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Published (Version of record)CC BY V4.0, Open Access
Published (Version of record)CC BY V4.0, Open
Journal article
Investigation of Data Quality Assurance across IoT Protocol Stack for V2I Interactions
Smart Cities, Vol.6(5), pp.2680-2705
10/2023
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Abstract
Networking protocols have undergone significant developments and adaptations to cater for unique communication needs within the IoT paradigm. However, meeting these requirements in the context of vehicle-to-infrastructure (V2I) communications becomes a multidimensional problem due to factors like high mobility, intermittent connectivity, rapidly changing topologies, and an increased number of nodes. Thus, examining these protocols based on their characteristics and comparative analyses from the literature has shown that there is still room for improvement, particularly in ensuring efficiency in V2I interactions. This study aims to investigate the most viable network protocols for V2I communications, focusing on ensuring data quality (DQ) across the first three layers of the IoT protocol stack. This presents an improved understanding of the performance of network protocols in V2I communication. The findings of this paper showed that although each protocol offers unique strengths when evaluated against the identified dimensions of DQ, a cross-layer protocol fusion may be necessary to meet specific DQ dimensions. With the complexities and specific demands of V2I communications, it's clear that no single protocol from our tri-layered perspective can solely fulfil all IP-based communication requirements given that the V2I communication landscape is teeming with heterogeneity, where a mixture of protocols is required to address unique communication demands.
Details
- Title
- Investigation of Data Quality Assurance across IoT Protocol Stack for V2I Interactions
- Creators
- Danladi Suleman - University of the Sunshine CoastRania Shibl - University of the Sunshine CoastKeyvan Ansari - Murdoch University
- Publication Details
- Smart Cities, Vol.6(5), pp.2680-2705
- Publisher
- MDPI
- Number of pages
- 26
- Identifiers
- 991013351557102368
- Copyright
- © 2023 by the authors.
- Academic Unit
- Faculty of Science and Engineering
- Language
- English
- Resource Type
- Journal article