Learning-based congestion control simulator for mobile internet education

2021 ◽  
Author(s):  
Junqin Huang ◽  
Linghe Kong ◽  
Jiejian Wu ◽  
Yutong Liu ◽  
Yuchen Li ◽  
...  
2012 ◽  
Vol 2 (11) ◽  
pp. 104-106
Author(s):  
C.Md.Jamsheed C.Md.Jamsheed ◽  
◽  
D.Surendra D.Surendra ◽  
D.Venkatesh D.Venkatesh

2019 ◽  
Vol 16 (7) ◽  
pp. 174-194 ◽  
Author(s):  
Weijin Jiang ◽  
Yang Wang ◽  
Yirong Jiang ◽  
Jiahui Chen ◽  
Yuhui Xu ◽  
...  

Author(s):  
Jaya Pratha Sebastiyar ◽  
Martin Sahayaraj Joseph

Distributed joint congestion control and routing optimization has received a significant amount of attention recently. To date, however, most of the existing schemes follow a key idea called the back-pressure algorithm. Despite having many salient features, the first-order sub gradient nature of the back-pressure based schemes results in slow convergence and poor delay performance. To overcome these limitations, the present study was made as first attempt at developing a second-order joint congestion control and routing optimization framework that offers utility-optimality, queue-stability, fast convergence, and low delay.  Contributions in this project are three-fold. The present study propose a new second-order joint congestion control and routing framework based on a primal-dual interior-point approach and established utility-optimality and queue-stability of the proposed second-order method. The results of present study showed that how to implement the proposed second-order method in a distributed fashion.


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