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    From grids to clouds: a collective intelligence study for inter-cooperated infrastructures

    Sotiriadis, Stelios and Bessis, N. and Sant, P. and Maple, C. From grids to clouds: a collective intelligence study for inter-cooperated infrastructures. In: Gentzsch, W. and Lorenz, P. and Dini, O. (eds.) ADVCOMP 2010, The Fourth International Conference on Advanced Engineering Computing and Applications in Sciences. IARIA. ISBN 9781612081014.

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    Abstract

    Recently, more effort has been put into developing interoperable and distributed environments that offer users exceptional opportunities for utilizing resources over the internet. By utilising grids and clouds, resource consumers and providers, they gain significant benefits by either using or purchasing the computer processing capacities and the information provided by data centres. On the other hand, the collective intelligence paradigm is characterized as group based intelligence that emerges from the collaboration of many individuals, who in turn, define a coordinated knowledge model. It is envisaged that such a knowledge model could be of significant advantage if it is incorporated within the grid and cloud community. The dynamic load and access balancing of the grid and cloud data centres and the collective intelligence provides multiple opportunities, involving resource provisioning and development of scalable and heterogeneous applications. The contribution of this paper is that by utilizing grid and cloud resources, internal information stored within a public profile of each participant, resource providers as well as consumers, can lead to an effective mobilization of improved skills of members. We aim to unify the grid and cloud functionality as consumable computational power, for a) discussing the supreme advantages of such on-line resource utilization and provisioning models and b) analyzing the impact of the collective intelligence in the future trends of the aforementioned technologies.

    Metadata

    Item Type: Book Section
    Additional Information: ISSN: 2308-4499
    School: Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences
    Research Centres and Institutes: Birkbeck Knowledge Lab
    Depositing User: Stelios Sotiriadis
    Date Deposited: 19 Jun 2018 12:53
    Last Modified: 09 Aug 2023 12:43
    URI: https://eprints.bbk.ac.uk/id/eprint/21890

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