No abstract

No abstract

Abstract-One of the main obstacles hindering wider adoption of storage cloud services is vendor lock-in, a situation in which large amounts of data that are placed in one storage system can not be migrated to another vendor, e.g., due to time and cost considerations. To prevent this situation we present an advanced on-boarding federation mechanism, enabling a cloud to add a special federation layer to efficiently import data from other storage clouds. This is achieved without being dependent on any special function from the other clouds.We design a generic, modular on-boarding architecture and demonstrate its implementation as part of a VISION Cloud, which is a large scale storage cloud designed for content-centric data. Our system is capable of integrating storage data from various clouds, providing a common global view of storage data. The users can access the data through the new cloud provider immediately after the setup, maintaining the normal operation of applications, so that they do not need to wait for the completion of the data migration process. Finally, we analyze the payment models of existing storage clouds, showing that transferring the data via on-boarding federation with a direct link between clouds can lead to significant time and cost savings.

No abstract

While it is common to use storage in a cloud-based manner, the question of true interoperability is rarely fully addressed. This question becomes even more relevant since the steadily growing amount of data that needs to be stored will supersede the capacity of a single system in terms of resources, availability, and network throughput quite soon. The logical conclusion is that a network of systems needs to be created that is able to cope with the requirements of big data applications and data deluge scenarios. This chapter shows how federation and interoperability will fit into a cloud storage scenario. The authors take a look at the challenges that federation imposes on autonomous, heterogeneous, and distributed cloud systems, and present approaches that help deal with the special requirements introduced by the VISION Cloud use cases from healthcare, media, telecommunications, and enterprise domains. Finally, the authors give an overview on how VISION Cloud addresses these requirements in its research scenarios and architecture.