Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/341274
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dc.coverage.spatialQuality of service improvements in mobile ad hoc network using hybrid simulated annealing stochastic diffusion search for virtual backbone optimization
dc.date.accessioned2021-09-20T10:37:43Z-
dc.date.available2021-09-20T10:37:43Z-
dc.identifier.urihttp://hdl.handle.net/10603/341274-
dc.description.abstractThe Mobile Ad hoc Network (MANET) is a collection of mobile nodes dependent on communication or a fixed infrastructure or a base station that provides connectivity. Each node in the MANET will either act as the host or act as the router or as both. All hosts will be able to freely move in a random manner and the network topology may also change with time. So, all routing protocols in the MANET will have to be adaptive and will have to further maintain the routes as the connectivity traits of the network may also change. To design an efficient and reliable routing protocol for the network is quite challenging and there may also be many other protocols developed which can be an attempt to accomplish the task efficiently. By supporting many constraints of the Quality of Service (QoS), the routing problem can be made Non-Deterministic Polynomial (NP)- complete. The protocols that remain in multipath routing are not always used for stability or for executing multipath routing. There are many more modified types of Ad Hoc On-demand Multipath Distance Vector (AOMDV) protocol that provides solutions to various routing issues. These are capable of resolving issues like route cut-off, the energy efficiency of nodes and route stability. Initially, there were many different algorithms that had the exact algorithms along with the approximate ones to address these problems. There were some more meta-heuristic algorithms that made use of the framework based on population. The Stochastic Diffusion Search (SDS) and the Artificial Bee Colony (ABC) were some examples that had an improved scheme along with good performance. They handled issues such as function optimization, image processing, data mining, combinatorial optimization problems, neural network training, and pattern recognition. For the purpose of this work, the Connected Dominating Set SDS (CDS-SDS), SDS with Tabu Search (TS) (SDS-TS) and Simulated Annealing (SA)-SDS (SA-SDS) methods are proposed. The primary objectives of this work of research were: to propose a new QoS-based AOMDV routing protocol for the MANET, to propose a new QoS load balanced CDS-SDS network backbone used for the MANET, to propose a new QoS load balanced SDS-TS network backbone used for the MANET, to propose a QoS load balanced SA-SDS network backbone for MANET. The routing protocol proposed for the AOMDV is a multipath extension to the AODV that discusses several issues in a QoS for the MANETs. The results prove the QoS-AOMDV with a jitter that is lower by about 44.44% for the 100 number of nodes, by about 18.18% for the 400 number of nodes on being compared to the AOMDV. An SDS algorithm may be used to determine an optimal coefficient that has a maximum and also an effective degree along with minimal residual nodes. Results prove that the CDS-SDS QoS can have a jitter that is higher by about 33.33% for the 100 number of nodes, and by about 21.42% for the 400 number of nodes on being compared to the QoS-AOMDV. newline
dc.format.extentxx,137 p.
dc.languageEnglish
dc.relationp122-1136
dc.rightsuniversity
dc.titleQuality of service improvements in mobile ad hoc network using hybrid simulated annealing stochastic diffusion search for virtual backbone optimization
dc.title.alternative
dc.creator.researcherKavitha, V R
dc.subject.keywordEngineering and Technology
dc.subject.keywordEngineering
dc.subject.keywordEngineering Electrical and Electronic
dc.subject.keywordQuality of service
dc.subject.keywordMobile ad hoc network
dc.description.note
dc.contributor.guideMoorthi, M
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.publisher.institutionFaculty of Information and Communication Engineering
dc.date.registered
dc.date.completed2020
dc.date.awarded2020
dc.format.dimensions21cm
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Information and Communication Engineering

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08_listoftables.pdf4.41 kBAdobe PDFView/Open
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10_listofabbreviations.pdf10.98 kBAdobe PDFView/Open
11_chapter1.pdf76.27 kBAdobe PDFView/Open
12_chapter2.pdf65.37 kBAdobe PDFView/Open
13_chapter3.pdf187.21 kBAdobe PDFView/Open
14_chapter4.pdf214.59 kBAdobe PDFView/Open
15_chapter5.pdf211.09 kBAdobe PDFView/Open
16_chapter6.pdf195.66 kBAdobe PDFView/Open
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18_references.pdf43.28 kBAdobe PDFView/Open
19_listofpublications.pdf58.23 kBAdobe PDFView/Open
80_recommendation.pdf55.05 kBAdobe PDFView/Open


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