Multipoint Relaying vs Chain-Branch-Leaf Clustering Performance in Optimized Link State Routing-based Vehicular Ad hoc Networks - Archive ouverte HAL Access content directly
Journal Articles IEEE Transactions on Intelligent Transportation Systems Year : 2020

Multipoint Relaying vs Chain-Branch-Leaf Clustering Performance in Optimized Link State Routing-based Vehicular Ad hoc Networks

Abstract

Routing protocols for vehicular ad hoc networks resort to clustering in order to optimize network performance. Concerning the Optimized Link State Routing (OLSR) protocol and the plethora of its derivatives, the multipoint relaying (MPR) technique has proven its efficiency as an accurate clustering scheme over the last two decades. However, it has been emphasized recently that the MPR technique, which was originally designed for open areas, does not benefit from the particular configuration of road sections which are intrinsically spatially constrained. A clustering scheme exploiting this particularity, namely Chain-Branch-Leaf (CBL), has been introduced in order to enhance the flooding of broadcast traffic, including that related to routing operations. In this paper, both MPR and CBL are evaluated through MATLAB simulation over several scenarios based on realistic road configurations and traffic generated with SUMO simulator. The results show that CBL actually reduces the number of nodes acting as relays (cluster-heads) in the network, thus decreasing the routing traffic related to creation and retransmission of topology control (TC) messages. Also, they show that, with CBL, the nodes chosen as relays remain longer in this role, thus favoring the overall network stability, and that most of the nodes remain attached longer to the same relay than with the MPR technique.
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Dates and versions

hal-02069029 , version 1 (15-03-2019)

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Lucas Rivoirard, Martine Wahl, Patrick Sondi. Multipoint Relaying vs Chain-Branch-Leaf Clustering Performance in Optimized Link State Routing-based Vehicular Ad hoc Networks. IEEE Transactions on Intelligent Transportation Systems, 2020, 21 (3), pp.1034-1043. ⟨10.1109/TITS.2019.2900767⟩. ⟨hal-02069029⟩
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