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Please use this identifier to cite or link to this item: http://hdl.handle.net/10023/2022
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Title: IRONMAN : Using social networks to add incentives and reputation to opportunistic networks
Authors: Bigwood, Gregory John
Henderson, Tristan
Keywords: QA75 Electronic computers. Computer science
Issue Date: 9-Oct-2011
Citation: Bigwood , G J & Henderson , T 2011 , ' IRONMAN : Using social networks to add incentives and reputation to opportunistic networks ' Paper presented at The Third IEEE International Conference on Social Computing (SocialCom) , Boston , United States , 9/10/11 - 11/10/11 , pp. 65-72 .
conference
Abstract: Opportunistic networks enable users to communicate in the absence of network infrastructure. But forwarding messages in such a network incurs costs for nodes in terms of energy and storage. This may lead to nodes being selfish and not forwarding messages for other nodes, resulting in degraded network performance. This paper presents a novel incentive mechanism for opportunistic networks that uses pre-existing social-network information to detect and punish selfish nodes, incentivising them to participate in the network. Trace-driven simulations demonstrate that our mechanism performs better than existing mechanisms, and that social-network information can also be used to improve existing incentive mechanisms.
Version: Preprint
Description: Paper published in IEEE Proceedings of SocialCom 2011.
Status: Peer reviewed
URI: http://hdl.handle.net/10023/2022
http://www.iisocialcom.org/conference/socialcom2011/index.html
DOI: http://dx.doi.org/10.1109/PASSAT/SocialCom.2011.60
Type: Conference paper
Rights: © 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Appears in Collections:University of St Andrews Research
Computer Science Research



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