Abstract
The massive growth of mobile vehicles arises immense mobile traffic demand on the current cellular communication system. To cope with this challenge, a new transmission pattern that vehicle nodes cache some data contents in advance and provide data access for future requests via direct contacts has become an appealing solution for data offloading. However due to the limited resources, the fact that vehicle nodes might not be willing to assist data caching and transfer is plausible. Therefore in this paper, we build a reward-based caching-offloading framework, which efficiently offload cellular traffic by exploiting the storage capability and contact opportunity among vehicle nodes. The whole framework is divided into request phase and caching phase, an auction mechanism which comprises the bidding strategy, the response-for-bids strategy, and the prediction method is designed in the former phase and the optimal caching decision can be derived by solving a 0–1 knapsack problem in the latter phase. We conduct simulations on time-evolving topology traces, which validates the feasibility and efficiency of the proposed offloading paradigm.
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Acknowledgements
This work was supported by Department of Product & Infrastructure, China Telecommunication Technology Labs, China Academy of Information and Communications Technology.
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Bao, X. et al. (2019). Mobile Offloading in Vehicular Networks: A Reward-Based Incentive Caching Scheme. In: Milošević, D., Tang, Y., Zu, Q. (eds) Human Centered Computing. HCC 2019. Lecture Notes in Computer Science(), vol 11956. Springer, Cham. https://doi.org/10.1007/978-3-030-37429-7_2
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DOI: https://doi.org/10.1007/978-3-030-37429-7_2
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