Intelligent Agents in Mobile Vehicular Ad-Hoc Networks: Leveraging Trust Modeling Based on Direct Experience with Incentives for Honesty

In this paper we introduce a multi-faceted trust model of use for the application of ad-hoc vehicular networks (VANETs) - scenarios where agents representing drivers exchange information with other drivers regarding road and traffic conditions. We argue that there is a need to model trust in various...

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Vydáno v:2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Ročník 2; s. 243 - 247
Hlavní autoři: Minhas, U F, Jie Zhang, Tran, T, Cohen, R
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.08.2010
Témata:
Ad hoc networks
Bismuth
Equations
Information exchange
Intelligent agent
Mathematical model
Roads
Traffic management
Trust modeling
VANET
Vehicles
ISBN:9781424484829, 1424484820
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Abstract In this paper we introduce a multi-faceted trust model of use for the application of ad-hoc vehicular networks (VANETs) - scenarios where agents representing drivers exchange information with other drivers regarding road and traffic conditions. We argue that there is a need to model trust in various dimensions and that combining these elements effectively can assist agents in making transportation decisions. We then introduce two new elements to our proposed model: i) distinguishing direct and indirect reports that are shared ii) employing a penalty for misleading reports, to promote honesty. We demonstrate how these two elements together serve to increase the value of the trust model, through a series of experiments of simulated traffic. In brief, we present a framework to facilitate the effective sharing of information in VANET environments between agents representing the vehicles.
AbstractList In this paper we introduce a multi-faceted trust model of use for the application of ad-hoc vehicular networks (VANETs) - scenarios where agents representing drivers exchange information with other drivers regarding road and traffic conditions. We argue that there is a need to model trust in various dimensions and that combining these elements effectively can assist agents in making transportation decisions. We then introduce two new elements to our proposed model: i) distinguishing direct and indirect reports that are shared ii) employing a penalty for misleading reports, to promote honesty. We demonstrate how these two elements together serve to increase the value of the trust model, through a series of experiments of simulated traffic. In brief, we present a framework to facilitate the effective sharing of information in VANET environments between agents representing the vehicles.
Author Tran, T
Jie Zhang
Cohen, R
Minhas, U F
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  surname: Jie Zhang
  fullname: Jie Zhang
  organization: Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore, Singapore
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  fullname: Tran, T
  organization: Sch. of Inf. Technol. & Eng., Univ. of Ottawa, Ottawa, ON, Canada
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  givenname: R
  surname: Cohen
  fullname: Cohen, R
  organization: David R. Cheriton Sch. of Comput. Sci., Univ. of Waterloo, Waterloo, ON, Canada
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Snippet In this paper we introduce a multi-faceted trust model of use for the application of ad-hoc vehicular networks (VANETs) - scenarios where agents representing...
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StartPage 243
SubjectTerms Ad hoc networks
Bismuth
Equations
Information exchange
Intelligent agent
Mathematical model
Roads
Traffic management
Trust modeling
VANET
Vehicles
Title Intelligent Agents in Mobile Vehicular Ad-Hoc Networks: Leveraging Trust Modeling Based on Direct Experience with Incentives for Honesty
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