Certain investigations on performance enhancement of vehicular adhoc network based on traffic scenarios

dc.contributor.guideNandalal, V
dc.coverage.spatialCertain investigations on performance enhancement of vehicular adhoc network based on traffic scenarios
dc.creator.researcherSuganyadevi, K
dc.date.accessioned2025-06-09T05:26:10Z
dc.date.available2025-06-09T05:26:10Z
dc.date.awarded2025
dc.date.completed2025
dc.date.registered
dc.description.abstractThe route-discovery technique in VANET is problematic owing to newlinethe strong network design, which makes communication difficult in both the newlineuplink and downlink directions. The fuzzy strategy and recital optimization are newlineused to offer effective connectivity in vehicular adhoc networks (VANETs) in newlineorder to offer high security and authenticated optimal route. newlineIn recent years, the popularity of VANET in wireless intelligent newlinetransportation systems has significantly increased. It is difficult to determine newlinethe quickest path between the source and the target in a VANET traffic system. newlineLonger routes feature increased network overhead, more expensive newlineconnections, more path failures, and worse routing efficiency. Identifying the newlineshortest route in optimization, often known as the Travelling Salesman Problem newline(TSP) and traffic congestion, is a well-known combinatorial optimization newlinechallenge with various practical applications. To improve routing efficiency, newlinethe HACOSMO (Hybrid-Ant Colony Optimization with Spider Monkey newlineOptimization) system s recommended meta-heuristic approach finds the newlineshortest path using distance and traffic based principles. The simulation NS-2 newlineoutcomes focused on the efficiency of the proposed method beats the other newlineexisting methods like ACO, GRACO, OACO, and IDBACOR in terms of newlineoverhead, throughput, latency, packet failure, and message transmission ratio. newlineAccording to HACOSMO, routing overhead is 8% to 11% under IDBACOR, newline10% to 14% under GRACO,19% to 31% under OACO, and 24% to 37% under newlineACO for a variety of vehicle counts and speed ranges. When compared to newlineIDBACOR, the proposed method enhances throughput by 3% to 7%, 6% to 8% newlinewhen compared to GRACO, 11% to 15% when compared to OACO, and 16% newlineto 25% when compared to ACO. newline
dc.description.note
dc.format.accompanyingmaterialNone
dc.format.dimensions21cm.
dc.format.extentxxv,170p.
dc.identifier.researcherid
dc.identifier.urihttp://hdl.handle.net/10603/644813
dc.languageEnglish
dc.publisher.institutionFaculty of Information and Communication Engineering
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.relationp.158-169
dc.rightsuniversity
dc.source.universityUniversity
dc.subject.keywordComputer Science
dc.subject.keywordComputer Science Information Systems
dc.subject.keywordEngineering and Technology
dc.subject.keywordfuzzy strategy and recital optimization
dc.subject.keywordRoute-discovery technique in VANET
dc.subject.keyworduplink and downlink directions
dc.titleCertain investigations on performance enhancement of vehicular adhoc network based on traffic scenarios
dc.title.alternative
dc.type.degreePh.D.

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