A binary feedback scheme for congestion avoidance in computer networks
ACM Transactions on Computer Systems (TOCS)
Intelligent congestion control for ABR service in ATM networks
ACM SIGCOMM Computer Communication Review
A predictive congestion control policy for broadband integrated wide area networks
Computer Networks and ISDN Systems
Congestion control and traffic management in ATM networks: recent advances and a survey
Computer Networks and ISDN Systems
Performance of TCP over ATM with time-varying available bandwidth
Computer Communications
The available bit rate service for data in ATM networks
IEEE Communications Magazine
Trellis-coded modulation with redundant signal sets Part II: State of the art
IEEE Communications Magazine
Rate regulation with feedback controller in ATM networks-a neural network approach
IEEE Journal on Selected Areas in Communications
Effective control of traffic flow in ATM networks using fuzzy explicit rate marking (FERM)
IEEE Journal on Selected Areas in Communications
The rate-based flow control framework for the available bit rate ATM service
IEEE Network: The Magazine of Global Internetworking
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We propose a predictive mechanism for managing the ABR traffic in ATM networks. For ABR traffic management, the establishment of a feedback loop between the source/destination end systems, and the network lets the data sources know the state of the network, and utilize the available network bandwidth more efficiently. However, because of the propagation delay of sending back the resource management cells to the data sources, the network is either underutilized (when the network load is light), or congested (when the network load is heavy) by the excessive cells that enter the network during the propagation period. The proposed predictive mechanism based on the Trellis diagram predicts the contents of the resource management cells and makes rate adjustments beforehand. We also show how the predictive mechanism can be used as an ''add-on'' to the current congestion control algorithms such as EFCI, PRCA and EPRCA. A performance evaluation demonstrates that the predictive approach reduces excessive cells and increases network utilization.