An ATSC 3.0-based scheduling and signaling system for hybrid broadcasting services

Yim, Hyun-Jeong; Oh, Hyeju; Kim, Soonchoul; Bae, Byungjun; Lim, Hyoungsoo

doi:10.1109/bmsb.2016.7521998

Cited by 5 publications

(2 citation statements)

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“…In particular, to provide broadcasting and communication convergence services, large-capacity and high-quality content needs to be transmitted based on internet protocol (IP) [5]. It is based on moving picture experts group (MPEG) media transport (MMT) or real-time object delivery over unidirectional transport (ROUTE) format to provide converged broadcasting services using the HTTP/TCP/IP protocol when transmitting the data through the network [6][7][8][9][10]. As mentioned above, the broadcasting gateway equipment is used to provide high-quality and large-capacity contents of 4K-UHD level or higher stably and seamlessly.…”

Section: Introductionmentioning

confidence: 99%

Machine-Learning Based Packet Switching Method for Providing Stable High-Quality Video Streaming in Multi-Stream Transmission

Jo,

Paik

2024

CMC

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Broadcasting gateway equipment generally uses a method of simply switching to a spare input stream when a failure occurs in a main input stream. However, when the transmission environment is unstable, problems such as reduction in the lifespan of equipment due to frequent switching and interruption, delay, and stoppage of services may occur. Therefore, applying a machine learning (ML) method, which is possible to automatically judge and classify network-related service anomaly, and switch multi-input signals without dropping or changing signals by predicting or quickly determining the time of error occurrence for smooth stream switching when there are problems such as transmission errors, is required. In this paper, we propose an intelligent packet switching method based on the ML method of classification, which is one of the supervised learning methods, that presents the risk level of abnormal multi-stream occurring in broadcasting gateway equipment based on data. Furthermore, we subdivide the risk levels obtained from classification techniques into probabilities and then derive vectorized representative values for each attribute value of the collected input data and continuously update them. The obtained reference vector value is used for switching judgment through the cosine similarity value between input data obtained when a dangerous situation occurs. In the broadcasting gateway equipment to which the proposed method is applied, it is possible to perform more stable and smarter switching than before by solving problems of reliability and broadcasting accidents of the equipment and can maintain stable video streaming as well.

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Section: Introductionmentioning

confidence: 99%

Machine-Learning Based Packet Switching Method for Providing Stable High-Quality Video Streaming in Multi-Stream Transmission

Jo,

Paik

2024

CMC

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“…ExistingresearchrelatedtotheMCNindustryremainsatthelevelofanalyzingtheindustry's currentstatuswithoutdealingwithitsmainissue.Manystudiesdescribethecurrentstatusofthe industryinthenewscreenecology (Kang,2015;Cunningham&Silver,2016;Kim,2016).Some haveexaminedthebusinessmodeloftheindustry (Gardner,2015;Song,2016;Koh&Youn,2016), butmostoftheseusedaliteraturereviewmethodandlimitedinterviews.Somerecentstudieshave examinedtherelationshipsofstakeholdersinMCNindustry.GardnerandLehnert(2016)focusedon therelationshipbetweenMCNcompaniesandcreators. Yim(2016)researchedthedifferencebetween legacymediaandMCNcompanies.LeeandSong(2016)studiedusers'acceptanceofcreatorcontent.…”

Section: Introductionmentioning

confidence: 99%

Exploring the Issues for the Success of Multichannel Network Businesses in Korea

Choi

Kim

2020

Journal of Global Information Management

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With the increasing popularity of online video content like YouTube carries, multichannel network (MCN) businesses have appeared. MCNs are organizations that partner with individual creators. They support production, promotion, copyright management, monetization, and share a portion of the revenue. The activation of the MCN industry is indispensable for the growth of a rich content environment. Despite the diverse stakeholder relationships that characterize the MCN industry (e.g., the MCN, creator, brand, advertising agency, platform, and users) most previous studies focused only on the perspectives of the creators and MCN participants. This study aims to identify each stakeholder's viewpoint. Using an interview-based systems approach, we interviewed 40 stakeholders in the MCN industry. After using a Causal Loop Diagram (CLD) to analyze the key factors and interactions among the diverse stakeholders, we suggest activation propositions. This study offers theoretical and practical implications through comprehensive understanding of six different perspectives within this industry.

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Time Information Transmission Based on FM Broadcast Signal

Xiang

2021

IEEE Access

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An ATSC 3.0-based scheduling and signaling system for hybrid broadcasting services

Cited by 5 publications

References 0 publications

Machine-Learning Based Packet Switching Method for Providing Stable High-Quality Video Streaming in Multi-Stream Transmission

Machine-Learning Based Packet Switching Method for Providing Stable High-Quality Video Streaming in Multi-Stream Transmission

Exploring the Issues for the Success of Multichannel Network Businesses in Korea

Time Information Transmission Based on FM Broadcast Signal

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