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Fuzzy-based beaconless probabilistic broadcasting for information dissemination in urban VANET - 2020

Fuzzy-based beaconless probabilistic broadcasting for information dissemination in urban VANET

Research Area:  Vehicular Ad Hoc Networks

Abstract:

Multi-hop broadcasting in Vehicular Ad Hoc Network (VANET) is the basic building block for renovating on-road travel experiences because it supports message dissemination among a large number of travelers in real-time. In order to make forwarding decisions, 1-hop neighbor table is suggested to be maintained at each vehicle by exchanging beacon packets on a periodic basis. However, a network crowded with both data packets and beacons gives rise to broadcast storms, resulting in insignificant resource consumption. Therefore, a beaconless approach would be a better solution that can control packet flow throughout the network, owing to minimizing packet collision and drop rate. Some recent literature that does not rely on beacon information broadcasts ample amounts of data packets, promoting wastage of bandwidth. To handle such issues, a Fuzzy-based Beaconless Probabilistic Broadcasting Algorithms (FBBPA) is proposed to notify vehicles about an event in less broadcasting. It is a receiver oriented broadcast suppression technique, where the forwarding probability of the packets in vehicles buffer is decided on the basis of their distance, angular orientation, movement direction and buffer load delay. The resultant probability is used to reschedule the packet. Among all the packets in the vehicles buffer, the one having the highest priority at an instant is broadcasted first. For accident and advertisement packets, the analysis through simulation reveals that the proposed algorithm outperformed the compared protocols in terms of reachability (Information coverage), average delay and saved rebroadcast.

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Author(s) Name:  Ankita Srivastava,Arun Prakash,Rajeev Tripathi

Journal name:  Ad Hoc Networks

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Publisher name:  Elsevier B.V.

DOI:  10.1016/j.adhoc.2020.102285

Volume Information:  Volume 108, 1 November 2020, 102285