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Conference Paper: Utility-maximizing data dissemination in socially selfish cognitive radio networks
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TitleUtility-maximizing data dissemination in socially selfish cognitive radio networks
 
AuthorsLi, H1
Huang, W1
Wu, C1
Li, Z2
Lau, FCM1
 
Issue Date2011
 
PublisherIEEE, Computer Society. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1001499
 
CitationThe IEEE 8th International Conference on Mobile Adhoc and Sensor Systems (MASS), Valencia, Spain, 17-22 October 2011. In Proceedings of 8th MASS, 2011, p. 212-221 [How to Cite?]
DOI: http://dx.doi.org/10.1109/MASS.2011.28
 
AbstractIn cognitive radio networks, the occupation patterns of the primary users can be very dynamic, which makes optimization (e.g., utility maximization) of data dissemination among secondary users difficult. Even under the assumption that all secondary users are fully collaborative, the optimization requires cross-layer decision making which is challenging. The challenge escalates if users are socially selfish, who prefer to relay data only to those other users with whom there are social ties. Such social selfishness of users translates into new constraints on network protocol design. There has been no study so far on the impact of social selfishness on data dissemination in cognitive radio networks. In this paper, we consider social selfishness of secondary users, and propose the design of a joint end-to-end rate control, routing, and channel allocation protocol which can maximize the overall throughput utility of multi-session unicast in cognitive radio networks. We give a distributed implementation of the protocol. Based on a Lyapunov optimization framework, we address social preferences of users using differentiated buffer sizes and relay rates for different data sessions, and apply back-pressure based transmission scheduling to achieve guaranteed utility optimality. A unique contribution of our Lyapunov optimization is that only a finite-sized buffer is required at each user node, which sets our design apart from other designs in existing literature where they assume infinite buffers. We investigate the the optimality of our protocol and the impact of user social selfishness using both theoretical analysis and extensive simulations. © 2011 IEEE.
 
ISBN978-0-7695-4469-4
 
DOIhttp://dx.doi.org/10.1109/MASS.2011.28
 
ReferencesReferences in Scopus
 
DC FieldValue
dc.contributor.authorLi, H
 
dc.contributor.authorHuang, W
 
dc.contributor.authorWu, C
 
dc.contributor.authorLi, Z
 
dc.contributor.authorLau, FCM
 
dc.date.accessioned2011-07-27T01:39:55Z
 
dc.date.available2011-07-27T01:39:55Z
 
dc.date.issued2011
 
dc.description.abstractIn cognitive radio networks, the occupation patterns of the primary users can be very dynamic, which makes optimization (e.g., utility maximization) of data dissemination among secondary users difficult. Even under the assumption that all secondary users are fully collaborative, the optimization requires cross-layer decision making which is challenging. The challenge escalates if users are socially selfish, who prefer to relay data only to those other users with whom there are social ties. Such social selfishness of users translates into new constraints on network protocol design. There has been no study so far on the impact of social selfishness on data dissemination in cognitive radio networks. In this paper, we consider social selfishness of secondary users, and propose the design of a joint end-to-end rate control, routing, and channel allocation protocol which can maximize the overall throughput utility of multi-session unicast in cognitive radio networks. We give a distributed implementation of the protocol. Based on a Lyapunov optimization framework, we address social preferences of users using differentiated buffer sizes and relay rates for different data sessions, and apply back-pressure based transmission scheduling to achieve guaranteed utility optimality. A unique contribution of our Lyapunov optimization is that only a finite-sized buffer is required at each user node, which sets our design apart from other designs in existing literature where they assume infinite buffers. We investigate the the optimality of our protocol and the impact of user social selfishness using both theoretical analysis and extensive simulations. © 2011 IEEE.
 
dc.description.naturepublished_or_final_version
 
dc.description.otherThe IEEE 8th International Conference on Mobile Adhoc and Sensor Systems (MASS), Valencia, Spain, 17-22 October 2011. In Proceedings of 8th MASS, 2011, p. 212-221
 
dc.identifier.citationThe IEEE 8th International Conference on Mobile Adhoc and Sensor Systems (MASS), Valencia, Spain, 17-22 October 2011. In Proceedings of 8th MASS, 2011, p. 212-221 [How to Cite?]
DOI: http://dx.doi.org/10.1109/MASS.2011.28
 
dc.identifier.citeulike10181183
 
dc.identifier.doihttp://dx.doi.org/10.1109/MASS.2011.28
 
dc.identifier.epage221
 
dc.identifier.hkuros187760
 
dc.identifier.isbn978-0-7695-4469-4
 
dc.identifier.openurl
 
dc.identifier.scopuseid_2-s2.0-83355161629
 
dc.identifier.spage212
 
dc.identifier.urihttp://hdl.handle.net/10722/135697
 
dc.languageeng
 
dc.publisherIEEE, Computer Society. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1001499
 
dc.relation.ispartofProceedings of the IEEE International Conference on Mobile Adhoc and Sensor Systems, MASS 2011
 
dc.relation.referencesReferences in Scopus
 
dc.rightsIEEE International Conference on Mobile Adhoc and Sensor Systems Proceedings. Copyright © IEEE, Computer Society.
 
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License
 
dc.rights©2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
 
dc.titleUtility-maximizing data dissemination in socially selfish cognitive radio networks
 
dc.typeConference_Paper
 
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Author Affiliations
  1. The University of Hong Kong
  2. University of Calgary