Feedback control system with PWA load dependent reference buffer occupancy for congestion control in computer networks

• Autorzy: Grzyb S. , Orłowski P.

Identyfikatory

DOI

10.15199/48.2016.04.11

Warianty tytułu

PL

Sterowanie zatorami w sieciach komputerowych z wykorzystaniem pętli sprzężenia zwrotnego oraz wartości referencyjnej odcinkowo afinicznie zależnej od zajętości bufora

• Języki publikacji: EN

Abstrakty

EN

Congestion avoidance plays the significant role in increasing network reliability and efficiency. To minimize blockage effects, many methods and algorithms have been proposed. A method of active egress queue length control in use not to over on underutilize buffer occupancy in non-stationary, discrete, dynamical model of communication channel is described in this paper. This approach allows to optimize available network nodes resources to avoid congestions effects or to minimize or alleviate negative impact of these congestion on network throughput.

PL

W artykule zaproponowano metodę aktywnego sterowania długości kolejki wyjściowej, w celu zminimalizowania niepożądanych efektów zatorów sieciowych. Metoda ta pozwala unikać sytuacji nadmiernego przepełnienia lub opróżnienia bufora wyjściowego. Do badań został wykorzystany niestacjonarny, dyskretny, dynamiczny model kanału komunikacyjnego. Takie podejście umożliwia optymalizację dostępnych zasobów w węzłach sieciowych.

Słowa kluczowe

EN

congestion control; discrete-time system; dynamical model; computer network

PL

sieć komputerowa; sprzężenie zwrotne; kolejka sieciowa

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2016
• Tom: R. 92, nr 4
• Strony: 42--45
• Opis fizyczny: Bibliogr. 26 poz., rys., wykr.

Twórcy

autor

Grzyb S.

• West Pomeranian University of Technology, Szczecin, Poland

autor

Orłowski P.

• West Pomeranian University of Technology, Szczecin, Poland

Bibliografia

• [1] Hazra J., Sinha A.K., Congestion management using multiobjective particle swarm optimization, IEEE Trans. Power Syst., vol. 22 (2007), No.4, 1726–1734
• [2] Panigrahi, B.K., Pandi, V.R., Congestion management using adaptive bacterial foraging algorithm. Energy Conversion and Management, vol. 50 (2009), pp. 1202-1209
• [3] Ignaciuk P., Bartoszewicz A. , Discrete-time sliding-mode congestion control in multisource communication networks with time-varying delay, IEEE Trans. on Control Systems Technology 19, 2010
• [4] Danielson C., Borrelli F., Oliver D., Anderson D., Constrained flow control in storage networks: capacity maximization and balancing, Automatica, vol. 49 (2013), no. 9, pp. 2612-2621
• [5] Grzyb S., Orłowski P., Mechanisms of communication congestion and blockades in networks with time-varying parameters, Pomiary Automatyka Kontrola, vol. 59 (2013), no. 7, pp. 704-707
• [6] Sun, H., Wu, J., Ma, D., Long, J., Spatial distribution complexities of traffic congestion and bottlenecks in different network topologies, Applied Mathematical Modelling, vol. 38(2) (2014), pp. 496-505
• [7] Jiang, Nan, Network congestion avoidance through speculative reservation, High Performance Computer Architecture (HPCA), 2012 IEEE 18th International Symposium on. IEEE, 2012
• [8] Ignaciuk P., Bartoszewicz A., Linear quadratic optimal sliding mode controllers for a single virtual circuit in a connectionoriented communication network, Proceedings of the 13th IEEE/IFAC International Conference on Methods and Models in Automation and Robotics, Szczecin, Poland, pp. 121-128, 2007
• [9] Nyirenda C.N., Dawou D.S., Fuzzy logic congestion control in IEEE 802.11 wireless local area networks: A performance evaluation, Proceedings of the AFRICON, 2007
• [10] Guan X., Yang B., Zhao B., Adaptive fuzzy sliding mode active queue management algorithms, Telecommunication Systems, vol.35 (2007), no.1-2
• [11] Masoumzadeh S., Meshgi K., Shiry S., Taghizadeh G., FQLRED: an adaptive scalable schema for active queue management, International Journal of Network Management, vol. 21 (2011), no.:2, pp. 147-167
• [12] Nyirenda C.N., Dawoud D.S., Multi-objective particle swarm optimization for fuzzy logic based active queue management, IEEE International Conference on Fuzzy Systems, 2006, pp. 2231–2238
• [13] Grieder, P., Kvasnica M., Baotic M., Morari M., Low Complexity Control of Piecewise Affine Systems with Stability Guarantee, American Control Conference, Boston, USA, 2004
• [14] Lee Y. I., Kouvaritakis B., Cannon M., Constrained receding horizon predictive control for nonlinear systems, Automatica, vol. 38, no. 12 (2002), pp. 2093-2102
• [15] Besselmann, T.; Lofberg, J.; Morari, M., Explicit MPC for LPV Systems: Stability and Optimality, IEEE Transactions on Automatic Control, vol.57, no.9 (2012), pp.2322-2332
• [16] Orłowski P., Convergence of the Discrete-Time Nonlinear Model Predictive Control with Successive Time-Varying Linearization along Predicted Trajectories, Electronika ir Elektrotechnika, vol. 113, no. 7 (2011), pp. 27-31
• [17] Orłowski P., Generalized feedback stability for periodic linear time–varying discrete–time systems, Bulletin of the Polish Academy of Sciences: Technical Sciences – Polish Academy of Sciences, vol. 60 no. 1 (2012), pp. 171–178
• [18] Yoshida H., Kawata K., Fukuyama Y., Takayama S., Nakanishi Y., A particle swarm optimization for reactive power and voltage control considering voltage security assessment, IEEE Trans. Power Syst., vol. 15, no. 4 (200), pp. 1232–1239
• [19] Bemporad A., Oliveri A., Poggi T., Storace M., Ultra-fast stabilizing model predictive control via canonical piecewise affine approximations, IEEE Trans. Automatic Control, vol. 56, no. 12 (2011), pp. 2883-2897
• [20] Grzyb S., Orłowski P., Mathematical model of the congested communication channel in networks with time-varying parameters, Pomiary Automatyka Kontrola, vol. 59, no. 11 (2013), pp. 1151-1154
• [21] Orłowski P., Effect of the partitions of approximate secant piece-wise affine model on controI quality for non-lineer, statedependent system, Przegląd Elektrotechniczny, vol. 88. no. 10 (2012), pp. 69-73
• [22] Grzyb S., Orłowski P., The use of simplified frequency characteristics for analysis of communication channels with time-varying parameters, Pomiary Automatyka Kontrola, vol. 60, no. 5 (2014), pp. 317-320
• [23] Grzyb S., Orłowski P., Congestion control in computer networks - Application of piece-wise affine controller and particle swarm optimization, 19th International Conference on Methods and Models in Automation and Robotics (MMAR), pp. 834-838, Miedzyzdroje, Poland, September 2–5, 2014
• [24] Orłowski P., Complexity analysis of the piece-wise affine approximation for the car on the nonlinear hill model related to discrete–time, minimum time control problem, Electronika ir Elektrotechnika, vol 20, no 10 (2014), pp. 3-6
• [25] Coleman T.F., Li Y., An Interior, Trust Region Approach for Nonlinear Minimization Subject to Bounds, SIAM Journal on Optimization, Vol. 6 (1996), pp. 418-445
• [26] Coleman T.F., Li Y., On the Convergence of Reflective Newton Methods for Large-Scale Nonlinear Minimization Subject to Bounds, Mathematical Programming, Vol. 67, no. 2 (1994), pp. 189-224

Uwagi

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.