage its reserved resources to maximize its revenue. We enhance the previous definition of the problem by considering more realistic parameters: geographical localization of resources and users, different types of applications, and data transfer costs. We propose a set of heuristics to solve the optimization problem of maximizing the cloud provider profit while offering appropriate Quality-of-Service to the users. The experimental analysis is performed over different scenarios using real data from cloud providers.