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Resource Sharing and Segment Allocation Optimized Video Streaming over Multi-hop Multi-path in Dense D2D 5G Networks

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Abstract

The rapid increase in mobile users (MUs) and various video applications and services (VASs) poses a set of challenges to 5G networks. Although device-to-device (D2D) communications and resource reuse techniques can improve the streaming performance of VASs, they have not utilized the fact that there are many MUs with available sharing downlink resources, namely cellular users (CUs), and many videos cached in dense MUs to establish an efficient video streaming session. In this paper, we propose a downlink resource sharing and segment allocation (RSA) optimization problem and solve it for high video streaming performance over multi-hop multi-path (MHMP) in dense D2D 5G networks. Particularly, the RSA provides a maximum capacity for the CUs that share their downlink resources with the D2D hops in each path by finding the optimal downlink resource sharing-receiving pairs between the CUs and the D2D hops. Then, the segments of a video cached in different D2D helpers (DHs) are sent to the D2D requester (DR) over the MHMP. By finding which segments are allocated to which paths for sending, the reconstructed distortion of the received segments at the DR is minimized for high playback quality. Simulation results are shown to investigate the benefits of the proposed solution compared to other schemes without RSA.

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Acknowledgement

This research is funded by Vietnam National Foundation for Science and Technology Development (NAFOSTED) under grant number 102.04-2018.308.

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Correspondence to Nguyen-Son Vo .

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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Tran, QN., Vo, NS., Bui, MP., Phan, VC., Kaleem, Z., Duong, T.Q. (2019). Resource Sharing and Segment Allocation Optimized Video Streaming over Multi-hop Multi-path in Dense D2D 5G Networks. In: Duong, T., Vo, NS., Nguyen, L., Vien, QT., Nguyen, VD. (eds) Industrial Networks and Intelligent Systems. INISCOM 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 293. Springer, Cham. https://doi.org/10.1007/978-3-030-30149-1_3

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  • DOI: https://doi.org/10.1007/978-3-030-30149-1_3

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