Abstract
In this paper, buffer dynamic modeling for wireless sensor networks as a highly nonlinear system is accomplished in discrete time, different subsystems are achieved based on delay, and the overall model is gained by blending them. According to nonlinear dynamics point of view, considering delay in the analysis of congestion control schemes is of paramount importance. In this paper, an adaptive back-off interval selection works with the proposed robust controller. Based on queue utilization and channel estimation algorithm, congestion is detected and a suitable rate is selected by adaptive back-off interval selection. An augmented form of our proposed system is utilized for controller synthesis. A new approach is proposed for controller synthesis based on non-quadratic and common quadratic Lyapunov candidates where the former is generalized to be more relaxed. Also, the monotonicity requirement of Lyapunov’s theorem is relaxed. The closed-loop systems are globally asymptotically stable in case of delay changes resulted from queue size changes. Extended simulation results confirm the effectiveness of our proposed schemes.
Similar content being viewed by others
References
M. Akar, U. Ozguner, Decentralized techniques for the analysis and control of Takagi-Sugeno fuzzy systems. IEEE Trans Fuzzy Syst 8, 691–704 (2000)
P. Antoniou, A. Pitsillides, T. Blackwell, A. Engelbrecht, L. Michael, Congestion control in wireless sensor networks based on bird flocking behavior. Comput Netw 57, 1167–1191 (2013)
S. Boyd, L.E. Ghaoui, E. Feron, V. Balakrishnan, Linear matrix inequalities in system and control theory, 15 (SIAM, Philadelphia, 1994)
Chand T, Sharma B, Kour M (2015) TRCCTP: a traffic redirection-based congestion control transport protocol for wireless sensor networks. In: IEEE sensors 1–4
Y. Chen, Z. Wang, Y. Yuan, P. Date, Distributed H∞ filtering for switched stochastic delayed systems over sensor networks with fading measurements. IEEE Trans Cybern 99, 1–13 (2018)
Dubey K, Sinha A (2015) Congestion control for self-similar traffic in wireless sensor network. In: Eighth international conference on contemporary computing (IC3), pp 331–335
S. Fakhimi Derakhshan, A. Fathehi, Non monotonic Lyapunov functions for stability analysis and stabilization of discrete time Takagi-Sugeno fuzzy systems. Int J Innov Comput Inf Control 10, 1567–1586 (2014)
S.S.S. Farahani, M.R. Jahed-Motlagh, M.A. Nekoui, Novel congestion control algorithms for a class of delayed networks. Turk J Electr Eng Comput Sci 23, 824–840 (2015)
S.S.S. Farahani, M.R. Jahed-Motlagh, M.A. Nekoui, S.V. Azhari, Robust decentralized adaptive nonquadratic congestion control algorithm for a class of delayed networks. Nonlinear Dyn 73, 2291–2311 (2013)
G. Feng, C.L. Chen, D. Sun, X.P. Guan, H-infinity controller synthesis of fuzzy dynamic systems based on piecewise Lyapunov functions and bilinear matrix inequalities. IEEE Trans Fuzzy Syst 13, 94–103 (2005)
Y. Gao, F. Xiao, J. Liu, R. Wang, Distributed soft fault detection for interval type-2 fuzzy-model-based stochastic systems with wireless sensor networks. IEEE Trans Ind Inf 15, 334–347 (2019)
S.H. Ghwanmeh, A.R. Al-Zoubidi, Wireless network performance optimization using opnet modeler. Inf Technol J 5, 18–24 (2006)
Justus JJ, Chandra Sekar A (2016) Congestion control in wireless sensor network using hybrid epidermic and DAIPaS approach. In: 2016 international conference on inventive computation technologies (ICICT)
M.A. Kafi, J. Ben-Othman, A. Ouadjaout, M. Bagaa, N. Badache, REFIACC: reliable, efficient, fair and interference-aware congestion control protocol for wireless sensor networks. Comput Commun 101, 1–11 (2017)
C. Lee, T. Jeong, S. Lian, Tournament-based congestion control protocol for multimedia streaming in ubiquitous sensor networks. Int J Commun Syst 24, 1246–1260 (2011)
C. Liang, F. Wen, Z. Wang, Distributed parameter estimation for univariate generalized Gaussian distribution over sensor networks. Circuits Syst Signal Process 36, 1311–1321 (2017)
W. Lu, Y. Liu, D. Wang, A distributed secure data collection scheme via chaotic compressed sensing in wireless sensor networks. Circuits Syst Signal Process 32, 1363–1387 (2013)
S. Mahdizadeh Aghdam, M. Khansari, H.R. Rabiee, M. Salehi, WCCP: a congestion control protocol for wireless multimedia communication in sensor networks. Ad Hoc Netw 13, 516–534 (2014)
S. Misra, V. Tiwari, M.S. Obaidat, LACAS: learning automata based congestion avoidance scheme for healthcare wireless sensor networks. IEEE J Sel Areas Commun 27, 466–479 (2009)
Mozelli LA, Palhares RM (2011) Less conservative H∞ fuzzy control for discrete-time Takagi-Sugeno systems. Hindawi Publ Corp Math Prob Eng
M. Padmakar Shelke, A. Malhotra, P. Mahalle, A packet priority intimation-based data transmission for congestion free traffic management in wireless sensor networks. Comput Electr Eng 64, 248–261 (2017)
A.A. Rezaee, M.H. Yaghmaee, A.M. Rahmani, A.H. Mohajerzadeh, HOCA: healthcare aware optimized congestion avoidance and control protocol for wireless sensor networks. J Netw Comput Appl 37, 216–228 (2014)
Z.M. Saric, D.D. Kukolj, N.D. Teslic, Acoustic source localization in wireless sensor network. Circuits Syst Signal Process 29, 837–856 (2010)
Singh SB, Dave M, Manshahia MS (2015) Bio inspired congestion control mechanism for wireless sensor networks. In: IEEE international conference on computational intelligence and computing research (ICCIC), 1–6
M. Sudip, W. Isaac, M. Subhas Chandra, Guide to wireless sensor networks, Computer Communication and Network Series (Springer, London, 2009)
Wan CY, Eisenman SB, Campbell AT (2003) CODA: congestion detection and avoidance in sensor networks. In: Proceedings of the 1st international conference on Embedded networked sensor systems SenSys ‘03, pp 266–279
Wang Y, Qi SZ, Chun Sun F (2004) Stability analysis and control of discrete-time fuzzy systems: a fuzzy Lyapunov function approach. In: 5th Asian control conference, pp 1855–1860
C. Wenguang, N. Yugang, Z. Yuanyuan, Congestion control and energy-balanced scheme based on the hierarchy for WSNs. IET Wirel Sens Syst 7(1), 1–8 (2017)
M.H. Yaghmaee, D. Adjeroh, Priority-based rate control for service differentiation and congestion control in wireless multimedia sensor networks. Comput Netw 53, 1798–1811 (2009)
M. Zawodniok, S. Jagannathan, Predictive congestion control protocol for wireless sensor networks. IEEE Trans Wirel Commun 6, 3955–3963 (2007)
M. Zawodniok, S. Jagannathan, Q. Shang, Distributed power control for cellular networks in the presence of channel uncertainties. IEEE Trans Wirel Commun 5, 540–549 (2006)
N. Zhao, Joint optimization of cooperative spectrum sensing and resource allocation in multi-channel cognitive radio sensor networks. Circuits Syst Signal Process 35, 2563–2583 (2016)
S. Zhao, Y.S. Shmaliy, C.K. Ahn, Bias-constrained optimal fusion filtering for decentralized WSN with correlated noise sources. IEEE Trans Signal Inf Process Netw 4, 727–735 (2018)
Acknowledgement
The authors gratefully acknowledge the financial and other support of this research, provided by the Islamic Azad university Islamshahr branch, Islamshahr, Iran.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations
Rights and permissions
About this article
Cite this article
Farahani, S.S.S., Derakhshan, S.F. Nonmonotonic-Based Congestion Control Schemes for a Delayed Nonlinear Network. Circuits Syst Signal Process 39, 154–174 (2020). https://doi.org/10.1007/s00034-019-01187-x
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00034-019-01187-x