The Researchers at Boston University are exploring the merits of "Colocation Games" (CGs) as a novel, economically-sound framework upon which emerging cloud architectures could be implemented. This work is funded by a National Science Foundation (NSF) grant. It introduces Colocation Games as the basis of a general framework for modeling, analyzing, and facilitating the interactions between the various stakeholders in distributed/cloud computing environments, where resources are offered in an open marketplace to independent, rational parties interested in setting up their own applications.
Carnegie Mellon University is actively involved in several cloud computing research programs and is one of the test sites for the Open Cirrus program. Their research includes studies on Multi-Tier Indexing for Web Search Engines, Integrated Cluster Computing Architecture, and others.
The researchers at Duke University are conducting research funded by the National Science Foundation (NSF) in collaboration with NCSU, UNC Chapel Hill, and NCAT State University to explore and test Trustworthy Virtual Cloud Computing.
Enabling Grids for E-sciencE (EGEE) is Europe's leading grid computing project, providing a computing support infrastructure for over 10,000 researchers world-wide, from fields as diverse as high energy physics, earth and life sciences. The EGEE project brings together experts from more than 50 countries with the common aim of building on recent advances in Grid technology and developing a service Grid infrastructure which is available to scientists. The project provides researchers in academia and business with access to a production level Grid infrastructure, independent of their geographic location.
Florida International University (FIU) researchers are leveraging cloud computing, using a National Science Foundation (NSF) grant on the Google/IBM Cloud, to analyze aerial images and objects to help support disaster mitigation and environmental protection.
The IBM/Google Academic Cloud Computing Initiative (ACCI) is a joint university initiative to help computer science students gain the skills they need to build cloud infrastructures and applications. The IBM/Google initiative aims to provide computer science students with a complete suite of open source based development tools so they can gain the advanced programming skills necessary to innovate and address the challenges of the Cloud Computing model - which uses many computers networked together through open standards - and thereby drive the Internet's next phase of growth.
The researchers at Indiana University are working on several cloud computing projects with grants from the National Science Foundation (NSF) and the National Institute of Health (NIH). Their research includes: Large-Scale Distributed Scientific Experiments on Shared Substrate; Exploring the use of cloud techniques to overcome current medical computing obstacles such as long computation time and large memory requirements; and The FutureGrid project that will provide an experimental platform that accommodates batch, grid and cloud computing.
The team at MIT is working in collaboration with Yale University and the University of Wisconsin at Madison on a comparative study, funded by a National Science Foundation (NSF) CLuE grant, of approaches to cluster-based, large-scale data analysis. In addition they are also independently studying Cloud Computing Infrastructure and Technology for Education.
The Networked European Software and Services Initiative (NESSI) is the European Technology Platform dedicated to Software and Services. The overall ambition of NESSI is to deliver NEXOF, a coherent and consistent open service framework leveraging research in the area of service-based systems to consolidate and trigger innovation in service-oriented economies.
The team at the North Carolina Agricultural & Technical State University is conducting research, funded by a National Science Foundation (NSF), in collaboration with NCSU, Duke University, and the University of NC at Chapel Hill to explore and test Trustworthy Virtual Cloud Computing.
The researchers at North Carolina State University are working on several cloud computing projects funded by the National Science Foundation (NSF). They include two collaborative studies on Trustworthy Virtual Cloud Computing and Hybrid Opportunistic Computing for Green Clouds. In addition, NetApp has contributed hardware, software and services to NCSU to expand their Virtual Computing Lab (VCL) and build the next generation of cloud computing environments.
Open Cirrus is an open cloud-computing research testbed designed to support research into design, provisioning, and management of services at a global, multi-datacenter scale. The open nature of the testbed is designed to encourage research into all aspects of service and datacenter management. In addition, they hope to foster a collaborative community around the testbed, providing ways to share tools, lessons and best practices, and ways to benchmark and compare alternative approaches to service management at datacenter scale.
The Purdue University team is investigating linguistic extensions to MapReduce abstractions for programming modern, large-scale systems, with special focus on applications that manipulate large, unstructured graphs. They also provide a cloud computing testbed called Wispy to TeraGrid users.
The RESERVOIR project is intended to increase the competitiveness of the EU economy by introducing a powerful ICT infrastructure for the reliable and effective delivery of services as utilities. This infrastructure will support the set-up and deployment of services on demand, and competitive costs, across disparate administrative domains, while assuring quality of service.
The research project SLA@SOI will provide a major milestone for the further evolution towards a service-oriented economy, where IT-based services can be flexibly traded as economic goods, i.e. under well defined and dependable conditions and with clearly associated costs. Eventually, this will allow for dynamic value networks that can be flexibly instantiated, thus driving innovation and competitiveness.
Tsinghua Cloud is an all-in-one Cloud Computing solution developed at the Grid Computing Division of Tsinghua University in China. The Cloud is composed of three components: Nova (virtual computation system: computing cloud), Carrier (distributed file system) and Corsair (distributed file manager based on Carrier: storage cloud), which can be utilized independently or in combination.
The Umeå University research on flexible and scalable IT infrastructures covers a range of topics central to cloud computing. Research drivers are compute and data intensive applications requiring, e.g., elastic locality-aware infrastructures to meet the rapid capacity and locality variations of industrial services and large-scale distributed environments that enable coordinated use of federated resources for eScience. Research outcomes include autonomic infrastructure management systems and sophisticated tools for creating cloud-enabled applications.
The National Science Foundation has awarded a grant to researchers at SDSC to explore new ways to manage extremely large data sets hosted on massive clusters, which have become known as computing “clouds”. This research will use the LiDAR topography data hosted by OpenTopography as a test case and will focus on how cloud computing can aid the management and processing of massive spatial data sets.
The University of Santa Barbara is actively pursuing several advancements in cloud computing. Their Massive Graphs in Clusters (MAGIC) project is focused on developing software infrastructure that can efficiently answer queries on extremely large graph datasets. They have also designed an open-source implementation of the Google AppEngine interface.
The Institute for Genome Sciences at the University of Maryland's School of Medicine has developed a virtual appliance that integrates state-of-the-art genomic tools on Cloud Computing platforms in a robust, user friendly, and automated package called CloVR. By providing a set of push-button pipelines for applications in viral, prokaryotic, metagenomic and eukaryotic sequencing projects, CloVR will facilitate the further integration of genomics into environmental and biomedical research.
The research team at the University of Maryland's Cloud Computing Center at College Park is working on a range of projects funded by the National Science Foundation (NSF). They include: A Hadoop Toolkit for Distributed Text Retrieval; Data-Intensive Text Processing; Commodity Computing in Genomic Research; and a series of other independent studies.
The team at the University of Massachusets Amherst Center for Intelligent Information Retrieval (CIIR) are using a National Science Foundation (NSF) grant and the Google/IBM cloud to learn more about world relationships.
The Cloud Computing and Distributed Systems (CLOUDS) Laboratory, formerly GRIDS Lab, is a software research and development group within the Department of Computer Science and Software Engineering at the University of Melbourne, Australia. The CLOUDS Lab is actively engaged in the design and development of next-generation computing systems and applications that aggregate or lease services of distributed resources depending on their availability, capability, performance, cost, and users' quality-of-science requirements. The lab is working towards realizing this vision through its two flagship projects: Gridbus and Cloudbus.
The team at the University of Minnesota is working on a project, funded by the National Science Foundation (NSF), that proposes a cloud proxy network that allows optimized and reliable data-centric operations to be performed at strategic network locations.
The researchers at the University of North Carolina at Chapel Hill are conducting research, funded by a National Science Foundation (NSF), in collaboration with NCSU, Duke University, and NCAT State University to explore and test Trustworthy Virtual Cloud Computing.
The team at the University of Utah is working with the University of Washington on building a new infrastructure for computational oceanography that uses the Google/IBM cloud to allow ad hoc, longitudinal query and visualization of massive ocean simulation results at interactive speeds.
The team at the University of Virginia is working on several cloud computing projects funded by the National Science Foundation (NSF). They include, Feedback-Controlled Management of Virtualized Resources for Predictable eScience and Image Super-Resolution Using Trillions of Examples.
The team at the University of Washington is working with the University of Utah on building a new infrastructure for computational oceanography that uses the Google/IBM cloud to allow ad hoc, longitudinal query and visualization of massive ocean simulation results at interactive speeds. In addition their Astronomy Survey Group is conducting research to Scale the Sky with MapReduce/Hadoop.
The team at the University of Wisconsin Madison have designed the Hierarchically-Redundant, Decoupled storage project (HaRD) to investigate the next generation of storage software for hybrid Flash/disk storage clusters. They are also working with MIT and Yale University on a comparative study, funded by a National Science Foundation (NSF) CLuE grant, of approaches to cluster-based, large-scale data analysis.
The team at Virginia Tech is collaborating with NC State University on studying Hybrid Opportunistic Computing for Green Clouds. This project, funded by the National Science Foundation (NSF), explores a new computing model of offering cloud services on active nodes that are serving on-demand utility computing users.
At Wayne State University they are working on developing a unified learning approach, namely URL, to automate the configuration processes of virtualized machines and applications running on the virtual machines and adapt the systems configuration to the dynamics of cloud. This research is funded by a National Science Foundation (NSF) grant.
The team at Yale University is working in collaboration with MIT and the University of Wisconsin at Madison on a comparative study, funded by a National Science Foundation (NSF) CLuE grant, of approaches to cluster-based, large-scale data analysis.