Congestion avoidance and control
SIGCOMM '88 Symposium proceedings on Communications architectures and protocols
Random early detection gateways for congestion avoidance
IEEE/ACM Transactions on Networking (TON)
Digital control system analysis and design (3rd ed.)
Digital control system analysis and design (3rd ed.)
Dynamics of random early detection
SIGCOMM '97 Proceedings of the ACM SIGCOMM '97 conference on Applications, technologies, architectures, and protocols for computer communication
Fluid-based analysis of a network of AQM routers supporting TCP flows with an application to RED
Proceedings of the conference on Applications, Technologies, Architectures, and Protocols for Computer Communication
Fuzzy Control
The BLUE active queue management algorithms
IEEE/ACM Transactions on Networking (TON)
A self-tuning structure for adaptation in TCP/AQM networks
SIGMETRICS '03 Proceedings of the 2003 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Design of a robust active queue management algorithm based on feedback compensation
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
A robust proportional controller for AQM based on optimized second-order system model
Computer Communications
Interface connecting the INET simulation framework with the real world
Proceedings of the 1st international conference on Simulation tools and techniques for communications, networks and systems & workshops
Design of a fuzzy controller for active queue management
Computer Communications
On credibility of simulation studies of telecommunication networks
IEEE Communications Magazine
IAPI: An intelligent adaptive PI active queue management scheme
Computer Communications
On the use of a full information feedback to stabilize RED
Journal of Network and Computer Applications
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Active queue management (AQM) is investigated to avoid incipient congestion in gateways to complement congestion control run by the transport layer protocol such as the TCP. Most existing work on AQM can be categorized as (1) ad-hoc event-driven control and (2) time-driven feedback control approaches based on control theory. Ad hoc event-driven approaches for congestion control, such as RED (random early detection), lack a mathematical model. Thus, it is hard to analyze their dynamics and tune the parameters. Time-driven control theoretic approaches based on solid mathematical models have drawbacks too. As they sample the queue length and run AQM algorithm at every fixed time interval, they may not be adaptive enough to an abrupt load surge. Further, they can be executed unnecessarily often under light loads due to the time-driven nature. To seamlessly integrate the advantages of both event-driven and control-theoretic time-driven approaches, we present an event-driven feedback control approach based on formal control theory. As our approach is based on a mathematical model, its performance is more analyzable and predictable than ad hoc event-driven approaches are. Also, it is more reactive to dynamic load changes due to its event-driven nature. Our simulation results show that our event-driven controller effectively maintains the queue length around the specified set-point. It achieves shorter E2E (end-to-end) delays and smaller E2E delay fluctuations than several existing AQM approaches, which are ad hoc event-driven and based on time-driven control theory, while achieving almost the same E2E delays and E2E delay fluctuations as the two other advanced control theoretic AQM approaches. Further, our AQM algorithm is invoked much less frequently than the tested baselines.