Journal
IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT
Volume 19, Issue 3, Pages 2780-2797Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNSM.2022.3161539
Keywords
SIoVs; data forwarding; interest tag; social relationship; fog computing
Categories
Funding
- National Natural Science Foundation of China [52177067, 62072078, 61902040]
- National Natural Science Key Foundation of China [U1966207]
- Hunan Provincial Education Department Scientific Research Project of China [20B024]
- Hunan Graduate Education Innovation and Professional Ability Improvement Project of China [CX20200881]
- National Research Fund Project of China [61872239]
- Hunan Provincial Natural Science Foundation of China [2019JJ40314, 2018JJ2445]
- Guangdong Key Lab of AI and Multi-modal Data Processing
- BNU-UIC Institute of Artificial Intelligence and Future Networks
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This paper proposes a dual-mode data forwarding scheme based on interest tags for fog computing-based SIoVs, aiming to address the issues of data forwarding optimization and adaptability in dynamic networks. The experimental results show that the proposed scheme is more efficient and stable than other related schemes.
Social Internet of vehicles (SIoVs) is a combination of vehicular ad-hoc networks (VANETs) and mobile social networks (MSNs). Although social relationships between vehicle nodes are more stable than location changes of vehicle nodes in SIoVs, there always are the problems of data forwarding optimization and adaptability for dynamic networks. In this paper, we propose a dual-mode data forwarding scheme based on interest tags for fog computing-based SIoVs. In the first data forwarding mode, the vehicle nodes calculate and use the cooperation degrees to select the next cooperative forwarding nodes until the data is forwarded to the destination node. In the second data forwarding mode, the RSUs assist the data forwarding of vehicle nodes based on the RSU ranking mechanism of interests, where the fog servers calculate the RSU ranking table of all the interests and the related RSU selects the top-k RSUs to forward the data according to the RSU ranking table. The experimental results show that our proposed scheme is more efficient and stable than other related schemes by the comparisons of delivery ratio, overhead ratio and average hop count.
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