Image Transfer and Storage Cost Aware Brokering Strategies for Multiple Clouds

Abstract

Nowadays, Clouds are used to host a large range of services. But between different Cloud Service Providers, the pricing model and the price of individual resources can be very different. Furthermore hosting a service in one Cloud is the major cause of service outage. To increase resiliency and minimize the monetary cost of running a service, it becomes mandatory to span it between different Clouds. Moreover, due to dynamicity of both the service and Clouds, it could be required to migrate a service at run time. Accordingly, this ability must be integrated into the multi-Cloud resource manager, i.e. the Cloud broker. But, when migrating a VM to a new Cloud Service Provider, the VM disk image has to be migrated too. Accordingly, data storage and transfer must be taken into account when choosing if and where an application will be migrated. In this paper, we extend a cost-optimization algorithm to take into account storage costs to approximate the optimal placement of a service. The data storage management consists in taking two decisions: the location of the upload of an image, and keep it on-line during the experiment lifetime or delete it when unused. Based on our experimentations, we show that the storage cost of VM disk image must not be neglected as it was done in previous works. Moreover, we show that using the accurate combinations of storage policies can dramatically reduce the storage cost (from 90% to 14% of the total bill).