Peer-to-peer grid computing with the OurGrid Community

Grid computing is a distributed computing paradigm which aims to aggregate several heterogeneous and distributed resources, belonging to different and independent organizations, in a dynamic, transparent and coordinated way. Since its introduction, Grid computing has been successfully applied to solve several scientific challenging applications. Despite of the consolidation of many of its aspects, there are some issues that are still open. One of them is the transparency: in many real Grid systems, users still need to be aware of Grid computing, either for adapting their applications to this paradigm or for wrapping them in a suitable software framework. In this paper we present the ShareGrid Portal, a Web portal and a portal framework, built on top of the ShareGrid project infrastructure. Its intent is both to ease the execution of user applications in a Grid system and to allow developers to flexibly add new portal functionalities. In this work, we compare it with other well-known Grid portals and we show its user interface and its architecture. Finally we discuss user experiences and future extensions.

Grid and Cooperative Computing, 2003

The common goals of the Grid and peer-to-peer communi- ties have brought them in close proximity. Both the technologies overlay a collaborative resource-sharing infrastructure on existing (public) net- works. In realizing this shared goal, however, they concentrate on signif- icantly contrasting issues. The Grid paradigm focuses on performance, control, security, specialization, and standardization. On the other hand, the peer-to-peer paradigm

Peer-to-Peer (P2P) Desktop Grids are computing infrastructures that aggregate a set of desktop-class machines in which all the participating entities have the same roles, responsibilities, and rights. In this paper, we present ShareGrid, a P2P Desktop Grid infrastructure based on the OurGrid middleware, that federates the resources provided by a set of small research laboratories to easily share and use their computing resources. We discuss the techniques and tools we employed to ensure scalability, efficiency, and usability, and describe the various applications used on it. We also demonstrate the ability of ShareGrid of providing good performance and scalability by reporting the results of experimental evaluations carried out by running various applications with different resource requirements. Our experience with ShareGrid indicates that P2P Desktop Grids can represent an effective answer to the computing needs of small research laboratories, as long as they provide both ease of management and use, and good scalability and performance.

Cluster Computing, 2002

Computational Grids [17, 25] have become an important asset in large-scale scientific and engineering research. By providing a set of services that allow a widely distributed collection of resources to be tied together into a relatively seamless computing framework, teams of researchers can collaborate to solve problems that they could not have attempted before. Unfortunately the task of building Grid applications remains extremely difficult because there are few tools available to support developers. To build reliable and re-usable Grid ...

The evolution of the global scientific cyberinfrastructure (CI) has, over the last 10+ years, led to a large diversity of CI instances. While specialized, competing and alternative CI building blocks are inherent to a healthy ecosystem, it also becomes apparent that the increasing degree of fragmentation is hindering interoperation, and thus limiting collaboration, which is essential for modern science communities often spanning international groups and multiple disciplines (but even 'small sciences', with smaller and localized communities, are often embedded into the larger scientific ecosystem, and are increasingly dependent on the availability of CI.) This open document represents the results of that workshop -including a draft of a mission statement and a proposal for a blueprint process -to inform the wider community as well as to encourage external experts to provide their feedback and comments. Grid computing has been promoted for more than 10 years as the Advanced Computational Infrastructure of the future, see Figure . Many scientists and others have considered grid computing as one of main sources of the impact that scientific and technological changes have made on the economy and society. This claim is based on the observation that the usage of large data volumes has become increasingly important to many disciplines, from natural sciences, engineering to the humanities and social sciences. However, despite significant investments in the grid concept, the number of users is not increasing. Instead, new concepts (or at least new terms) like cloud computing seem to be replacing the grid computing approach (or name). Many fields have depended on computational science simulations, and many now are beginning to depend on computationally intensive data analysis. Infrastructure providers seek to build computational systems that support these researchers. Developing the common vision that is needed to support these efforts is the eventual goal of the Zakopane workshop (Grid Computing: The Next Decade -), which brought together international leaders and early stage researchers in grid computing and e-Science from Europe, the USA, and Asia to discuss the needs and processes towards this goal.

Making Grids Work, 2008

In this paper, we discuss how Peer-to-Peer data distribution techniques can be adapted to Desktop Grid computing environments, particularly to the BOINC platform. To date, Desktop Grid systems have focused primarily on utilizing spare CPU cycles, yet have neglected to take advantage of client network capabilities. Leveraging client bandwidth will not only benefit current projects by lowering their overheads but will also facilitate Destkop Grid adoption by data-heavy applications. In this paper, weoutline two approaches to Peer-to-Peer data sharing that could be adapted for volunteer computing platforms: the highly successful BitTorrent protocol; and, a more complex, yet secure and customizable, hierarchal Peer-to-Peer data center approach.

Journal of Parallel and …, 2007

Currently, most computational grids (systems allowing transparent sharing of processing resources across organizational boundaries) are assembled using human negotiation. This procedure does not scale well, and is too inflexible to allow for large open grids. Peer-to-peer grids present an alternative way to build grid infrastructures with a large number of sites. However, to actually assemble a large grid, peers must have an incentive to collaborate by providing resources to the system. In this paper we propose an incentive mechanism called the Network of Favors, which is designed to make it in the best interest of each participating peer to make as much as possible of its spare processing resources available to the system. We show through analysis, simulations, and experiments with an implementation that the Network of Favors promotes collaboration in a simple and robust fashion. We also describe OurGrid, a peer-to-peer grid based on the Network of Favors that is in production since December 2004.

e-Science and Grid Computing, 2005

Clusters of workstations are one of the most suitable resources to assist e-scientists in the execution of large-scale experiments that demand processing power. The utilization rate of these machines is usually far from 100%, and hence this should motivate administrators to share their clusters to grid communities. However, exploiting these resources in computational grids is challenging and brings several problems. This paper presents a transparent resource allocation strategy to harness idle cluster resources aimed at executing grid applications. This novel approach does not make use of a formal allocation request to cluster resource managers. Moreover, it does not interfere with local cluster users, being non-intrusive, and hence motivating cluster administrators to publish their resources to grid communities. We present experimental results regarding the effects of the proposed strategy on the attendance time of both cluster and grid requests and we also analyze its effectiveness in clusters with different utilization rates

2009