QoS-adaptive proxy caching for multimedia streaming over the internet

2003 ◽  
Vol 13 (3) ◽  
pp. 257-269 ◽  
Author(s):  
Fang Yu ◽  
Qian Zhang ◽  
Wenwu Zhu ◽  
Ya-Qin Zhang
Author(s):  
Ping-Cheng Yeh ◽  
Hung-Yun Hsieh ◽  
Zhung-Han Wu ◽  
Yen-Chi Lee ◽  
Chun-Cheng Chiang ◽  
...  

Due to the time-varying nature of wireless channels and the Internet backbone traffic, it is a challenging task to maintain the quality of wireless multimedia streaming throughout the transmission. An effective solution is to adapt the codec setting based on the wireless channel condition or the Internet backbone state. In this chapter, we present three cross-layer codec adaptation algorithms that adjust the codec setting in real-time based on media access control frame error rate, received signal strength indication, and path bandwidth respectively. Results show that the algorithms are effective in achieving good video quality for wireless multimedia streaming over wireless links.


2004 ◽  
Vol 42 (8) ◽  
pp. 88-94 ◽  
Author(s):  
Jiangchuan Liu ◽  
Jianliang Xu

Author(s):  
Chetan Kumar ◽  
Sean Marston

Approximately 4 billion people have access to the Internet, additionally 23 billion devices are connected as of 2018. This has allowed for a substantial growth in data collection which has allowed for Big Data to flourish. The continued increase in user, devices, and Big Data usage has created a significant intensification in Internet traffic. This in turn has the potential to increase user delays when accessing data on the Internet. There are a number of ways to help reduce user latency, web caching is able to reduce web user delays in addition to reducing network traffic and the load on web servers. In this study we propose a proxy level web caching mechanism leveraging historical web patterns to help reduce user latency and accelerate the Internet. In addition we survey the state of the art of other caching approaches. Our investigation shows that using historical patterns as part of a proxy caching mechanisms in large scale networks can significantly shorten the latency for users in this era of Big Data


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