A non-equilibrium analysis and control framework for active queue management

Alpcan, Tansu; Wang, Paul; Mehta, Prashant G.; Başar, Tamer

doi:10.1016/j.automatica.2008.02.008

Cited by 7 publications

(1 citation statement)

References 54 publications

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“…In comparison, PAQMAN employs an MDP-based approach and only requires the target delay as its input parameter. A closely related yet different approach has been discussed in the works [17], [18] where the authors first assume that the system dynamics is given by a deterministic fluid model for which they set out to perform a non-equilibrium analysis. To that end, they first identify a Markov chain that closely approximates the behaviour of the deterministic system, i.e., estimate the transition matrix of the chain for a given level of state-space discretization.…”

Section: Related Workmentioning

confidence: 99%

PAQMAN: A Principled Approach to Active Queue Management

Kar¹,

Alt²,

Koeppl³

et al. 2022

Preprint

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Active Queue Management (AQM) aims to prevent bufferbloat and serial drops in router and switch FIFO packet buffers that usually employ drop-tail queueing. AQM describes methods to send proactive feedback to TCP flow sources to regulate their rate using selective packet drops or markings. Traditionally, AQM policies relied on heuristics to approximately provide Quality of Service (QoS) such as a target delay for a given flow. These heuristics are usually based on simple network and TCP control models together with the monitored buffer filling. A primary drawback of these heuristics is that their way of accounting flow characteristics into the feedback mechanism and the corresponding effect on the state of congestion are not well understood. In this work, we show that taking a probabilistic model for the flow rates and the dequeueing pattern, a Semi-Markov Decision Process (SMDP) can be formulated to obtain an optimal packet dropping policy. This policy-based AQM, denoted PAQMAN, takes into account a steady-state model of TCP and a target delay for the flows. Additionally, we present an inference algorithm that builds on TCP congestion control in order to calibrate the model parameters governing underlying network conditions. Finally, we evaluate the performance of our approach using simulation compared to state-of-the-art AQM algorithms.

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Section: Related Workmentioning

confidence: 99%

PAQMAN: A Principled Approach to Active Queue Management

Kar¹,

Alt²,

Koeppl³

et al. 2022

Preprint

View full text Add to dashboard Cite

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Optimal control applications and methods literature survey (No. 10)

2009

Optim Control Appl Methods

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In order to keep readers up to date, the journal will contain a list of recently published journal articles relevant to the fields of optimal control, system optimization and applications six times a year. This list is compiled from a wide range of journals. Please note that even though the list has been broadly categorized these classifications are by no means strict, and are there to assist the reader. Please also note that inclusion in the list is not an endorsement of a paper's quality. If you have any suggestions or comments, please e-mail Leonardo Giovanini at lgiovanini@fich.unl.edu.ar.

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