Collaborate algorithms for the multi-channel program download problem in VOD applications

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Abstract

Video-on-demand (VOD) is a multimedia technology that allows users to watch video programs from a server flexibly at any time. In recent years, VOD applications are very popular in many networks, especially in internet of vehicles where video programs can often be collaboratively downloaded from multiple channels simultaneously. In this paper, we first study the Multi-Channel Program Download Problem (McPDP), which is to download a set of interested programs from different channels within limited time. We prove that McPDP is NP-complete by reduction from 3-SAT(3). For another version with neatly placed programs of equal length, the aligned multi-channel program download problem (AMcPDP), we present an algorithm by transforming it into a max-flow problem. Finally, we have also analyzed the performance of these proposed algorithms by simulation using MATLAB.

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Zhang, W., Yang, L., Zhang, K., & Peng, C. (2017). Collaborate algorithms for the multi-channel program download problem in VOD applications. In Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST (Vol. 201, pp. 333–342). Springer Verlag. https://doi.org/10.1007/978-3-319-59288-6_30

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