In this paper, a data aggregation scheme for VANETs will be proposed, namely, Catch-Up. First, the aggregation problem in VANETs will be defined, which is quite different from that in sensor networks. The basic idea in this scheme is to insert a delay before forwarding a report to the next hop. However, this scheme makes this delay more controllable in order to increase the probability that a report can be merged with reports ahead or reports behind. Intelligent delay control policies are made based on local observations of individual vehicles. A future reward model will be designed a to define the benefits of different delay-control policies, and then a decision tree is established to help a vehicle to choose an optimal policy from the perspective of long-term rewards. The Catch-Up scheme has a desirable property that for a given time frame and a given road section, the scheme can guarantee to aggregate all traffic reports into a single report within a certain distance. This property is particularly appealing for the facts that traffic reports could travel tens of kilometers, and a highly aggregated report could save a lot in communication overhead. The authors conducted simulation experiments with NS2 and GrooveNet, which demonstrate the effectiveness of the scheme developed. The remainder of this paper is organized as follows. Section 2 introduces related work. Section 3 presents the system model for our scheme. Section 4 describes the details of this aggregation scheme. Section 5 discusses two properties of this scheme. Section 6 presents simulation results. Section 7 concludes the whole paper.


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    Titel :

    Catch-up: A data aggregation scheme for VANETs


    Weitere Titelangaben:

    Catch-Up: ein Datenerfassungsschema für VANETs


    Beteiligte:
    Yu, Bo (Autor:in) / Gong, Jiayu (Autor:in) / Xu, Cheng-Zhong (Autor:in)


    Erscheinungsdatum :

    2008


    Format / Umfang :

    9 Seiten, 8 Bilder, 2 Tabellen, 22 Quellen




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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