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Evolutionary algorithms for route selection and rate allocation in multirate multicast networks

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Abstract

In multirate multicasting, different users (receivers) in the same multicast group can receive service at different rates, depending on the user requirements and the network congestion level. Compared with unirate multicasting, this provides more flexibility to the users and allows more efficient usage of the network resources. In this paper, we simultaneously address the route selection and rate allocation problem in multirate multicast networks; that is, the problem of constructing multiple multicast trees and simultaneously allocating the rate of receivers for maximizing the sum of utilities over all receivers, subject to link capacity and delay constraints for high-bandwidth delay-sensitive applications in point-to-point communication networks. We propose a genetic algorithm for this problem and elaborate on many of the elements in order to improve solution quality and computational efficiency in applying the proposed methods to the problem. These include the genetic representation, evaluation function, genetic operators, and procedure. Additionally, a new method using an artificial intelligent search technique, called the coevolutionary algorithm, is proposed to achieve better solutions, and methods of selecting environmental individuals and evaluating fitness are developed. The results of extensive computational simulations show that the proposed algorithms provide high-quality solutions and outperform existing approach.

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References

  1. Ballardie T, Francis P, Crowcroft J (1993) Core Based Trees (CBT). In: Proceedings, SIGCOMM’93 Conference, pp 85–95

  2. Jia X, Wang L (1997) Group multicasting routing algorithm by using multiple minimum Steiner trees. Comput Commun 20:750–758

    Article  Google Scholar 

  3. Low CP, Song X (2002) On finding feasible solutions for the delay constrained group multicast routing problem. IEEE Trans Comput 51(5):581–588

    Article  MathSciNet  Google Scholar 

  4. Turletti T, Bolot JC (1994) Issues with multicast video distribution in heterogeneous packet networks. In: Proceedings, Packet Video Workshop, Portland, OR

  5. Kishino F, Manabe K, Hayashi Y, Yasuda H (1989) Variable bit-rate coding of video signals for ATM networks. IEEE J Select Areas Commun 7:801–806

    Article  Google Scholar 

  6. Li X, Paul S, Ammar M (1998) Layered video multicast with retransmission (LVMR): evaluation of hierarchical rate control. In: Proceedings, IEEE INFOCOM’98, San Francisco, CA, Vol 3, pp 1062–1072

  7. Bertsekas DP, Gallagher R (1992) Data networks, 2nd ed., Prentice-Hall, Englewood Cliffs

    MATH  Google Scholar 

  8. Kelly FP (1997) Charging and rate control for elastic traffic. Euro Trans Telecommun 8:33–37

    Article  Google Scholar 

  9. Graves E, Srikant R, Towsley D (2001) Decentralized computation of weighted Max–Min fair bandwidth allocation in networks with multicast flows. In: Proceedings, Tyrrhenian International Workshop Digital Communications (IWDC), Taormina, Italy

  10. Sarkar S, Tassiulas L (1999) Fair allocation of utilities in multirate multicast networks. In: Proceedings, 37th Annual Allerton Conference on Communication, Control and Computing, Monticello, IL

  11. Kelly FP, Maulloo AK, Tan DKH (1998) Rate control for communication networks: shadow prices, proportional fairness and stability. J Oper Res Soc 49:237–252

    Article  MATH  Google Scholar 

  12. Low SH, Lapsley DE (1999) Optimization flow control. I. Basic algorithm and convergence. IEEE/ACM Trans Network 7(6):861–874

    Article  Google Scholar 

  13. Kunniyur S, Srikant R (2000) End-to-end congestion control schemes: utility functions, random losses and ECN marks. In: Proceedings, INFOCOM 2000, Tel Aviv, Israel, March, Vol 3, pp 1323–1332

  14. Kar K, Sarkar S, Tassiulas L (2002) A scalable low-overhead rate control algorithm for multirate multicast sessions. IEEE J Select Areas Commun 20(8):1541–1557

    Article  Google Scholar 

  15. Shacham N (1992) Multipoint communication by hierarchical encoded data. In: Proceedings, IEEE INFOCOM’92 Conference, Vol 3, pp 2107–2114

  16. Fei Z, Ammar M, Zegura EW (2002) Multicast server selection: problems, complexity, and solutions. IEEE J Select Areas Commun 20(7):1399–1413

    Article  Google Scholar 

  17. Lorenz DH, Orda A (2002) Optimal partition of QoS requirements on unicast paths and multicast trees. IEEE/ACM Trans Network 10(1):102–114

    Article  Google Scholar 

  18. Matrawy A, Lambadaris I (2003) A rate adaptation algorithm for multicast sources in priority-based IP networks. IEEE Commun Lett 7(2):94–96

    Article  Google Scholar 

  19. Sarkar S, Tassiulas L (2002) A framework for routing and congestion control for multicast information flows. IEEE Trans Inform Theory 48(10):2690–2708

    Article  MATH  MathSciNet  Google Scholar 

  20. Goldberg DE (1989) Genetic algorithm in search optimization & machine learning. Addison-Wesley, Reading, MA

    Google Scholar 

  21. Michalewicz Z (1994) Genetic algorithm + data structures = evolution programs, 2nd ed., Springer-Verlag, Berlin

    Google Scholar 

  22. Moriarty DE, Miikkulainen R (1997) Forming neural networks through efficient and adaptive coevolution. Evolutionary Comput 5:373–399

    Google Scholar 

  23. Potter MA (1997) The design and analysis of a computational model of cooperative coevolution. PhD dissertation. George Mason University, Fairfax, VA

  24. Rosin CD, Belew RK (1997) New methods for competitive coevolution. Evolutionary Comput 5:1–29

    Google Scholar 

  25. Maher ML, Poon J (1996) Modeling design exploration as co-evolution. Microcomput Civil Eng 11:195–210

    Article  Google Scholar 

  26. Kim YK, Kim SJ, Kim JY (2000) Balancing and sequencing mixed-model U-lines with a coevolutionary algorithm. Product Plan Control 11(8):754–764

    Article  Google Scholar 

  27. Williamson B (2000) Developing IP multicasting networks, Vol I. Cisco Press, Indianapolis, IN

    Google Scholar 

  28. Wittmann R, Zitterbart M (2001) Multicast communication—protocols and applications. Morgan Kaufmann, San Francisco, CA

    Google Scholar 

  29. Davis L (1985) Applying adaptive algorithms to epistatic domains. In: Proceedings, International Joint Conference on Artificial Intelligence, pp 162–164

  30. Whitley D (1989) The genitor algorithm and selection pressure: why rank-based allocation of reproductive trials is best. In: Schaffer JD (ed) Proceedings of 3rd International Conference on Genetic Algorithms, Virginia, June. Morgan Kaufmann, San Márteo, CA, pp 116–121

  31. Syswerda G (1991) A study of reproduction in generational and steady-state genetic algorithms. In: Rawlins GJE (ed) Foundations of genetic algorithms. Morgan Kaufmann, San Márteo, CA, pp 94–101

    Google Scholar 

  32. Varian HR (2002) Microeconomic analysis, 3rd ed. Norton, New York

    Google Scholar 

  33. Davidor Y (1991) A naturally occurring niche and species phenomenon: the model and first results. In: Belew R, Booker L (eds) Proceedings of 4th International on Conference Genetic Algorithms, San Diego, July. Morgan Kaufmann, San Márteo, CA, pp 257–263

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Kim, SJ., Choi, MK. Evolutionary algorithms for route selection and rate allocation in multirate multicast networks. Appl Intell 26, 197–215 (2007). https://doi.org/10.1007/s10489-006-0014-2

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