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Dynamic Optimization of Active Queue Management Routers to Improve Queue Stability
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 Title & Authors
Dynamic Optimization of Active Queue Management Routers to Improve Queue Stability
Radwan, Amr;
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This paper aims to introduce the numerical methods for solving the optimal control theory to model bufferbloat problem. Mathematical tools are useful to provide insight for system engineers and users to understand better about what we are facing right now while experiment in a large-scale testbed can encourage us to implement in realistic scenario. In this paper, we introduce a survey of the numerical methods for solving the optimal control problem. We propose the dynamic optimization sweeping algorithm for optimal control of the active queue management. Simulation results in network simulator ns2 demonstrate that our proposed algorithm can obtain the stability faster than the others while still maintain a short queue length (≈10 packets) and low delay experience for arriving packets (0.4 seconds).
AQM Router;Optimal Control;Pontryagin Minimum Principle;
 Cited by
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한국정보통신학회논문지, 2016. vol.20. 8, pp.1487-1493 crossref(new window)
Optimal Control Scheme for SEIR Model in Viral Communications, Journal of the Korea Institute of Information and Communication Engineering, 2016, 20, 8, 1487  crossref(new windwow)
S.H. Low, "A Duality Model of TCP and Queue Management Algorithms," IEEE/ACM Transactions on Networking, Vol. 11, No. 4, pp. 525-536, 2003. crossref(new window)

C.V. Hollot, V. Misra, D. Towsley, and W.-B. Gong, "A Control Theoretic Analysis of RED," Proceedings of IEEE INFOCOM 2001, Vol. 3, pp. 1510-1519, 2001.

M. Barbera, A. Lombardo, C. Panarello, and G. Schembra, "Queue Stability Analysis and Performance Evaluation of a TCP-Complaint Window Management Mechanism," IEEE/ACM Transactions on Networking, Vol. 18, No. 4, pp. 1275-1288, 2010. crossref(new window)

A. Radwan, Utilization of Parametric Programming and Evolutionary Computing in Optimal Control, Doctor's Thesis of Humboldt Universität, 2012.

J. T. Beets, Practical Methods for Optimal Control using Nonlinear Programming, Society for Industrial and Applied Mathematics (SIAM), Philadelphia, PA, 2001.

O. Von Stryk and R. Bulirsch, "Direct and Indirect Methods for Trajectory Optimization," Annals of Operations Research, Vol. 37, No. 1, pp. 357-373, 1992. crossref(new window)

H. To, T. Thi, and W. Hwang, "Cascade Probability Control to Mitigate Bufferbloat under Multiple Real-World TCP Stacks," Mathematical Problems in Engineering, Vol. 2015, 2015. crossref(new window)

M. Wall, GAlib: A C++ Library of Genetic Algorithm Components, Massachusetts Institute of Technology, ver.2.4, rev.B, 1996.

Y. Chen, Functional Optimization Models for Active Queue Management (2005). http: (accessed May, 26, 2015)

T. Issariyakul and E. Hossain. Introduction to Network Simulator NS2. Springer Publishing Company, Incorporated, New York, 2008.

N. Kuhn, P. Natarajan, N. Khademi, and D. Ros, AQM Characterization Guidelines, IETF Internet-Draft, 2015.

K. Shim, J. Yim, G. Lee, and J. Kim "A Web Service System Analysis Method Using Petri Net with Queue," Journal of Korea Multimedia Society, Vol. 14, No. 11, pp. 1409-1419, 2011. crossref(new window)