Journal of Applied Science and Engineering

Published by Tamkang University Press

1.30

Impact Factor

2.10

CiteScore

Gao Zihe  1, Guo Qing1 and Na Zhenyu2

1Communication Research Center of Harbin Institute of Technology, Harbin, P.R. China
2Dalian Maritime University School of Information Science and Technology, Dalian, P.R. China


 

Received: May 7, 2010
Accepted: October 29, 2010
Publication Date: June 1, 2011

Download Citation: ||https://doi.org/10.6180/jase.2011.14.2.09  


ABSTRACT


Traditional routing algorithms for Low Earth Orbit (LEO) often adopt single path and greed mechanism, which are ambivalent to realize optimum performances for the whole network. Compared with single path routing, Multipath routing has the advantages of strong fault tolerance and load balancing which is more appropriate for LEO satellite networks. A distributed multipath routing algorithm combined with Multi-Agent System (MASMR) is proposed in the paper. In MASMR, mobile agents and ‘blackboard’are introduced. The former is used to gather multipath information and the latter provides direct interactive mode between agents. Simulation results show that, compared with Ant Colony Optimization, MASMR not only presents better end-to-end delay and but also tracks the fast changing topology of LEO satellite networks.


Keywords: Multipath Routing, Multi-Agent System, Low Earth Orbit


REFERENCES


  1. [1] Svigelj, A., Mohorcic, M., Kandus, G., et al., “Routing in ISL Networks Considering Empirical IP Traffic,” IEEE Journal on Selected Areas in Communications, Vol. 22, pp. 261272 (2004).
  2. [2] Werner, W., Berndl, G. and Edmaier, B., “Performance of Optimized Routing in LEO Inter Satellite Link Networks,” Proceedings of IEEE 47th Vehicular Technology Conference, Vol. 1, pp. 246250 (1997).
  3. [3] Chang, H. S., Kim, B. W., Lee, C. G., et al., “FSABased Link Assignment and Routing in Low-Earth Orbit Satellite Networks,” Vehicular Technology, IEEE Transactions, Vol. 47, pp. 10371048 (1998).
  4. [4] Wood, L., Clerget, A., Andrikopoulos, I., et al., “IP Routing Issues in Satellite Constellation Networks,” International Journal of Satellite Communications, Vol. 19, pp. 6992 (2001).
  5. [5] Ekici, E., Akyildiz, L. F. and Bender, M. D., “A Distributed Routing Algorithm for Datagram Traffic in LEO Satellite Networks,” IEEE/ACM Transactions on Networking, Vol. 9, pp. 137147 (2001).
  6. [6] Ekici, E., Akyildiz, L. F. and Bender, M. D., “Datagram Routing Algorithm for LEO Satellite Networks,” IEEE Infocom 2000 Conference on Computer Communications, TelAviv, Israel, pp. 500508 (2000).
  7. [7] Narvaez, P. and Clerget, A., “Internet Routing over LEO Satellite Constellations,” The 3rd International Workshop on Satellite Based Information Services Mobicom’ 1998, Dallas, Texas, pp. 5157 (1998).
  8. [8] Mohorcic, M., Svigelj, A. and Kandus, G., “Traffic Class Dependent Routing in ISL Networks,” IEEE Transactions on Aerospace and Electronic Systems, Vol. 39, pp. 11601172 (2004).
  9. [9] Fogel, D. B., “Evolutionary Computation: Toward a New Philosophy of Machine Intelligence,” IEEE Press (1995).
  10. [10] Koza, J. R., Genetic Programming: On the Programming of Computers by Means of Netural Selection, Cambridge, MA: MIT Press (1992).
  11. [11] Deneubourg, J. L., Pasteels, J. M. and Verhaeghe, J. C., “Probabilistic Behaviour in Ants: A Strategy of Errors [J],” Journal of Theoretical Biology, Vol. 105, pp. 259271 (1983).
  12. [12] Deneubourg, J. L. and Goss, S., “Collective Patterns and Decision-Making [J],” Ehtology, Ecology & Evolution, Vol. 1, pp. 295311 (1989).
  13. [13] Beckers, R., Goss, S., Deneubourg, J. L., et al., “Colony Size, Communication and Ant Foraging Strategy,” Psyche, Vol. 96, pp. 239256 (1989).
  14. [14] Colorni, A., Dorigo, M., Maniezzo, V., et al., “Distributed Optimization by Ant Colonies,” Proceedings of the 1st European Conference on Artificial Life, pp. 134142 (1991).
  15. [15] Dorigo, M., “Optimization, Learning and Natural Algorithms,” Ph. D. Thesis, Department of Electronics, Politecnico Dimilano, Italy (1992).
  16. [16] Di Caro, G. and Dorigo, M., “AntNet: Distributed Stigmergetic Control for Communications Networks,” Journal of Artificial Intelligence Research (JAIR), Vol. 9, pp. 317365 (1998).
  17. [17] Di Caro, G. and Dorigo, M., “Two Ant Colony Algorithms for Best-Effort Routing in Datagram Networks,” Proceedings of the Tenth IASTED International Conference on Parallel and Distributed Computing and Systems (PDCS’98), pp. 541546, IASTED/ ACTA Press (1998).
  18. [18] Di Caro, G. and Vasilakos, T., “Ant-SELA: AntAgents and Stochastic Automata Learn Adaptive Routing Tables for QoS Routing in ATM Networks,” ANTS’2000 - From Ant Colonies to Artificial Ants: Second International Workshop on Ant Colony Optimization, Brussels (Belgium), September 8-9 (2000).
  19. [19] Di Caro, G., Ducatelle, F. and Gambardella, L. M., “AntHocNet: An Ant-Based Hybrid Routing Algorithm for Mobile Ad Hoc Networks,” Proceedings of Parallel Problem Solving from Nature (PPSN) VIII, volume 3242 of Lecture Notes in Computer Science, pp. 461470, Springer-Verlag (2004).
  20. [20] Arnous, R. A., Arafat, H. A. and Salem, M. M. “Improving the Load Balancing within the Data Network via Modified AntNet Algorithm,” ITI 5th International Conference on Information and Communications Technology (ICICT), Cairo, pp. 189195 (2007).