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AI-Enabled Reliable...
AI-Enabled Reliable Channel Modelling Architecture for FoG Computing Vehicular Networks’
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- Sodhro, Ali (author)
- Linköpings universitet,Databas och informationsteknik,Tekniska fakulteten,Sukkur IBA Univ, Pakistan
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- Sodhro, Gul Hassan (author)
- Shah Abdul Latif Univ Khairpur Mirs, Pakistan
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- Guizani, Mohsen (author)
- Qatar Univ, Qatar
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- Pirbhulal, Sandeep (author)
- Univ Beira Interior, Portugal
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- Boukerche, Azzedine (author)
- Univ Ottawa, Canada; Prince Sultan Univ, Saudi Arabia
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(creator_code:org_t)
- IEEE : IEEE, 2020
- 2020
- English.
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In: IEEE Wireless Communication Magazine. - IEEE : IEEE. - 1536-1284 .- 1558-0687. ; 27:2, s. 14-21
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Abstract
Subject headings
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- Artificial intelligence (AI)-driven fog computing (FC) and its emerging role in vehicular networks is playing a remarkable role in revolutionizing daily human lives. Fog radio access networks are accommodating billions of Internet of Things devices for real-time interactive applications at high reliability. One of the critical challenges in today's vehicular networks is the lack of standard wireless channel models with better quality of service (QoS) for passengers while enjoying pleasurable travel (i.e., highly visualized videos, images, news, phone calls to friends/relatives). To remedy these issues, this article contributes significantly in four ways. First, we develop a novel AI-based reliable and interference-free mobility management algorithm (RIMMA) for fog computing intra-vehicular networks, because traffic monitoring and driver's safety management are important and basic foundations. The proposed RIMMA in association with FC significantly improves computation, communication, cooperation, and storage space. Furthermore, its self-adaptive, reliable, intelligent, and mobility-aware nature, and sporadic contents are monitored effectively in highly mobile vehicles. Second, we propose a reliable and delay-tolerant wireless channel model with better QoS for passengers. Third, we propose a novel reliable and efficient multi-layer fog driven inter-vehicular framework. Fourth, we optimize QoS in terms of mobility, reliability, and packet loss ratio. Also, the proposed RIMMA is compared to an existing competitive conventional method (i.e., baseline). Experimental results reveal that the proposed RIMMA outperforms the traditional technique for intercity vehicular networks.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Kommunikationssystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Communication Systems (hsv//eng)
Keyword
- Vehicular ad hoc networks
- Wireless communication
- Edge computing
- Quality of service
- Monitoring
- Channel models
- Packet loss
Publication and Content Type
- ref (subject category)
- art (subject category)
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