Comparison of evolutionary multi-objective optimization algorithms for the utilization of fairness in network control

Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics

Volumn , Issue , 2010, Pages 2647-2655

  Köppen, Mario ^a   Verschae, Rodrigo ^a   Yoshida, Kaori ^a   Tsuru, Masato ^a  

^a KYUSHU INSTITUTE OF TECHNOLOGY   (Japan)

Author keywords

Evolutionary computation; Fairness; General fairness relation; Maxmin fairness; Meta heuristics; Multi objective optimization; Pareto dominance

Indexed keywords

EVOLUTIONARY COMPUTATIONS; FAIRNESS; GENERAL FAIRNESS RELATION; MAX-MIN FAIRNESS; META HEURISTICS; PARETO DOMINANCE;

ALGORITHMS; CYBERNETICS; PARETO PRINCIPLE; PARTICLE SWARM OPTIMIZATION (PSO);

MULTIOBJECTIVE OPTIMIZATION;

EID: 78751543031     PISSN: 1062922X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICSMC.2010.5641898     Document Type: Conference Paper

References (16)

1. C. A. Coello Coello and G. B. Lamont, Eds., Applications of Multi-Objective Evolutionary Algorithms. Singapore: World Scientific, 2004, ISBN 981-256-106-4.
2. D. Bertsekas and R. Gallager, Data Networks. Englewood Cliffs, N: Prentice Hall, 1992.
3. J. Y. L. Boudec. Rate adaptation, congestion control and fairness: a tutorial. [Online]. Available: http://icalwww.epfl.ch/PS-files/LEB3 132.pdf
4. J. Jaffe, "Bottleneck flow control," IEEE Trans. Commun., vol. COM-29, July 1981.
5. S. Haldar and D. K. Subramanian, "Fairness in processor scheduling in time sharing systems," SIGOPS Oper. Syst. Rev., vol. 25, no. 1, pp. 4-18, 1991.
6. R. Jain, D. Chiu, and W. Hawe, "A quantitative measure of fairness and discrimination for resource allocation in shared systems," DEC, Tech. Rep. Research Report TR-301, 1984.
7. M. Köppen, M. Tsuru, and Y. Oie, "Evolutionary approach to maxmin-air network-resource allocation," in Applications and the Internet, IEEE/IPSJ International Symposium on. Turku, Finland: IEEE Computer Society, 2008, pp. 253-256.
8. F. Kelly, "Charging and rate control for elastic traffic," Eur. Trans. Telecomm., vol. 8, pp. 33-37, Jan./Feb. 1997.
9. X. Wang, K. Kar, and J.-S. Pang, "Lexicographic max-min fairness in a wireless ad-hoc network with random access," in Proceedings of IEEE Conference on Decision and Control (CDC), San Diego, CA, December 2006.
10. M. Köppen, K. Yoshida, M. Tsuru, and Y. Oie, "Fairness-based global optimization of user-centric networks," in INC, IMS and IDC, 2009. NCM '09. Fifth International Joint Conference on, Seoul, Korea, Aug. 2009, pp. 441-443.
11. J. D. Schaffer, " Multiple objective optimization with vector evaluated genetic algorithms," in Proceedings of the 1st International Conference on Genetic Algorithms. Hillsdale, NJ, USA: L. Erlbaum Associates Inc., 1985, pp. 93-100.
12. E. Zitzler, M. Laumanns, and L. Thiele, "SPEA2: Improving the Strength Pareto Evolutionary Algorithm," in EUROGEN 2001, Evolutionary Methods for Design, Optimization and Control with Applications to Industrial Problems, K. Giannakoglou, D. Tsahalis, J. Periaux, P. Papailou, and T. Fogarty, Eds., Athens, Greece, 2002, pp. 95-100.
13. K. Deb, S. Agrawal, A. Pratap, and T. Meyarivan, "A fast elitist non-dominated sorting genetic algorithm for multi-objective optimisation: NSGA-II," in PPSN VI: Proceedings of the 6th 1nternational Conference on Parallel Problem Solving from Nature. London, UK: Springer-Verlag, 2000, pp. 849-858.
14. J. Knowles and D. Corne, "The pareto archived evolution strategy: a new baseline algorithm for pareto multi objective optimisation," in Evolutionary Computation, 1999. CEC 99. Proceedings of the 1999 Congress on, vol. 1, 1999, pp. 98-105.
15. M. Reyes-Sierra and C. A. C. Coello, " Multi-objective particle swarm optimizers: A survey of the state-of-the-art," International Journal of Computational Intelligence Research, vol. 2, no. 3, pp. 287-308, 2006.
16. J. Kennedy and R. Eberhart, "Particle swarm optimization," in IEEE International Conference on Neural Networks, Proc., vol. IV, 1995, pp. 1942-1948.