scholarly journals Congestion Control Using Multilevel Explicit Congestion Notification

2007 ◽  
Vol 3 (0) ◽  
pp. 42-54 ◽  
Author(s):  
Arjan Durresi ◽  
Leonard Barolli ◽  
Raj Jain ◽  
Makoto Takizawa
Keyword(s):  
Congestion Control ◽  
Explicit Congestion Notification

Harmonia: Explicit Congestion Notification and Credit-Reservation Transport Converged Congestion Control in Datacenters

2021 ◽  
Vol 36 (5) ◽  
pp. 1071-1086
Author(s):  
Ding-Huang Hu ◽  
De-Zun Dong ◽  
Yang Bai ◽  
Shan Huang ◽  
Ze-Jia Zhou ◽  
...  
Keyword(s):  
Congestion Control ◽  
Explicit Congestion Notification

scholarly journals ECN Congestion Control Mechanism in IP Networks

1970 ◽  
Vol 8 (1-2) ◽  
pp. 12-24
Author(s):  
Subarna Shakya ◽  
Anup Sainju
Keyword(s):  
Congestion Control ◽  
Size Variation ◽  
Window Size ◽  
Ip Networks ◽  
Network Simulator ◽  
Network Resource ◽  
Advantages And Disadvantages ◽  
Wide Range ◽  
Explicit Congestion Notification ◽  
Congestion Control Mechanism

Explicit Congestion Notification (ECN) is a newer method for congestion control in TCP IP networks. Network Simulator 2 (NS2) software has been used to compare the performance of ECN packet marking to other older and newer congestion control schemes, such as DropTail and Random Early Detection (RED), in both LAN and WAN schemes. During the simulations different parameters including proportion of packet drops, window size variation, queue size, and throughput were measured to evaluate the performance. The overall objective was to independently and comparatively study ECN in a wide range of situations to better understand its advantages and disadvantages. The results of these simulations showed that when all the network prerequisites were met (i.e. all the nodes including being ECN-aware), ECN reduced packet drops and thereby optimized network resource utilization and data throughput.Key Words : Explicit Congestion Notification; Network Simulator; Random Early Detect; DropTailDOI: http://dx.doi.org/10.3126/jie.v8i1-2.5093Journal of the Institute of Engineering Vol. 8, No. 1&2, 2010/2011Page : 12-24Uploaded Date: 19 July, 2011

scholarly journals Intelligent Active Queue Management Using Explicit Congestion Notification

2019 ◽  
Author(s):  
Cesar A. Gomez ◽  
Xianbin Wang ◽  
Abdallah Shami
Keyword(s):  
Congestion Control ◽  
Active Queue Management ◽  
Transport Layer ◽  
Machine Learning Techniques ◽  
Queue Management ◽  
Control Mechanisms ◽  
Network Layer ◽  
Explicit Congestion Notification ◽  
Buffer Control ◽  
The Right

As more end devices are getting connected, the Internet will become more congested. A variety of congestion control techniques have been developed either on transport or network layers. Active Queue Management (AQM) is a paradigm that aims at mitigating the congestion on the network layer by active buffer control to avoid overflow. However, finding the right parameters for an AQM scheme is challenging, due to the complexity and dynamics of the networks. On the other hand, the Explicit Congestion Notification (ECN) mechanism is a solution that makes visible incipient congestion on the network layer to the transport layer. In this work, we propose to exploit the ECN information to improve AQM algorithms by applying Machine Learning techniques. Our intelligent method uses an artificial neural network to predict congestion and an AQM parameter tuner based on reinforcement learning. The evaluation results show that our solution can enhance the performance of deployed AQM, using the existing TCP congestion control mechanisms.

An Efficient Congestion Control Scheme for Data Using Tokens in Network

2012 ◽  
Vol 2 (11) ◽  
pp. 104-106
Author(s):  
C.Md.Jamsheed C.Md.Jamsheed ◽  
◽  
D.Surendra D.Surendra ◽  
D.Venkatesh D.Venkatesh
Keyword(s):  
Congestion Control ◽  
Control Scheme

Routing Optimization with Efficient Second Order Distributed Approach Using Congestion Control Rules

2017 ◽  
Vol 7 (7) ◽  
pp. 363
Author(s):  
Jaya Pratha Sebastiyar ◽  
Martin Sahayaraj Joseph
Keyword(s):  
Congestion Control ◽  
Second Order ◽  
Back Pressure ◽  
Order Method ◽  
Delay Performance ◽  
Routing Optimization ◽  
Distributed Approach ◽  
Control Rules ◽  
Primal Dual ◽  
Queue Stability

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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