Please use this identifier to cite or link to this item:
Full metadata record
DC FieldValueLanguage
dc.contributor.authorAlwadani, Dhaiffallah-
dc.contributor.authorKolberg, Mario-
dc.contributor.authorBuford, John-
dc.description.abstractIn this paper we investigate the behaviour of Opportunistic Native Multicast under node churn. Previously, we have introduced an Opportunistic Native Multicast approach that facilitates native multicast where possible and which reverts to using overlay multicast when needed. Here, we are evaluating Overlay Native Multicast in a more realistic environment considering the effect of network churn and propose election algorithms to offer resilience and adaptivity required in the real world. We have developed a mechanism where the network can autonomously and deterministically elect a primary node for each multicast island. We have further investigated ways to improve the efficiency and responsiveness of the protocol by introducing a secondary node selection process. We have tested our proposed improvements using Oversim simulation. We show that Opportunistic Native Multicast can achieve success rates well above 90 percent despite realistic levels of node churn.en_UK
dc.relationAlwadani D, Kolberg M & Buford J (2016) Opportunistic native multicast under churn In: Proceedings of 2016 SAI Computing Conference, SAI 2016, Piscataway, NJ, USA: IEEE. 2016 SAI Computing Conference (SAI), 13.7.2016 - 15.7.2016, London, pp. 644-648.-
dc.rightsThe publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.-
dc.subjectOverlay Multicastingen_UK
dc.subjectHybrid Multicastingen_UK
dc.titleOpportunistic native multicast under churnen_UK
dc.typeConference Paperen_UK
dc.rights.embargoreasonThe publisher does not allow this work to be made publicly available in this Repository therefore there is an embargo on the full text of the work.-
dc.type.statusBook Chapter: publisher version-
dc.citation.btitleProceedings of 2016 SAI Computing Conference, SAI 2016-
dc.citation.conferencename2016 SAI Computing Conference (SAI)-
dc.publisher.addressPiscataway, NJ, USA-
dc.contributor.affiliationUniversity of Stirling-
dc.contributor.affiliationComputing Science - CSM Dept-
dc.contributor.affiliationAvaya Labs Research-
Appears in Collections:Computing Science and Mathematics Conference Papers and Proceedings

Files in This Item:
File Description SizeFormat 
07556050.pdf88.89 kBAdobe PDFUnder Permanent Embargo    Request a copy

This item is protected by original copyright

Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.

If you believe that any material held in STORRE infringes copyright, please contact providing details and we will remove the Work from public display in STORRE and investigate your claim.