Petri, I., Diaz-Montes, J., Rana, O., Punceva, M., Rodero, I. & Parashar, M. (2017) IEEE Transactions on Services Computing [Info Economics, Q1]

Publicat: 24 Noiembrie 2020

Petri, I., Diaz-Montes, J., Rana, O., Punceva, M., Rodero, I. & Parashar, M. (2017) Modelling and implementing social community clouds. IEEE Transactions on Services Computing, 10(3), 410-422.

DOI: https://doi.org/10.1109/TSC.2015.2470258

✓ Publisher: IEEE
✓ Web of Science Core Collection: Science Citation Index Expanded, Social Sciences Citation Index
✓ Categories: Computer Science, Information Systems; Computer Science, Software Engineering
✓ Article Influence Score (AIS): 1.331 (2017) / Q1 in all categories

Abstract: As the number of people who interact on social networks increases, and coupled with the greater capability made available within our computational devices, there is the potential to establish "Social Clouds"-a resource sharing infrastructure that enable people who have trust relationships to come together to share computational/data services within a community. Social clouds can also provide the means to enhance multi-user collaboration and greatly stimulate the exchange of resources among participants. Recent research in the establishment and use of Social Clouds has raised significant interest by proposing an environment where users are able to trade resources mediated by a social networking mechanism. In such a cloud environment the incentives for sharing can represent a solution for improving resource utilisation and for making available additional capacity to friends and collaborators. In this paper we demonstrate how revenue can be earned within a social cloud community, by executing internal (intra community) and external (inter community) tasks. A number of different scenarios are first investigated through simulation, using the PeerSim simulator, in order to validate our approach. We use two key metrics: revenue and reputation, to evaluate how the system dynamics change as new tasks are added to one or more communities for execution, along with additional behaviours, such as nodes migrating from one community to another, or selectively reporting on the outcome of task execution. Subsequently, we develop a practical deployment using a federated cloud scenario using the CometCloud system-deployed over three sites: Cardiff (UK), Rutgers and Indiana. We show how approaches that have been simulated in PeerSim can be implemented in practice.

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