36,670 research outputs found

    A view at desktop clouds

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    Cloud has emerged as a new computing paradigm that promises to move into computing-as-utility era. Desktop Cloud is a new type of Cloud computing. It merges two computing models: Cloud computing and volunteer computing. The aim of Desktop Cloud is to provide Cloud services out of infrastructure that is not made for this purpose in order to reduce running and maintenance costs. This paper discusses this new type of Cloud by comparing it with current Cloud and Desktop Grid models. It, also, presents several research challenges in Desktop Cloud that require further attention

    A collaborative citizen science platform for real-time volunteer computing and games

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    Volunteer computing (VC) or distributed computing projects are common in the citizen cyberscience (CCS) community and present extensive opportunities for scientists to make use of computing power donated by volunteers to undertake large-scale scientific computing tasks. Volunteer computing is generally a non-interactive process for those contributing computing resources to a project whereas volunteer thinking (VT) or distributed thinking, which allows volunteers to participate interactively in citizen cyberscience projects to solve human computation tasks. In this paper we describe the integration of three tools, the Virtual Atom Smasher (VAS) game developed by CERN, LiveQ, a job distribution middleware, and CitizenGrid, an online platform for hosting and providing computation to CCS projects. This integration demonstrates the combining of volunteer computing and volunteer thinking to help address the scientific and educational goals of games like VAS. The paper introduces the three tools and provides details of the integration process along with further potential usage scenarios for the resulting platform.Comment: 12 pages, 13 figure

    An Approach to Ad hoc Cloud Computing

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    We consider how underused computing resources within an enterprise may be harnessed to improve utilization and create an elastic computing infrastructure. Most current cloud provision involves a data center model, in which clusters of machines are dedicated to running cloud infrastructure software. We propose an additional model, the ad hoc cloud, in which infrastructure software is distributed over resources harvested from machines already in existence within an enterprise. In contrast to the data center cloud model, resource levels are not established a priori, nor are resources dedicated exclusively to the cloud while in use. A participating machine is not dedicated to the cloud, but has some other primary purpose such as running interactive processes for a particular user. We outline the major implementation challenges and one approach to tackling them

    Next Generation Cloud Computing: New Trends and Research Directions

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    The landscape of cloud computing has significantly changed over the last decade. Not only have more providers and service offerings crowded the space, but also cloud infrastructure that was traditionally limited to single provider data centers is now evolving. In this paper, we firstly discuss the changing cloud infrastructure and consider the use of infrastructure from multiple providers and the benefit of decentralising computing away from data centers. These trends have resulted in the need for a variety of new computing architectures that will be offered by future cloud infrastructure. These architectures are anticipated to impact areas, such as connecting people and devices, data-intensive computing, the service space and self-learning systems. Finally, we lay out a roadmap of challenges that will need to be addressed for realising the potential of next generation cloud systems.Comment: Accepted to Future Generation Computer Systems, 07 September 201

    Towards distributed architecture for collaborative cloud services in community networks

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    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

    Support Service for Reciprocal Computational Resource Sharing in Wireless Community Networks

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    In community networks, individuals and local organizations 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. Most current community networks use wireless links for the node interconnection, applying off-the-shelf wireless equipment. While IP connectivity over the shared network infrastructure is successfully achieved, the deployment of applications in community networks is surprisingly low. To address the solution of this problem, we propose in this paper a service to incentivize the contribution of computing and storage as cloud resources to community networks, in order to stimulate the deployment of services and applications. Our final goal is the vision that in the long term, the users of community networks will not need to consume applications from the Internet, but find them within the wireless community network

    The Landscape of Salesforce for Nonprofits: A Report on the Current Marketplace for Apps

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    Do you use Salesforce as a Constituent Relationship Management database at your organization, or are you considering it? Since it launched in 1999, more than 20,000 nonprofits have employed the cloud-based system, which is made available to them for free through the philanthropic Salesforce Foundation. What's the catch? Making such a powerful system work for the particular needs of a nonprofit isn't always straightforward. This report can tell you everything you need to know.What's in it? To learn more about the benefits and drawbacks of Salesforce, we interviewed nine prominent consultants specializing in implementing Salesforce for nonprofits along with several members of the Salesforce.com Foundation about what the platform does well, and what you'll want to add to it to suit your needs. We evaluated some of the constituent management packages built on top of Salesforce, including the Salesforce Foundation's Nonprofit Starter Pack, which is aimed at turning the sales automation platform into a tool for nonprofits. We also took a look at the universe of add-ons to the base Salesforce platform -- called "apps" because of Salesforce's online marketplace, the App Exchange -- to find out which might be useful to support a nonprofit's processes.The goal for this report was to break down misconceptions about the tool and to collect disparate information in one place to help you make informed decisions. Whether you're already using Salesforce, are thinking about adopting it, or have yet to even consider it, there's information here for you.What's more, we've included a directory of consultants or firms with experience working with nonprofits to implement Salesforce and the additional App Exchange modules that we cover in this report to make it easier for you to find the help you'll need

    A cooperative approach for distributed task execution in autonomic clouds

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    Virtualization and distributed computing are two key pillars that guarantee scalability of applications deployed in the Cloud. In Autonomous Cooperative Cloud-based Platforms, autonomous computing nodes cooperate to offer a PaaS Cloud for the deployment of user applications. Each node must allocate the necessary resources for customer applications to be executed with certain QoS guarantees. If the QoS of an application cannot be guaranteed a node has mainly two options: to allocate more resources (if it is possible) or to rely on the collaboration of other nodes. Making a decision is not trivial since it involves many factors (e.g. the cost of setting up virtual machines, migrating applications, discovering collaborators). In this paper we present a model of such scenarios and experimental results validating the convenience of cooperative strategies over selfish ones, where nodes do not help each other. We describe the architecture of the platform of autonomous clouds and the main features of the model, which has been implemented and evaluated in the DEUS discrete-event simulator. From the experimental evaluation, based on workload data from the Google Cloud Backend, we can conclude that (modulo our assumptions and simplifications) the performance of a volunteer cloud can be compared to that of a Google Cluster

    Personal Volunteer Computing

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    We propose personal volunteer computing, a novel paradigm to encourage technical solutions that leverage personal devices, such as smartphones and laptops, for personal applications that require significant computations, such as animation rendering and image processing. The paradigm requires no investment in additional hardware, relying instead on devices that are already owned by users and their community, and favours simple tools that can be implemented part-time by a single developer. We show that samples of personal devices of today are competitive with a top-of-the-line laptop from two years ago. We also propose new directions to extend the paradigm
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