Facebook Meets the Virtualized Enterprise

Curry, Roger; Kiddle, Cameron; Markatchev, Nayden; Simmonds, Rob; Tan, Tingxi; Arlitt, Martin; Walker, Bruce J.

doi:10.1109/edoc.2008.19

Cited by 17 publications

(9 citation statements)

References 1 publication

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“…Cloud computing techniques have been applied to various eScience applications. We have surveyed a lot of eScience papers and summarized them in the following four categories based on their areas of expertise: Life sciences [51,56], Physical sciences [28,37], Climate and Earth sciences [32,43] as well as Social sciences and Humanities [23,49].…”

Section: Applicationmentioning

confidence: 99%

eScience and Big Data Workflows in Clouds

Zhou¹,

He²,

Ibrahim³

2016

Big Data

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Cloud computing has evolved as a popular computing infrastructure for many applications. With (big) data acquiring a crucial role in eScience, efforts have been made recently exploring how to efficiently develop and deploy scientific applications on the unprecedentedly scalable cloud infrastructures. We review recent efforts in developing and deploying scientific computing applications in the cloud. In particular, we introduce a taxonomy specifically designed for scientific computing in the cloud, and further review the taxonomy with four major kinds of science applications, including life sciences, physics sciences, social and humanities sciences, and climate and earth sciences. Due to the large data size in most scientific applications, the performance of I/O operations can greatly affect the overall performance of the applications. We notice that, the dynamic I/O performance of the cloud has made the resource provisioning an important and complex problem for scientific applications in the cloud. We present our efforts on improving the resource provisioning efficiency and effectiveness of scientific applications in the cloud. Finally, we present the open problems for developing the next-generation eScience applications and systems in the cloud and conclude this chapter.

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Section: Applicationmentioning

confidence: 99%

eScience and Big Data Workflows in Clouds

Zhou¹,

He²,

Ibrahim³

2016

Big Data

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“…For example, Automated Service Provisioning ENvironment (ASPEN) [6] exposes applications hosted by Cloud providers to user communities in Facebook. The focus of ASPEN is exposing applications and sharing data within an enterprise through an intuitive and integrated environment, however this could also be applied to a scientific domain.…”

Section: Related Workmentioning

confidence: 99%

Collaborative eResearch in a Social Cloud

Thaufeeg

Bubendorfer

Chard

2011

2011 IEEE Seventh International Conference on eScience

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Abstract-Social networks provide a useful basis for enabling collaboration among groups of individuals. This is applicable not only to social communities but also to the scientific community. Already scientists are leveraging social networking concepts in projects to form groups, share information and communicate with their peers. For scientific projects which require large computing resources, one useful aspect of collaboration is the sharing of computing resources among project members. A social network provides an ideal platform to share these resources. This paper introduces a framework for Social Cloud computing with a view towards collaboration and resource sharing within a scientific community. The architecture of a Social Cloud, where individuals or institutions contribute the capacity of their computing resources by means of Virtual Machines leased through the social network, is outlined. Members of the Social Cloud can contribute, request, and use Virtual Machines from other members, as well as form Virtual Organizations among groups of members.

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“…Recently, Curry et. al [14] presented work on how business enterprises can benefit from Web 2.0 technologies such as social networks and cloud computing by providing an intuitive environment for employees to access enterprise resources. Their implementation used Facebook to allow employees access to legacy applications running on a cloud-computing-based virtual appliances through a Facebook web-gateway.…”

Section: Related Workmentioning

confidence: 99%

On the Use of Social Networking Groups for Automatic Configuration of Virtual Grid Environments

Juste

Wolinsky

et al. 2008

2008 Grid Computing Environments Workshop

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Social networking sites have enhanced the Web by providing online "communities" where users can easily create identities, establish relationships between identities, and share resources with one another across the Web. The availability of social networking APIs, such as OpenSocial or the Facebook platform, make it possible for third-party developers to tap into these social relationships and design socially-aware applications. In this paper, we describe how social networking groups can be used to help create virtual private computing clusters that consist of nodes spanning different administrative domains and organizations. To demonstrate the feasibility and usage of our approach, we developed a fully functional prototype implementation and present the quantitative results of our virtual private network. Our design integrates virtual machines, peer-to-peer virtual private networks, and the Facebook Platform API, to enable a user community in which we can easily deploy ad-hoc Condor resource pools that are managed through the Web-based Facebook group interface.

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Facebook Meets the Virtualized Enterprise

Cited by 17 publications

References 1 publication

eScience and Big Data Workflows in Clouds

eScience and Big Data Workflows in Clouds

Collaborative eResearch in a Social Cloud

On the Use of Social Networking Groups for Automatic Configuration of Virtual Grid Environments

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