A Distributed Real-Time Transcoding CDN System Design and Performance Simulation Study.

Yuan Ren, Cheng Huang, Yongbo Lv, Wanjun Lv, Han Zhang

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Yuan RenSchool of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China.

Cheng HuangSchool of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China.

Yongbo LvSchool of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China.

Wanjun LvSchool of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China.ORCID 0000-0002-9272-9215

Han ZhangSchool of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China.ORCID 0000-0003-2497-2245

Funding

This paper was substantially supported by National Natural Science Foundation of China [Project Nos. 61872036].

6 · The paper itself

Abstract

Content Delivery Network (CDN) technology is one of the core technologies for performance optimization of mobile WEB applications, but it often encounters bottlenecks in video storage. In this paper, based on studying the basic technical model of distributed real-time transcoding CDN, we propose an overall technical architecture of a distributed real-time transcoding CDN system, present the business process of distributed real-time transcoding CDN resource negotiation in the model, design a resource storage policy model and algorithm, including the hot storage ratio resource storage value evaluation method and storage resource allocation algorithm. Through simulation experiments, we verify the technical efficiency of the distributed real-time transcoding CDN system by simulation experiments.

Indexed as

CDN systemsdistributed real-time transcodingresource negotiationresource storage policies

Identifiers

PMID35271092

DOI10.3390/s22051945

PMCPMC8915081

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.