Abstract
The explosive growth of smart devices has led to the evolution of multimedia data (mainly video) services in mobile networks. It attracted many mobile network operators (MNO) to deploy novel network architectures and develop effective economic policies. Mobile data offloading through smart devices (SDs) by exploring device-to-device (D2D) communications can significantly reduce network congestion and enhance quality of service at a lower cost, which is the key requirement of upcoming 5G networks. This reasonable cost solution is useful for attracting mobile users to participate in the offloading process by paying them proper incentives. It is beneficial for MNOs as well as mobile users. Moreover, D2D communications promise to be one of the prominent services for 5G networks. In this paper, we present a combinatorial optimal reverse auction (CORA) mechanism, which efficiently selects and utilizes available high-end SDs on the basis of available resources for offloading purposes. It also decides the optimal pricing policy for the selected SDs. The efficiency of CORA has been realized in terms of bandwidth and storage demand. Subsequently, we implement caching in SDs, eNodeB (eNB), and evolved packet core (EPC) with the help of our novel video dissemination cache update algorithm to solve the latency or delay issues in the offloading process. Due to high popularity, we specifically focus on video data. Simulation results show that the proposed SD caching scenario curtails the delay up to 75% and the combined cache (CC) scenario slashes the delay varying from 15 to 57%. We also scruitinize the video downloading time performance of various cache scenarios (i.e., CC, EPC cache, eNB cache, and SD cache scenarios).
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This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2016R1D1A1B03935633).
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Umrao, S., Roy, A., Saxena, N. et al. Mobile Network Operator and Mobile User Cooperation for Customized D2D Data Services. J Netw Syst Manage 26, 878–903 (2018). https://doi.org/10.1007/s10922-018-9447-2
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DOI: https://doi.org/10.1007/s10922-018-9447-2