scholarly journals Blockchain-Enabled Intelligent Video Caching and Transcoding in Clustered MEC Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Yan Li ◽  
Zheng Wan
Keyword(s):  
Video Transmission ◽  
Video On Demand ◽  
Video Data ◽  
Transmission Model ◽  
Smart Devices ◽  
Video Content ◽  
Video Caching ◽  
Transaction Process ◽  
Streaming Service ◽  
Transcoding Service

In recent years, the number of smart devices has exploded, leading to an unprecedented increase in demand for video live and video-on-demand (VoD) services. Also, the privacy of video providers and requesters and the security of requested video data are much more threatened. In order to solve these issues, in this paper, a blockchain-enabled CMEC video transmission model (Bl-CMEC) for intelligent video caching and transcoding will be proposed to ensure the transactions’ transparency, system security, user information privacy, and integrity of the video data, enhance the ability of severs in actively caching popular video content in the CMEC system, and realize transcoding function at network edge nodes. Furthermore, we chose a scheme based on deep reinforcement learning (DRL) to intelligently access the intracluster joint caching and transcoding decisions. Then, the joint video caching and transcoding decision smart contract is specially designed to automatically manage the transaction process of the joint caching and transcoding service, which records key information of joint caching and transcoding transactions and payment information on a continuous blockchain. The simulation results demonstrate that the proposed Bl-CMEC framework not only can provide users with better QoE performance for video streaming service but also can ensure the security, integrity, and consistency for the video providers, video requesters, and video data.

Video Content-Based Retrieval Techniques

2011 ◽  
pp. 114-155
Author(s):  
Waleed E. Farag ◽  
Hussein Abdel-Wahab
Keyword(s):  
Digital Libraries ◽  
Video On Demand ◽  
Video Data ◽  
Video Content ◽  
Content Based Retrieval ◽  
Java Language ◽  
Multimedia Streams ◽  
Video Shot ◽  
Shot Boundary ◽  
Shed Light

The increasing use of multimedia streams nowadays necessitates the development of efficient and effective methodologies and systems for manipulating databases storing these streams. These systems have various areas of application such as video-on-demand and digital libraries. The importance of video content-based retrieval (CBR) systems motivates us to explain their basic components in this chapter and shed light on their underlying working principles. In general, a content-based retrieval system of video data consists of the following four stages: (1) Video Shot Boundary Detection, (2) Key Frames (KFs) selection, (3) features extraction (from selected KFs), and (4) retrieval stage (where similarity matching operations are performed). Each one of the above stages will be reviewed and expounded based on our experience in building a Video Content-based Retrieval (VCR) system that has been fully implemented from scratch in JAVA Language (2002). Moreover, current research directions and outstanding problems will be discussed for each stage in the context of our VCR system.

Amazons Kampf um das Wohnzimmer

2016 ◽  
Vol 13 (3) ◽  
pp. 37-39
Author(s):  
Ralf Kaumanns
Keyword(s):  
Streaming Media ◽  
Video On Demand ◽  
Video Content ◽  
On Demand

Der Kampf um das Wohnzimmer ist voll entbrannt. Eine Reihe von Anbietern versuchen Streaming Media-Dienste im deutschen Markt zu etablieren. Amazon hat sich mit seiner Strategie eine marktführende Rolle erarbeiten können. Laut einer Analyse von Goldmedia¹ besitzt Amazon mittlerweile einen Anteil im Video-On-Demand-Markt von 38,9%, deutlich vor Wettbewerbern wie Apple, Maxdome, Google oder Netflix. Der Erfolg kommt nicht von ungefähr. Der Grund liegt vor allem in einer umfassenden Strategie rund um das Thema Bewegtbild und Video Content. Im Kampf um das Wohnzimmer haben selbst große und finanzkräftige Wettbewerber einen schweren Stand, um mit umfassend gebündelten Angeboten Schritt zu halten.

Detecting “DeepFakes” in H.264 Video Data Using Compression Ghost Artifacts

2020 ◽  
Vol 2020 (4) ◽  
pp. 116-1-116-7
Author(s):  
Raphael Antonius Frick ◽  
Sascha Zmudzinski ◽  
Martin Steinebach
Keyword(s):  
Image Forensics ◽  
Video Data ◽  
Experimental Results ◽  
Video Sequences ◽  
The Internet ◽  
Video Content ◽  
High Quality ◽  
The Public

In recent years, the number of forged videos circulating on the Internet has immensely increased. Software and services to create such forgeries have become more and more accessible to the public. In this regard, the risk of malicious use of forged videos has risen. This work proposes an approach based on the Ghost effect knwon from image forensics for detecting forgeries in videos that can replace faces in video sequences or change the mimic of a face. The experimental results show that the proposed approach is able to identify forgery in high-quality encoded video content.

scholarly journals Factors Affecting the Popularity of Video Content on Live-Streaming Services: Focusing on V Live, the South Korean Live-Streaming Service

2020 ◽  
Vol 12 (5) ◽  
pp. 1784 ◽  
Author(s):  
Minjeong Ham ◽  
Sang Woo Lee
Keyword(s):  
Live Streaming ◽  
Cumulative Number ◽  
Video Content ◽  
Factors Affecting ◽  
South Korean ◽  
Key Characteristics ◽  
Quality Video ◽  
Streaming Service ◽  
High Quality Video ◽  
Production Company

Naver V Live, a South Korean live-streaming service, showcases video contents specific to the entertainment industry, such as K-pop and music. On V Live, K-pop stars and their fans can interact directly in a natural way, and V Live provides high-quality video content with novel topics. This study has identified key characteristics of video content that affect its popularity. A total of 620 video contents of five leading Star channels were classified on the basis of production company, type of video content, and whether it was live-streamed or not. The popularity of video content was measured by the number of comments, hearts, and views. To control potential bias, additional variables were set as control variables—such as the number of channel subscribers, mini-album sales, if the video content was previewed, and cumulative number of days since the video content was uploaded. For analysis, a hierarchical linear regression was conducted. The findings suggest future directions in video content planning.

scholarly journals Redundant VoD Streaming Service in a Private Cloud: Availability Modeling and Sensitivity Analysis

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Rosangela Maria De Melo ◽  
Maria Clara Bezerra ◽  
Jamilson Dantas ◽  
Rubens Matos ◽  
Ivanildo José De Melo Filho ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Cloud Computing ◽  
Hierarchical Modeling ◽  
Video On Demand ◽  
Differential Sensitivity ◽  
Private Cloud ◽  
Streaming Service ◽  
Critical Components ◽  
Modeling Strategy ◽  
Vod Streaming

For several years cloud computing has been generating considerable debate and interest within IT corporations. Since cloud computing environments provide storage and processing systems that are adaptable, efficient, and straightforward, thereby enabling rapid infrastructure modifications to be made according to constantly varying workloads, organizations of every size and type are migrating to web-based cloud supported solutions. Due to the advantages of the pay-per-use model and scalability factors, current video on demand (VoD) streaming services rely heavily on cloud infrastructures to offer a large variety of multimedia content. Recent well documented failure events in commercial VoD services have demonstrated the fundamental importance of maintaining high availability in cloud computing infrastructures, and hierarchical modeling has proved to be a useful tool for evaluating the availability of complex systems and services. This paper presents an availability model for a video streaming service deployed in a private cloud environment which includes redundancy mechanisms in the infrastructure. Differential sensitivity analysis was applied to identify and rank the critical components of the system with respect to service availability. The results demonstrate that such a modeling strategy combined with differential sensitivity analysis can be an attractive methodology for identifying which components should be supported with redundancy in order to consciously increase system dependability.

Efficient Ontology Integration Model for Better Inference in Context Aware Computing

2011 ◽  
Vol 268-270 ◽  
pp. 841-846
Author(s):  
Soo Mi Yang
Keyword(s):  
Video Data ◽  
Smart Devices ◽  
Collaborative Network ◽  
Context Aware ◽  
Integration Model ◽  
Smart Cameras ◽  
Ontology Integration ◽  
Context Aware Computing ◽  
Heterogeneous Devices ◽  
Distributed Ontology

In this paper, we describe efficient ontology integration model for better context inference based on distributed ontology framework. Context aware computing with inference based on ontology is widely used in distributed surveillance environment. In such a distributed surveillance environment, surveillance devices such as smart cameras may carry heterogeneous video data with different transmission ranges, latency, and formats. However even smart devices, they generally have small memory and power which can manage only part of ontology data. In our efficient ontology integration model, each of agents built in such devices get services not only from a region server, but also peer servers. For such a collaborative network, an effective cache framework that can handle heterogeneous devices is required for the efficient ontology integration. In this paper, we propose a efficient ontology integration model which is adaptive to the actual device demands and that of its neighbors. Our scheme shows the efficiency of model resulted in better context inference.

Netflix, Amazon, and branded television content in subscription video on-demand portals

2017 ◽  
Vol 40 (5) ◽  
pp. 725-741 ◽  
Author(s):  
Michael L Wayne
Keyword(s):  
Brand Equity ◽  
Video On Demand ◽  
Press Coverage ◽  
Recent Past ◽  
Industrial Practice ◽  
On Demand ◽  
Television Network ◽  
Television Content ◽  
The Us ◽  
Streaming Service

Branding has been described as the defining industrial practice of television’s recent past. This article examines publicly available industry documents, trade press coverage, and executive interviews to understand the place of traditional television network branding in subscription video on-demand (SVOD) portals as represented by Amazon and Netflix. Focusing on materials relating to licensed rather than original content and this content’s role within the US domestic SVOD market, two distinct approaches emerge. For Amazon, the brand identities of some television networks act as valuable lures drawing customers into its Prime membership program. For Netflix, linear television networks are competitors whose brand identities reduce Netflix’s own brand equity. Ultimately, Amazon’s efforts to build a streaming service alongside network brand identities and Netflix’s efforts to build its own brand at the expense of such identities demonstrate the need to think about contemporary television branding as an ongoing negotiation between established and emerging practices.

A Chunkless Peer-to-Peer Transport Protocol for Multimedia Streaming

2011 ◽  
pp. 337-360
Author(s):  
Roberto Cesco ◽  
Riccardo Bernardini ◽  
Roberto Rinaldo
Keyword(s):  
Video Transmission ◽  
Peer To Peer ◽  
Point Of View ◽  
Multimedia Streaming ◽  
Transport Protocol ◽  
Video Content ◽  
Research Communities ◽  
Start Up ◽  
The Media ◽  
Media Stream

Video transmission over IP is currently a hot topic both in entertainment and research communities. A problem that threatens the development of video over IP services is the bandwidth required to serve a potentially very large number of users. In this context, Peer-to-peer (P2P) technologies are considered a possible solution for the distribution of video content to many users. This chapter describes a novel P2P transport protocol suited for live multimedia streaming. The described protocol has low start-up time, it is robust with respect to data losses (due to congestion or node departure) and it can help counteracting the malicious injection of “bogus packets” in the media stream. The proposed protocol can be used with any type of data and, from the application point of view, it appears as a protocol similar to TCP or UDP, making the reuse of existing software and protocols easier.

Temporal-Based Video Event Detection and Retrieval

2012 ◽  
Vol 3 (4) ◽  
pp. 39-51
Author(s):  
Min Chen
Keyword(s):  
Event Detection ◽  
Video Retrieval ◽  
Class Imbalance ◽  
Video Data ◽  
Temporal Information ◽  
Temporal Association ◽  
Association Mining ◽  
Video Content ◽  
Video Content Analysis ◽  
High Level

The fast proliferation of video data archives has increased the need for automatic video content analysis and semantic video retrieval. Since temporal information is critical in conveying video content, in this chapter, an effective temporal-based event detection framework is proposed to support high-level video indexing and retrieval. The core is a temporal association mining process that systematically captures characteristic temporal patterns to help identify and define interesting events. This framework effectively tackles the challenges caused by loose video structure and class imbalance issues. One of the unique characteristics of this framework is that it offers strong generality and extensibility with the capability of exploring representative event patterns with little human interference. The temporal information and event detection results can then be input into our proposed distributed video retrieval system to support the high-level semantic querying, selective video browsing and event-based video retrieval.

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