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A Novel Distribution Service Policy for Crowdsourced Live Streaming in Cloud Platform | IEEE Journals & Magazine | IEEE Xplore

A Novel Distribution Service Policy for Crowdsourced Live Streaming in Cloud Platform


Abstract:

Dynamic requests of viewers from sparse and dispersed locations for crowdsourced-live-streaming (CSLS) service make current cloud service providers (CSPs) inadequate to p...Show More

Abstract:

Dynamic requests of viewers from sparse and dispersed locations for crowdsourced-live-streaming (CSLS) service make current cloud service providers (CSPs) inadequate to provide sufficient quality of experience (QoE). To solve this issue, we propose a multi-CDN-assisted-CSLS (MCACLS) architecture, a novel cloud architecture complemented by multiple content delivery networks (Multi-CDNs). MCACLS architecture can enhance a CSP's capacity of video distribution service and improve the quality of CSLS service for end-users while reducing the overall operational cost. MCACLS adaptively adjusts resources between a CSP and its leased CDN service in a fine granularity to deal with the volatility of user requests. However, scheduling resources cost-effectively in response to user requests from different regions is a critical issue that must be addressed. We formulate the above problem into a constrained stochastic optimization problem and propose an algorithm based on the Nash bargaining solution. Our proposed algorithm makes tradeoff between QoE of users and the overall operational cost for CSPs. Illustrative studies validate the advantages of MCACLS and show that it is more cost-effective, reducing the overall operational cost by up to 15% compared with other alternatives while achieving sufficient QoE for viewers.
Published in: IEEE Transactions on Network and Service Management ( Volume: 15, Issue: 2, June 2018)
Page(s): 679 - 692
Date of Publication: 01 February 2018

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I. Introduction

User-generated video services have become popular all around the world with the dominance of high-performance smart phones and high-speed mobile networks. Crowdsourced live streaming (CSLS) service emerged in recent years is this kind of service that allows an individual to be an online broadcaster. There are many well-known platforms providing this new type of user-generated video service, such as Twitch.tv, YouTube Live and Douyu.tv. Taking Twitch.tv as an example, the number of viewers in the platform has increased from 20 million to 45 million in just three years [1]. The prevalence of CSLS service has attracted a lot of attention from academia and industry.

https://www.twitch.tv/

http://www.youtube.com/

https://www.douyu.com/

Cites in Papers - |

Cites in Papers - IEEE (9)

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1.
Xingchi Liu, Mahsa Derakhshani, Lyudmila Mihaylova, Sangarapillai Lambotharan, "Risk-Aware Contextual Learning for Edge-Assisted Crowdsourced Live Streaming", IEEE Journal on Selected Areas in Communications, vol.41, no.3, pp.740-754, 2023.
2.
Lan Ding, Qinkai Wang, Ye Tian, "Exploiting Danmu Interactions for Optimizing Crowdsourced Livecast Services", 2022 7th International Conference on Big Data Analytics (ICBDA), pp.198-203, 2022.
3.
Jiannan Zheng, Haitao Zhang, Yilin Jin, Huadong Ma, "Collaborative Framework of Cloud Transcoding and Distribution Supporting Cost-Efficient Crowdsourced Live Streaming", 2021 IEEE 27th International Conference on Parallel and Distributed Systems (ICPADS), pp.931-938, 2021.
4.
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5.
Xingyan Chen, Changqiao Xu, Mu Wang, Zhonghui Wu, Shujie Yang, Lujie Zhong, Gabriel-Miro Muntean, "A Universal Transcoding and Transmission Method for Livecast with Networked Multi-Agent Reinforcement Learning", IEEE INFOCOM 2021 - IEEE Conference on Computer Communications, pp.1-10, 2021.
6.
Xingyan Chen, Changqiao Xu, Mu Wang, Zhonghui Wu, Lujie Zhong, Luigi Alfredo Grieco, "Augmented Queue-Based Transmission and Transcoding Optimization for Livecast Services Based on Cloud-Edge-Crowd Integration", IEEE Transactions on Circuits and Systems for Video Technology, vol.31, no.11, pp.4470-4484, 2021.
7.
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8.
Xingchi Liu, Mahsa Derakhshani, Sangarapillai Lambotharan, "Joint Transcoding Task Assignment and Association Control for Fog-Assisted Crowdsourced Live Streaming", IEEE Communications Letters, vol.23, no.11, pp.2036-2040, 2019.
9.
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Cites in Papers - Other Publishers (5)

1.
Jeong-Hoon Kim, Sun-Hyun Kim, Charn-Doh Bak, Seung-Jae Han, "Adaptive cloud resource allocation for large-scale crowdsourced multimedia live streaming services", Cluster Computing, 2023.
2.
Hongyi Li, Chunhai Cui, Shuai Jiang, "Strategy for improving the football teaching quality by AI and metaverse-empowered in mobile internet environment", Wireless Networks, 2022.
3.
Dr. M. Duraipandian, "Ranked k-NN Crowdsourced Model for Cloud Internet of Things (CIoT)", Journal of ISMAC, vol.2, no.3, pp.173, 2020.
4.
Rui-Xiao Zhang, Ming Ma, Tianchi Huang, Haitian Pang, Xin Yao, Chenglei Wu, Jiangchuan Liu, Lifeng Sun, "Livesmart", Proceedings of the 27th ACM International Conference on Multimedia, pp.420, 2019.
5.
Chongwu Dong, Wushao Wen, "Joint Optimization for Task Offloading in Edge Computing: An Evolutionary Game Approach", Sensors, vol.19, no.3, pp.740, 2019.
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References

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