Show simple item record

dc.contributor.authorFølstad, Eirik Larsen
dc.contributor.authorHelvik, Bjarne Emil
dc.date.accessioned2015-02-03T11:10:45Z
dc.date.accessioned2016-06-20T13:20:32Z
dc.date.available2015-02-03T11:10:45Z
dc.date.available2016-06-20T13:20:32Z
dc.date.issued2014
dc.identifier.citationRak, Jacek [Eds.] Proceedings of RNDM 2014 6th International Workshop on Reliable Networks Design and Modeling p. 158-164, IEEE Communications Society, 2014nb_NO
dc.identifier.isbn978-1-4799-7039-1
dc.identifier.urihttp://hdl.handle.net/11250/2393291
dc.description.abstractThe wireless access to any service in different contexts is nowadays taken for granted. However, the dependability requirements are different for various services and contexts. Critical services put high requirement on the service reliability, i.e., the probability of no service interruption should be close to one. Dual homing may be used to increase the service reliability in a multi technology, multi operator wireless environment, where the user's mobility necessitates access point selections and handovers. To allow the user to assess the risk of the service session, a prediction of the service reliability is necessary. This prediction must fulfil the need for the optimal sequence of access point selections and handovers with regard to service reliability and being computation efficient to accomplish the need for the real-time operation. We demonstrate how genetic algorithms (GA) may be used to predict and to improve the (near) optimal service reliability by fast and simple heuristics, far more computationally efficient than an Integer Linear Programming (ILP) optimization.nb_NO
dc.language.isoengnb_NO
dc.publisherIEEEnb_NO
dc.titleUsing genetic algorithms to improve the reliability of dual homed wireless critical servicesnb_NO
dc.typeChapternb_NO
dc.date.updated2015-02-03T11:10:44Z
dc.description.versionacceptedVersion
dc.source.pagenumber158-164nb_NO
dc.source.journalProceedings of RNDM 2014 6th International Workshop on Reliable Networks Design and Modelingnb_NO
dc.identifier.doi10.1109/RNDM.2014.7014946
dc.identifier.cristin1212289
dc.description.localcode(c) 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, 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 components of this work in other works.nb_NO


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record