InterCloud: Utility-Oriented Federation of Cloud Computing Environments for Scaling of Application Services

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.Comment: 20 pages, 4 figures, 3 tables, conference pape

Cloud computing resource scheduling and a survey of its evolutionary approaches

A disruptive technology fundamentally transforming the way that computing services are delivered, cloud computing offers information and communication technology users a new dimension of convenience of resources, as services via the Internet. Because cloud provides a finite pool of virtualized on-demand resources, optimally scheduling them has become an essential and rewarding topic, where a trend of using Evolutionary Computation (EC) algorithms is emerging rapidly. Through analyzing the cloud computing architecture, this survey first presents taxonomy at two levels of scheduling cloud resources. It then paints a landscape of the scheduling problem and solutions. According to the taxonomy, a comprehensive survey of state-of-the-art approaches is presented systematically. Looking forward, challenges and potential future research directions are investigated and invited, including real-time scheduling, adaptive dynamic scheduling, large-scale scheduling, multiobjective scheduling, and distributed and parallel scheduling. At the dawn of Industry 4.0, cloud computing scheduling for cyber-physical integration with the presence of big data is also discussed. Research in this area is only in its infancy, but with the rapid fusion of information and data technology, more exciting and agenda-setting topics are likely to emerge on the horizon

DEPAS: A Decentralized Probabilistic Algorithm for Auto-Scaling

The dynamic provisioning of virtualized resources offered by cloud computing infrastructures allows applications deployed in a cloud environment to automatically increase and decrease the amount of used resources. This capability is called auto-scaling and its main purpose is to automatically adjust the scale of the system that is running the application to satisfy the varying workload with minimum resource utilization. The need for auto-scaling is particularly important during workload peaks, in which applications may need to scale up to extremely large-scale systems. Both the research community and the main cloud providers have already developed auto-scaling solutions. However, most research solutions are centralized and not suitable for managing large-scale systems, moreover cloud providers' solutions are bound to the limitations of a specific provider in terms of resource prices, availability, reliability, and connectivity. In this paper we propose DEPAS, a decentralized probabilistic auto-scaling algorithm integrated into a P2P architecture that is cloud provider independent, thus allowing the auto-scaling of services over multiple cloud infrastructures at the same time. Our simulations, which are based on real service traces, show that our approach is capable of: (i) keeping the overall utilization of all the instantiated cloud resources in a target range, (ii) maintaining service response times close to the ones obtained using optimal centralized auto-scaling approaches.Comment: Submitted to Springer Computin

Identity in research infrastructure and scientific communication: Report from the 1st IRISC workshop, Helsinki Sep 12-13, 2011

Motivation for the IRISC workshop came from the observation that identity and digital identification are increasingly important factors in modern scientific research, especially with the now near-ubiquitous use of the Internet as a global medium for dissemination and debate of scientific knowledge and data, and as a platform for scientific collaborations and large-scale e-science activities.

The 1 1/2 day IRISC2011 workshop sought to explore a series of interrelated topics under two main themes: i) unambiguously identifying authors/creators & attributing their scholarly works, and ii) individual identification and access management in the context of identity federations. Specific aims of the workshop included:

• Raising overall awareness of key technical and non-technical challenges, opportunities and developments.
• Facilitating a dialogue, cross-pollination of ideas, collaboration and coordination between diverse – and largely unconnected – communities.
• Identifying & discussing existing/emerging technologies, best practices and requirements for researcher identification.

This report provides background information on key identification-related concepts & projects, describes workshop proceedings and summarizes key workshop findings

Towards distributed architecture for collaborative cloud services in community networks

Internet and communication technologies have lowered the costs for communities to collaborate, leading to new services like user-generated content and social computing, and through collaboration, collectively built infrastructures like community networks have also emerged. Community networks get formed when individuals and local organisations from a geographic area team up to create and run a community-owned IP network to satisfy the community’s demand for ICT, such as facilitating Internet access and providing services of local interest. The consolidation of today’s cloud technologies offers now the possibility of collectively built community clouds, building upon user-generated content and user-provided networks towards an ecosystem of cloud services. To address the limitation and enhance utility of community networks, we propose a collaborative distributed architecture for building a community cloud system that employs resources contributed by the members of the community network for provisioning infrastructure and software services. Such architecture needs to be tailored to the specific social, economic and technical characteristics of the community networks for community clouds to be successful and sustainable. By real deployments of clouds in community networks and evaluation of application performance, we show that community clouds are feasible. Our result may encourage collaborative innovative cloud-based services made possible with the resources of a community.Peer ReviewedPostprint (author’s final draft

Enhancing Federated Cloud Management with an Integrated Service Monitoring Approach

Cloud Computing enables the construction and the provisioning of virtualized service-based applications in a simple and cost effective outsourcing to dynamic service environments. Cloud Federations envisage a distributed, heterogeneous environment consisting of various cloud infrastructures by aggregating different IaaS provider capabilities coming from both the commercial and the academic area. In this paper, we introduce a federated cloud management solution that operates the federation through utilizing cloud-brokers for various IaaS providers. In order to enable an enhanced provider selection and inter-cloud service executions, an integrated monitoring approach is proposed which is capable of measuring the availability and reliability of the provisioned services in different providers. To this end, a minimal metric monitoring service has been designed and used together with a service monitoring solution to measure cloud performance. The transparent and cost effective operation on commercial clouds and the capability to simultaneously monitor both private and public clouds were the major design goals of this integrated cloud monitoring approach. Finally, the evaluation of our proposed solution is presented on different private IaaS systems participating in federations. © 2013 Springer Science+Business Media Dordrecht