Novel hysteretic noisy chaotic neural network for broadcast scheduling problems in packet radio networks

IEEE Transactions on Neural Networks

Volumn 21, Issue 9, 2010, Pages 1422-1433

  Sun, Ming ^a   Zhao, Lin ^b   Cao, Wei ^a   Xu, Yaoqun ^c   Dai, Xuefeng ^a   Wang, Xiaoxu ^d  

^a QIQIHAR UNIVERSITY   (China)

^b HARBIN ENGINEERING UNIVERSITY   (China)

^c HARBIN UNIVERSITY OF COMMERCE   (China)

^d NORTHWESTERN POLYTECHNICAL UNIVERSITY   (China)

Author keywords

Broadcast scheduling problems; hysteretic; noisy chaotic neural network; packet radio network

Indexed keywords

AVERAGE TIME DELAY; BROADCAST SCHEDULING PROBLEMS; CHANNEL UTILIZATION; COMBINATORIAL OPTIMIZATION PROBLEMS; EQUIVALENT MODEL; FRAME LENGTH; FRAME STRUCTURE; HIGHER NOISE LEVELS; HYSTERETIC; HYSTERETIC DYNAMICS; MULTIPLE ACCESS; NEAR-OPTIMAL SOLUTIONS; NETWORK PARAMETERS; NOISE AMPLITUDE; NOISY CHAOTIC NEURAL NETWORKS; OPTIMAL TIME; PACKET RADIO NETWORKS; SIMULATION RESULT; STOCHASTIC CHAOTIC SIMULATED ANNEALING;

COMBINATORIAL OPTIMIZATION; HYSTERESIS; PACKET NETWORKS; RADIO; RADIO BROADCASTING; SIMULATED ANNEALING; SOIL STRUCTURE INTERACTIONS; STIFFNESS; STRUCTURAL FRAMES; STRUCTURAL OPTIMIZATION; TIME DELAY; TIME DIVISION MULTIPLE ACCESS;

NEURAL NETWORKS;

ALGORITHM; ARTICLE; ARTIFACT; ARTIFICIAL NEURAL NETWORK; COMPUTER SIMULATION; ELECTRONICS; MASS MEDIUM; METHODOLOGY; NONLINEAR SYSTEM; STANDARD; TELECOMMUNICATION;

ALGORITHMS; ARTIFACTS; COMPUTER SIMULATION; ELECTRONICS; MASS MEDIA; NEURAL NETWORKS (COMPUTER); NONLINEAR DYNAMICS; RADIO;

EID: 77956326349     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2010.2059041     Document Type: Article

References (42)

1. N. Funabiki and J. Kitamichi, "A gradual neural network algorithm for broadcast scheduling problems in packet radio networks," IEICE Trans. Fundam., vol. E82-A, no. 5, pp. 815-824, 1999.
2. S. Salcedo-Sanz, C. Bousoño-Calzön, and A. R. Figueiras-Vidal, "A mixed neural-genetic algorithm for the broadcast scheduling problem," IEEE Trans. Wireless Commun., vol. 2, no. 2, pp. 277-283, Mar. 2003.
3. G. Wang and N. Ansari, "Optimal broadcast scheduling in packet radio networks using mean field annealing," IEEE J. Sel. Areas Commun., vol. 15, no. 2, pp. 250-260, Feb. 1997.
4. L. Wang and H. Shi, "A gradual noisy chaotic neural network for solving the broadcast scheduling problem in packet radio networks," IEEE Trans. Neural Netw., vol. 17, no. 4, pp. 989-1000, Jul. 2006.
5. J. Yeo, H. Lee, and S. Kim, "An efficient broadcast scheduling algorithm for TDMA ad-hoc networks," Comput. Oper. Res., vol. 29, no. 13, pp. 1793-1806, 2002.
6. A. Ephremides and T. V. Truong, "Scheduling broadcast in multihop radio networks," IEEE Trans. Commun., vol. 38, no. 6, pp. 456-460, Jun. 1990.
7. G. Chakraborty and Y. Hirano, "Genetic algorithm for broadcast scheduling in packet radio networks," in Proc. IEEE Int. Conf. Evol. Comput., Anchorage, AK, May 1998, pp. 183-188.
8. N. Funabiki and Y. Takefuji, "A parallel algorithm for broadcast scheduling problems in packet radio networks," IEEE Trans. Commun., vol. 41, no. 6, pp. 828-831, Jun. 1993.
9. H. Shi and L. Wang, "Broadcast scheduling in wireless multihop networks using a neural-network-based hybrid algorithm," Neural Netw., vol. 18, nos. 5-6, pp. 765-771, 2005.
10. L. Chen and K. Aihara, "Chaotic simulated annealing by a neural network model with transient chaos," Neural Netw., vol. 8, no. 6, pp. 915-930, 1995.
11. I. Tokuda, K. Aihara, and T. Nagashima, "Adaptive annealing for chaotic optimization," Phys. Rev. E, Stat. Phys. Plasmas Fluids Relat. Interdiscip. Top., vol. 58, no. 4, pp. 5157-5160, 1998.
12. L. Chen and K. Aihara, "Global searching ability of chaotic neural networks," IEEE Trans. Ciruits Syst. I, Fundam. Theory Appl., vol. 46, no. 8, pp. 974-993, Aug. 1999.
13. T. Kwok and K. Smith, "A unified framework for chaotic neural-network approaches to combinatorial optimization," IEEE Trans. Neural Netw., vol. 10, no. 4, pp. 978-981, Jul. 1999.
14. T. Kwok and K. Smith, "Experimental analysis of chaotic neural network models for combinatorial optimization under a unifying framework," Neural Netw., vol. 13, no. 7, pp. 731-744, 2000.
15. A. Mirzaei and R. Safabakhsh, "Optimal matching by the transiently chaotic neural network," Appl. Soft Comput., vol. 9, no. 3, pp. 863-873, 2009.
16. L. Wang, S. Li, F. Tian, and X. Fu, "A noisy chaotic neural network for solving combinatorial optimization problems: Stochastic chaotic simulated annealing," IEEE Trans. Syst. Man Cybern. B, Cybern., vol. 34, no. 5, pp. 2119-2125, Oct. 2004.
17. L. Wang and K. Smith, "On chaotic simulated annealing," IEEE Trans. Neural Netw., vol. 9, no. 4, pp. 716-718, Jul. 1998.
18. L. Zhao, M. Sun, J. Cheng, and Y. Xu, "A novel chaotic neural network with the ability to characterize local features and its application," IEEE Trans. Neural Netw., vol. 20, no. 4, pp. 735-742, Apr. 2009.
19. C. Zhou, T. Chen, and W. Huang, "Chaotic neural network with nonlinear self-feedback and its application in optimization," Neurocomputing, vol. 14, no. 3, pp. 209-222, 1997.
20. L. Wang, W. Liu, and H. Shi, "Noisy chaotic neural networks with variable thresholds for the frequency assignment problem in satellite communications," IEEE Trans. Syst. Man Cybern. C. Appl. Rev., vol. 38, no. 2, pp. 209-217, Mar. 2008.
21. L. Wang, W. Liu, and H. Shi, "Delay-constrained multicast routing using the noisy chaotic neural networks," IEEE Trans. Comput., vol. 58, no. 1, pp. 82-89, Jan. 2009.
22. S. Bharitkar and J.M. Mendel, "The hysteretic Hopfield neural network," IEEE Trans. Neural Netw., vol. 11, no. 4, pp. 879-888, Jul. 2000.
23. W. J. Freeman, "Simulation of chaotic EEG patterns with a dynamic model of the olfactory system," Biol. Cybern. Syst., vol. 56, nos. 2-3, pp. 139-150, 1987.
24. G. W. Hoffman and M. W. Benson, "Neurons with hysteresis form a network that can learn without any changes in synaptic strengths," in Proc. Amer. Inst. Phys. Conf. Neural Netw. Comput., vol. 151. Aug. 1986, pp. 219-226.
25. J. D. Keeler, E. E. Pichler, and J. Ross, "Noise in neural networks: Thresholds, hysteresis and neuromodulation of signal-noise," Proc. Nat. Acad. Sci., vol. 86, no. 5, pp. 1712-1716, 1989.
26. Y. Takefuji and K. C. Lee, "An artificial hysteresis binary neuron: A model suppressing the oscillatory behaviors of neural dynamics," Biol. Cybern., vol. 64, no. 5, pp. 353-356, 1991.
27. L. Wang and J. Ross, "Synchronous neural networks of nonlinear threshold elements with hysteresis," Proc. Nat. Acad. Sci., vol. 87, no. 3, pp. 988-992, 1989.
28. X. Liu and C. Xiu, "A novel hysteretic chaotic neural network and its applications," Neurocomputing, vol. 70, nos. 13-15, pp. 2561-2565, 2007.
29. P. Thangavel and D. Gladis, "Hysteretic Hopfield network with dynamic tunneling for crossbar switch and N-queens problem," Neurocomputing, vol. 70, nos. 13-15, pp. 2544-255, 2007.
30. S. Amari, "Neural theory of association and concept-formation," Biol. Cybern., vol. 26, no. 3, pp. 175-185, 1977.
31. J. J. Hopfield and D. W. Tank, "Neural computation of decisions in optimization problems," Biol. Cybern., vol. 52, no. 3, pp. 142-152, 1985.
32. H. Nozawa, "A neural network model as a globally coupled map and applications based on chaos," Chaos, vol. 2, no. 3, pp. 377-386, 1992.
33. S. Kirkpatrick, C. D. Gelatt, and M. P. Vecchi, "Optimization by simulated annealing," Science, vol. 220, no. 4598, pp. 671-680, 1983.
34. C. Peterson and J. R. Anderson, "A mean field theory learning algorithm for neural networks," Complex Syst., vol. 1, no. 5, pp. 995-1019, 1987.
35. L. Chen and K. Aihara, "Chaos and asymptotical stability in discrete time neural networks," Phys. D, vol. 104, nos. 3-4, pp. 286-325, 1997.
36. D. Jungnickel, Graphs, Networks and Algorithms. Berlin, Germany: Springer-Verlag, 1999.
37. X. Wu, B. S. Sharif, O. R. Hinton, and C. C. Tsimenidis, "Solving optimum TDMA broadcast scheduling in mobile ad hoc networks: A competent permutation genetic algorithm approach," IEE Proc. Commun., vol. 152, no. 6, pp. 780-788, Dec. 2005.
38. I. Ahmad, B. Al-Kazemi, and A. S. Das, "An efficient algorithm to find broadcast schedule in ad hoc TDMA networks," J. Comput. Syst. Netw. Commun., vol. 2008, no. 12, pp. 1-10, Jan. 2008.
39. X. Zhang and Y. Wang, "New mixed broadcast scheduling approach using neural networks and graph coloring in wireless sensor network," J. Syst. Eng. Electron., vol. 20, no. 1, pp. 185-191, 2009.
40. R. Gunasekaran, S. Siddharth, P. Krishnaraj, M. Kalaiarasan, and V. R. Uthariaraj, "Efficient algorithms to solve broadcast scheduling problem in WiMAX mesh networks," Comput. Commun., vol. 33, no. 11, pp. 1325-1333, 2010.
41. Z. Lü and J. K. Hao, "A memetic algorithm for graph coloring," Eur. J. Oper. Res., vol. 203, no. 1, pp. 241-250, 2010.
42. D. H. Al-Omari and K. E. Sabri, "New graph coloring algorithms," Am. J. Math. Stat., vol. 2, no. 4, pp. 739-741, 2006.