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Congestion control mechanisms are essential to stabilize the network system and provision quality of service. In this paper, we propose a robust congestion control scheme for time-delay and dynamic networks. First, a Smith predictor is used to compensate for time delay in the data transmission. Second, an active queue management controller is derived using internal model control theory for strong...
In this paper, we present a robust adaptive neural network control design approach for strict-feedback nonlinear systems with uncertainties. In the controller design process, all unknown terms at intermediate steps are passed down and approximated by a single neural network at the last step. By this way, the structure of the designed controller is much simpler, and the control law and the adaptive...
Most of the existing congestion control schemes cannot guarantee the quality of service in wide-area networks with large round trip time (RTT). Aiming at the above problem, a two-degree-of-freedom congestion control strategy (named TCC) is proposed for improving the stability and robustness of the TCP/AQM system. TCC employs a modified Smith predictor with two additional controllers to compensate...
Active queue management (AQM) mechanism plays an important role in network congestion control. In this paper, we propose an effective AQM algorithm, named adaptive real queue control (ARQC). In particular, an explicit congestion indicator, virtual regulating time, is designed to detect network congestion. Then by analyzing the queuing system on routers, we present the guideline to calculate the dropping/marking...
Numerous active queue management (AQM) schemes have been proposed to stabilize the queue length in routers, but most of them lack adequate adaptability to TCP dynamics, due to the nonlinear and time-varying nature of communication networks. To deal with the above problems, we propose an intelligent price-based congestion control algorithm named IPC. IPC measures congestion through using an intelligent...
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