Flexible and Scalable Routing Approach for Mobile Ad Hoc Networks by Function Approximation of Q-Learning

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atmire.migration.oldid4458
dc.contributor.advisorAlhajj, Reda
dc.contributor.advisorRokne, Jon
dc.contributor.authorElzohbi, Mohamad
dc.contributor.committeememberKawash, Jalal
dc.contributor.committeememberHelaoui, Mohamed
dc.date.accessioned2016-05-20T14:52:42Z
dc.date.available2016-05-20T14:52:42Z
dc.date.issued2016
dc.date.submitted2016en
dc.description.abstractWireless mobile devices are rapidly spreading to the extent that it is hard to find a person not exposed to such technology. These devices could be connected directly or indirectly by wireless channels to form a mobile ad hoc network (MANET). Finding a route for flow from a source to a destination in a network is known as routing. Dynamic topology and unstable link states are the main problems facing routing in MANETs. This thesis employs reinforcement learning, namely Q-learning to develop a routing mechanism. Features inspired from the network are used in approximating the Q-function to form a new intelligent routing metric. This way, the routing process concentrates on specific routes instead of network-wide broadcasting. Accordingly, it is possible to achieve flexibility and scalability in routing. Advantages of the proposed routing technique have been highlighted by conducting experiments in two MANETs environments, namely hand-held devices based MANETs and VANETs.en_US
dc.identifier.citationElzohbi, M. (2016). Flexible and Scalable Routing Approach for Mobile Ad Hoc Networks by Function Approximation of Q-Learning (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/26186en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/26186
dc.identifier.urihttp://hdl.handle.net/11023/3034
dc.language.isoeng
dc.publisher.facultyGraduate Studies
dc.publisher.institutionUniversity of Calgaryen
dc.publisher.placeCalgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.
dc.subjectArtificial Intelligence
dc.subjectComputer Science
dc.subject.classificationMobile ad hoc networksen_US
dc.subject.classificationReinforcement learningen_US
dc.subject.classificationQ-learningen_US
dc.subject.classificationRouting protocolen_US
dc.subject.classificationFunction approximationen_US
dc.titleFlexible and Scalable Routing Approach for Mobile Ad Hoc Networks by Function Approximation of Q-Learning
dc.typemaster thesis
thesis.degree.disciplineComputer Science
thesis.degree.grantorUniversity of Calgary
thesis.degree.nameMaster of Science (MSc)
ucalgary.item.requestcopytrue
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