Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/462096
Title: Unsupervised Clustering Algorithms for Reliable Routing and Data Dissemination using Optimization Techniques in Vehicular Adhoc Networks
Researcher: Radhika, D
Guide(s): BHUVANESWARI A
Keywords: Computer Science
Computer Science Hardware and Architecture
Engineering and Technology
University: Bharathidasan University
Completed Date: 2021
Abstract: Today the usage of vehicles have increased tremendously. VANET is Vehicular Ad newlinehoc Network which promotes the road safety among the vehicles. In recent years, VANETs newlinehave emerged as a significant research area in the transportation sector. VANETs are newlineconsidered as reliable networks for vehicular communication on highways or urban newlineenvironments through the wireless medium. The purpose of VANET is to foster the QoS, newlinehigh connectivity, bandwidth and security besides the number of challenges. The issues of newlineVANET are routing and data dissemination due to its dynamic movement. Therefore, the newlineresearch work tries to find best clustering algorithms and optimization techniques for newlinereliable routing and data dissemination. newlineThe purpose of this research is to form cluster with a selected CH (Cluster Head) and newlineto select the optimal number of CHs. The path can be constructed from the source CH to the newlinedestination CH by sending the beacon messages. The proposed research work are as follows newlineMMBCMDSOR (Mean shift Margin Boost Clustering based Multivariate Dolphin Swarm newlineOptimized Routing), BEXCMWO (Bagging Ensemble X-Means Clustering based Multi newlinecriteria Whale Optimization), MIBCMCSO (Mutual Informated Brown Agglomerative newlineClustering based Multiattribute Cockroach Swarm Optimization) and DLRSCODOR (Deep newlineLearned Ruzicka Spectral Clustering based Oppositional Dragonfly Optimized Routing). newlineThese research contributions were developed using the unsupervised clustering algorithms newlineand optimization techniques to achieve routing and dissemination in an efficient manner. The newlinemobility parameters such as density, direction, distance and velocity were used for newlinepartitioning the network into clusters. To select the CH for a cluster, unsupervised clustering newlinealgorithms were used and for the selection of optimal CHs various optimization techniques newlinewere utilized. A beacon message is sent from the selected CHs to destination for the optimal newlinepath selection and thus achieves data dissemination. newlineAll the four proposed algorithms are impl
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URI: http://hdl.handle.net/10603/462096
Appears in Departments:Department of Computer Science and Applications

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10. cha 6.pdfAttached File1.18 MBAdobe PDFView/Open
11. annex.pdf3.48 MBAdobe PDFView/Open
1. tit.pdf253.14 kBAdobe PDFView/Open
2. pre.pdf615.46 kBAdobe PDFView/Open
3. con.pdf126.77 kBAdobe PDFView/Open
4. abs.pdf5.46 kBAdobe PDFView/Open
5. cha 1.pdf436.67 kBAdobe PDFView/Open
6. cha 2.pdf983.78 kBAdobe PDFView/Open
7. cha 3.pdf1.16 MBAdobe PDFView/Open
80_recommendation.pdf3.48 MBAdobe PDFView/Open
8. cha 4.pdf1.34 MBAdobe PDFView/Open
9. cha 5.pdf1.08 MBAdobe PDFView/Open
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