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Node Value and Content Popularity‐Based Caching Strategy for Massive VANETs
Author(s) -
Jinyuan Gu,
Yancheng Ji,
Wei Duan,
Guoan Zhang
Publication year - 2021
Publication title -
wireless communications and mobile computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.42
H-Index - 64
eISSN - 1530-8677
pISSN - 1530-8669
DOI - 10.1155/2021/5585896
Subject(s) - computer science , node (physics) , computer network , popularity , value (mathematics) , content (measure theory) , structural engineering , engineering , psychology , social psychology , mathematical analysis , mathematics , machine learning
The high-speed dynamic environment and massive information transmitted via wireless communications in the vehicular ad hoc networks (VANETs) pose a great challenge to privacy and security. To overcome this issue, use of the content-centric networking (CCN) provides a potential and practical solution. In-network caching is a main feature for future smart cities, in which the content is mainly placed in network nodes. Therefore, how to effectively select the cache locality and cache content is essential to improve the overall network performance, which is an inevitable trend. With these observations, this article proposes a caching strategy based on the node value and content popularity (NVCP) for the massive VANET scenario. In the proposed NVCP scheme, different from the traditional caching strategies, we evaluate the node value from three aspects: the connectivity, intermediary, and eigenvector centralities, synthetically, since the content with different types of popularity is placed in nodes with different values, resulting in the redundancy deterioration and diversity improvement for the content. The proposed caching strategy is evaluated by the stochastic network topology with multifactors, which provides different impacts on the system performance. Simulation results show that the NVCP outperforms the traditional cache strategies for 6G-CCN in terms of the cache hit ratio, average hop count, and transmission latency. Moreover, placing the content in the neighbor nodes is also introduced to further improve the utilization of the cache space and achieve better cache performance.

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