Cuckoos United: Extending Cuckoo Filters for Message Dissemination in Vehicular Networks
Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed › peer-review
Contributors
Abstract
In Vehicular Ad Hoc Networks (VANETs), neighbor information of vehicles is an important prerequisite for many use cases ranging from intersection collision avoidance up to more complex applications like vehicular platooning. A prime use case of this neighbor information is message forwarding in larger scenarios. The conventional way of transferring this neighbor information in VANETs is beaconing - simple one-hop broadcasts periodically transmitted by each vehicle including position and mobility information. A key requirement for efficient beaconing protocols is to keep the size of beacons small to avoid channel congestion. One possible approach to reduce the beacon size is to transmit the information in a compressed form using a probabilistic data structure, like a Cuckoo Filter. In order to inform nodes at larger scenarios, recent works have shown that extending the beaconing approach with two-hop neighbor information is beneficial. In this paper, we employ such a beaconing scheme and use a two-hop neighbor table approach utilizing Cuckoo Filters for warning message dissemination. A core contribution of our work is the extension of standard Cuckoo Filters to support the union operation which is necessary for proper two-hop neighbor management. We compare our Cuckoo Filter approach against a naïve approach that transmits raw information for beaconing to evaluate the effectiveness of our system. Our results show that our Cuckoo Filter approach performs better than a naïve approach in terms of channel utilization and shows an increased number of covered two-hop neighbors for warning message dissemination.
Details
Original language | English |
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Title of host publication | 11th IEEE International Conference on Computing, Networking and Communications (ICNC 2024) |
Place of Publication | Big Island, HI |
Pages | 1144-1148 |
Number of pages | 5 |
ISBN (electronic) | 9798350370997 |
Publication status | Published - 1 Feb 2024 |
Peer-reviewed | Yes |
Externally published | Yes |
External IDs
ORCID | /0009-0008-5617-9528/work/161406210 |
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Scopus | 85197874305 |