Crowdsourced Multi-View Live Video Streaming using Cloud Computing

Bilal, Kashif; Erbad, Aiman; Hefeeda, Mohamed

doi:10.1109/access.2017.2720189

Cited by 32 publications

(18 citation statements)

References 27 publications

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“…Offloading can be implemented on Cloud-based solutions, where appropriate resource allocation techniques can be used to increase user satisfaction [85] or deployment costs of the CDN networks [84]. Nonetheless, task offloading at the Edge can supplement the achieved performance.…”

Section: Video Streamingmentioning

confidence: 99%

Task offloading in Edge and Cloud Computing: A survey on mathematical, artificial intelligence and control theory solutions

et al. 2021

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Next generation communication networks are expected to accommodate a high number of new and resource-voracious applications that can be offered to a large range of end users. Even though end devices are becoming more powerful, the available local resources cannot cope with the requirements of these applications. This has created a new challenge called task offloading, where computation intensive tasks need to be offloaded to more resource powerful remote devices. Naturally, the Cloud Computing is a well-tested infrastructure that can facilitate the task offloading. However, Cloud Computing as a centralized and distant infrastructure creates significant communication delays that cannot satisfy the requirements of the emerging delay-sensitive applications. To this end, the concept of Edge Computing has been proposed, where the Cloud Computing capabilities are repositioned closer to the end devices at the edge of the network. This paper provides a detailed survey of how the Edge and/or Cloud can be combined together to facilitate the task offloading problem. Particular emphasis is given on the mathematical, artificial intelligence and control theory optimization approaches that can be used to satisfy the various objectives, constraints and dynamic conditions of this end-to-end application execution approach. The survey concludes with identifying open challenges and future directions of the problem at hand.

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Section: Video Streamingmentioning

confidence: 99%

Task offloading in Edge and Cloud Computing: A survey on mathematical, artificial intelligence and control theory solutions

et al. 2021

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“…A substantial number of these papers have their roots in the discipline of psychology, which has a long tradition of developing and using models to explain behavior [ 59 , 60 , 65 ]. The subdomains focused on the platform and the transmission are characterized by the use of more heterogeneous methods, although the former stands out for the inclusion of descriptive statistics and techniques for constructing graphs [ 87 , 88 , 89 , 90 , 91 , 92 ], and the latter for compiling information through application programming interfaces (APIs), both for Twitch [ 73 , 93 , 94 , 95 , 96 , 97 ] and other platforms such as Douyu [ 98 ]. The collection of information through public APIs is spreading to other subdomains (Streamer [ 99 ] Riot Games API; Receiver [ 100 ] Twitch API; and Platform [ 87 , 89 , 91 ] Twitch API), opening up future research opportunities if simultaneous information about the streamer, receiver, and platform can be connected.…”

Section: Resultsmentioning

confidence: 99%

“…There is a wide variety of topics addressed and a wealth of related applications being developed. Among the topics that have been covered, we found the development of functionalities to enhance communication [ 134 , 137 ], immersive user experiences through the implementation of multi-view systems [ 93 ], resource allocation to facilitate adaptive live streaming [ 141 ], and the application of the streamer’s biometric data to enhance the viewer’s experience [ 79 ]. Another significant group of papers in this cluster dealt with how to reduce bandwidth overheads and operating costs [ 16 , 131 , 133 , 138 ], broadcast times and latency [ 19 ], or metrics to optimize video quality [ 20 ].…”

Section: Resultsmentioning

confidence: 99%

“…A substantial number of these papers have their roots in the discipline of psychology, which has a long tradition of developing and using models to explain behavior [59,60,65]. The subdomains focused on the platform and the transmission are characterized by the use of more heterogeneous methods, although the former stands out for the inclusion of descriptive statistics and techniques for constructing graphs [87][88][89][90][91][92], and the latter for compiling information through application programming interfaces (APIs), both for Twitch [73,[93][94][95][96][97] and other platforms such as Douyu [98]. Regarding the discipline and the methodology, Table 2 presents for each of the identified research subdomains the main approaches applied and the research areas in which the WoS indexes these documents.…”

Section: The Domain Of Research On Video Game Live Streamingmentioning

confidence: 99%

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Exploring the Emerging Domain of Research on Video Game Live Streaming in Web of Science: State of the Art, Changes and Trends

Cabeza-Ramírez

García

Fernández

2021

IJERPH

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In recent years, interest in video game live streaming services has increased as a new communication instrument, social network, source of leisure, and entertainment platform for millions of users. The rise in this type of service has been accompanied by an increase in research on these platforms. As an emerging domain of research focused on this novel phenomenon takes shape, it is necessary to delve into its nature and antecedents. The main objective of this research is to provide a comprehensive reference that allows future analyses to be addressed with greater rigor and theoretical depth. In this work, we developed a meta-review of the literature supported by a bibliometric performance and network analysis (BPNA). We used the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) protocol to obtain a representative sample of 111 published documents since 2012 and indexed in the Web of Science. Additionally, we exposed the main research topics developed to date, which allowed us to detect future research challenges and trends. The findings revealed four specializations or subdomains: studies focused on the transmitter or streamer; the receiver or the audience; the channel or platform; and the transmission process. These four specializations add to the accumulated knowledge through the development of six core themes that emerge: motivations, behaviors, monetization of activities, quality of experience, use of social networks and media, and gender issues.

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“…The system called Cloud based View Crowdsourced Streaming (CMVCS) in which multiple contributors watching an event capture the event from different angles. [1] In this paper they propose a novel system to collect individual video streams (views) captured for the same event by multiple attendees, and combine them into multi-view videos, where viewers can watch the event from various angles, taking crowdsourced media streaming to a new immersive level. The system is called Cloud based Multi-View Crowdsourced Streaming (CMVCS), and it delivers multiple views of an event to viewers at the best possible video representation based on each viewer's available bandwidth.…”

Section: Scientific (Ijtsrd)mentioning

confidence: 99%

A Review on: Video Streaming using Cloud Computing Based on Android Application

Panhalkar¹,

Khandagale²

2018

IJTSRD

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In real life there is need to capture and share all special event. If there is multi attendee then the existing have some problem .The proposed system which collects individual video streams captured from same event and they combine into multi view videos. In this approach viewers can watch the one event from various angels; this is called as Cloud based Multi View Crowdsource Streaming (CMVCS). This approach focus on resource allocation of CMVCS system. Capture the video from one side and simultaneously access that video from anywhere. In this approach the system gives high bandwidth capability for decreasing the delay time.

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Crowdsourced Multi-View Live Video Streaming using Cloud Computing

Cited by 32 publications

References 27 publications

Task offloading in Edge and Cloud Computing: A survey on mathematical, artificial intelligence and control theory solutions

Task offloading in Edge and Cloud Computing: A survey on mathematical, artificial intelligence and control theory solutions

Exploring the Emerging Domain of Research on Video Game Live Streaming in Web of Science: State of the Art, Changes and Trends

A Review on: Video Streaming using Cloud Computing Based on Android Application

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