scholarly journals MMCSACC: A Multi-Source Multimedia Conference System Assisted by Cloud Computing for Smart Campus

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 35879-35889 ◽  
Author(s):  
Wei Zhang ◽  
Xinchang Zhang ◽  
Huiling Shi
Keyword(s):  
Cloud Computing ◽  
Smart Campus ◽  
Multimedia Conference System ◽  
Multimedia Conference ◽  
Conference System

A Deep Learning Solution for Multimedia Conference System Assisted by Cloud Computing

2018 ◽  
Vol 13 (3) ◽  
pp. 85-98
Author(s):  
Wei Zhang ◽  
Huiling Shi ◽  
Xinming Lu ◽  
Longquan Zhou
Keyword(s):  
Cloud Computing ◽  
Deep Learning ◽  
Data Distribution ◽  
Transmission Efficiency ◽  
Multimedia Data ◽  
Low Latency ◽  
Bandwidth Optimization ◽  
Multimedia Conference System ◽  
Multimedia Conference ◽  
Conference System

With the development of information technology, more and more people use multimedia conference system to communicate or work across regions. In this article, an ultra-reliable and low-latency solution based on Deep Learning and assisted by Cloud Computing for multimedia conference system, called UCCMCS, is designed and implemented. In UCCMCS, there are two-tiers in its data distribution structure which combines the advantages of cloud computing. And according to the requirements of ultra-reliability and low-latency, a bandwidth optimization model is proposed to improve the transmission efficiency of multimedia data so as to reduce the delay of the system. In order to improve the reliability of data distribution, the help of cloud computing node is used to carry out the retransmission of lost data. the experimental results show UCCMCS could improve the reliability and reduce the latency of the multimedia data distribution in multimedia conference system.

A Deep Learning Solution for Multimedia Conference System Assisted by Cloud Computing

2020 ◽  
pp. 372-385
Author(s):  
Wei Zhang ◽  
Huiling Shi ◽  
Xinming Lu ◽  
Longquan Zhou
Keyword(s):  
Cloud Computing ◽  
Deep Learning ◽  
Data Distribution ◽  
Transmission Efficiency ◽  
Multimedia Data ◽  
Low Latency ◽  
Computing Node ◽  
Multimedia Conference System ◽  
Multimedia Conference ◽  
Conference System

With the development of information technology, more and more people use multimedia conference system to communicate or work across regions. In this article, an ultra-reliable and low-latency solution based on Deep Learning and assisted by Cloud Computing for multimedia conference system, called UCCMCS, is designed and implemented. In UCCMCS, there are two-tiers in its data distribution structure which combines the advantages of cloud computing. And according to the requirements of ultra-reliability and low-latency, a bandwidth optimization model is proposed to improve the transmission efficiency of multimedia data so as to reduce the delay of the system. In order to improve the reliability of data distribution, the help of cloud computing node is used to carry out the retransmission of lost data. the experimental results show UCCMCS could improve the reliability and reduce the latency of the multimedia data distribution in multimedia conference system.

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