Multi-cloud computing is a promising paradigm to support very large scale world wide distributed applications. Multi-cloud computing is the usage of multiple, independent cloud environments, which assumed no priori agreement between cloud providers or third party. However, multi-cloud computing has to face several key challenges such as portability, provisioning, elasticity, and high availability. Developers will not only have to deploy applications to a specific cloud, but will also have to consider application portability from one cloud to another, and to deploy distributed applications spanning multiple clouds. This article presents soCloud a service-oriented component-based Platform as a Service for managing portability, elasticity, provisioning, and high availability across multiple clouds. soCloud is based on the OASIS Service Component Architecture standard in order to address portability. soCloud provides services for managing provisioning, elasticity, and high availability across multiple clouds. soCloud has been deployed and evaluated on top of ten existing cloud providers: Windows Azure, DELL KACE, Amazon EC2, CloudBees, OpenShift, dotCloud, Jelastic, Heroku, Appfog, and an Eucalyptus private cloud.
Cloud computing providers have setup several data centers at different geographical locations over the Internet in order to optimally serve needs of their customers around the world However, existing systems do not support mechanisms and policies for dynamically coordinating load distribution among different Cloud-based data centers in order to determine optimal location for hosting application services to achieve reasonable QoS levels Further, the Cloud computing providers are unable to predict geographic distribution of users consuming their services, hence the load coordination must happen automatically, and distribution of services must change in response to changes in the load To counter this problem, we advocate creation of federated Cloud computing environment (InterCloud) that facilitates just-in-time, opportunistic, and scalable provisioning of application services, consistently achieving QoS targets under variable workload, resource and network conditions The overall goal is to create a computing environment that supports dynamic expansion or contraction of capabilities (VMs, services, storage, and database) for handling sudden variations in service demands. This paper presents vision, challenges, and architectural elements of InterCloud for utility-oriented federation of Cloud computing environments The proposed InterCloud environment supports scaling of applications across multiple vendor clouds We have validated our approach by conducting a set of rigorous performance evaluation study using the CloudSim toolkit The results demonstrate that federated Cloud computing model has immense potential as it offers significant performance gains as regards to response time and cost saving under dynamic workload scenarios. Scalability is said to be one of the major advantages brought by the cloud paradigm and, more specifically, the one that makes it different to an "advanced outsourcing" solution. However, there are some important pending issues before making the dreamed automated scaling for applications come true. In this paper, the most notable initiatives towards whole application scalability in cloud environments are presented. We present relevant efforts at the edge of state of the art technology, providing an encompassing overview of the trends they each follow. We also highlight pending challenges that will likely be addressed in new research efforts and present an ideal scalable cloud system. Infrastructure-as-a-Service (IaaS) cloud computing offers new possibilities to scientific communities. One of the most significant is the ability to elastically provision and relinquish new resources in response to changes in demand. In our work, we develop a model of an “elastic site” that efficiently adapts services provided within a site, such as batch schedulers, storage archives, or Web services to take advantage of elastically provisioned resources. We describe the system architecture along with the issues involved with elastic provisioning, such as security, privacy, and various logistical considerations. To avoid over- or under-provisioning the resources we propose three different policies to efficiently schedule resource deployment based on demand. We have implemented a resource manager, built on the Nimbus toolkit to dynamically and securely extend existing physical clusters into the cloud. Our elastic site manager interfaces directly with local resource managers, such as Torque. We have developed and evaluated policies for resource provisioning on a Nimbus-based cloud at the University of Chicago, another at Indiana University, and Amazon EC2. We demonstrate a dynamic and responsive elastic cluster, capable of responding effectively to a variety of job submission patterns. We also demonstrate that we can process 10 times faster by expanding our cluster up to 150 EC2 nodes.