Publication:
Analysis of distributed algorithms for density estimation in VANETs

dc.contributor.departmentDepartment of Electrical and Electronics Engineering
dc.contributor.departmentDepartment of Computer Engineering
dc.contributor.departmentGraduate School of Sciences and Engineering
dc.contributor.kuauthorAkhtar, Nabeel
dc.contributor.kuauthorErgen, Sinem Çöleri
dc.contributor.kuauthorÖzkasap, Öznur
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.contributor.schoolcollegeinstituteGRADUATE SCHOOL OF SCIENCES AND ENGINEERING
dc.date.accessioned2024-11-09T23:36:54Z
dc.date.issued2012
dc.description.abstractVehicle density is an important system metric used in monitoring road traffic conditions. Most of the existing methods for vehicular density estimation require either building an infrastructure, such as pressure pads, inductive loop detector, roadside radar, cameras and wireless sensors, or using a centralized approach based on counting the number of vehicles in a particular geographical location via clustering or grouping mechanisms. These techniques however suffer from low reliability and limited coverage as well as high deployment and maintenance cost. In this paper, we propose fully distributed and infrastructure-free mechanisms for the density estimation in vehicular ad hoc networks. Unlike previous distributed approaches, that either rely on group formation, or on vehicle flow and speed information to calculate density, our study is inspired by the mechanisms proposed for system size estimation in peer-to-peer networks. We adapted and implemented three fully distributed algorithms, namely Sample & Collide, Hop Sampling and Gossip-based Aggregation. The extensive simulations of these algorithms at different vehicle traffic densities and area sizes for both highways and urban areas reveal that Hop Sampling provides the highest accuracy in least convergence time and introduces least overhead on the network, but at the cost of higher load on the initiator node.
dc.description.indexedbyWOS
dc.description.openaccessNO
dc.description.publisherscopeInternational
dc.description.sponsoredbyTubitakEuN/A
dc.description.sponsorshipTurk Telekom [11315-07] Our work was supported by Turk Telekom under Grant Number 11315-07. We would like to thank Irem Nizamoglu and Orkhan Badirkhanli for their invaluable contribution during the initial phase of our work.
dc.identifier.isbn978-1-4673-4995-6
dc.identifier.isbn978-1-4673-4994-9
dc.identifier.issn2157-9857
dc.identifier.urihttps://hdl.handle.net/20.500.14288/12740
dc.identifier.wos315437900022
dc.keywordsInformation
dc.keywordsVehicles
dc.keywordsRoads
dc.keywordsPeer to peer computing
dc.keywordsEstimation
dc.keywordsHeuristic algorithms
dc.keywordsUrban areas
dc.language.isoeng
dc.publisherIeee
dc.relation.ispartof2012 IEEE Vehicular Networking Conference (VNC)
dc.subjectComputer science
dc.subjectHardware architecture
dc.subjectEngineering
dc.subjectElectrical electronic engineering
dc.titleAnalysis of distributed algorithms for density estimation in VANETs
dc.typeConference Proceeding
dspace.entity.typePublication
local.contributor.kuauthorAkhtar, Nabeel
local.contributor.kuauthorErgen, Sinem Çöleri
local.contributor.kuauthorÖzkasap, Öznur
local.publication.orgunit1GRADUATE SCHOOL OF SCIENCES AND ENGINEERING
local.publication.orgunit1College of Engineering
local.publication.orgunit2Department of Electrical and Electronics Engineering
local.publication.orgunit2Department of Computer Engineering
local.publication.orgunit2Graduate School of Sciences and Engineering
relation.isOrgUnitOfPublication21598063-a7c5-420d-91ba-0cc9b2db0ea0
relation.isOrgUnitOfPublication89352e43-bf09-4ef4-82f6-6f9d0174ebae
relation.isOrgUnitOfPublication3fc31c89-e803-4eb1-af6b-6258bc42c3d8
relation.isOrgUnitOfPublication.latestForDiscovery21598063-a7c5-420d-91ba-0cc9b2db0ea0
relation.isParentOrgUnitOfPublication8e756b23-2d4a-4ce8-b1b3-62c794a8c164
relation.isParentOrgUnitOfPublication434c9663-2b11-4e66-9399-c863e2ebae43
relation.isParentOrgUnitOfPublication.latestForDiscovery8e756b23-2d4a-4ce8-b1b3-62c794a8c164

Files