Journal of the Institute of Electronics Engineers of Korea TC (대한전자공학회논문지TC)

The Institute of Electronics and Information Engineers (대한전자공학회)
권호 표지

Reinforcement Method to Enhance Adaptive Route Search for Efficient Real-Time Application Specific QoS Routing

Real-Time Application의 효과적인 QoS 라우팅을 위한 적응적 Route 선택 강화 방법

  • Oh, Jae-Seuk (Yonsei University, Electrical and Electronic Engineering) ;
  • Bae, Sung-Il (Yonsei University, Electrical and Electronic Engineering) ;
  • Ahn, Jin-Ho (Yonsei University, Electrical and Electronic Engineering) ;
  • Sungh Kang (Yonsei University, Electrical and Electronic Engineering)
  • Published : 2003.12.01
Download PDF
⟨ Previous Next ⟩

Abstract

In this paper, we present a new method to calculate reinforcement value in QoS routing algorithm targeted for real-time applications based on Ant algorithm to efficiently and effectively reinforce ant-like mobile agents to find the best route toward destination in a network regarding necessary QoS metrics. Simulation results show that the proposed method realizes QoS routing more efficiently and more adaptively than those of the existing method thereby providing better solutions for the best route selection for real-time application that has high priority on delay jitter and bandwidth.

본 논문은 real-time 어플리케이션들을 위한 보나 효과적이고 효율적으로 ant-like mobile agent들이 QoS metrics를 고려하여 네트워크상에서 목적지까지 가장 최적화된 route을 찾는 Ant 알고리듬을 바탕으로 한 QoS 라우팅 알고리듬에서의 route 선택 강화 계산방법을 제시한다. 시뮬레이션 결과 본 논문에서 제시하는 방법이 기존의 방법보다 delay jitter와 bandwidth를 우선으로 하는 real-time application에 대한 가장 최적화된 route을 보다 효과적이고 보다 네트워크 환경에 적응적으로 찾아내는 것을 확인하였다.

Keywords

References

  1. Zhang, S., Liu, Z.: 'A QoS Routing Algorithm Based on Ant Algorithm', 25th Annual IEEE Conference on Local Computer Networks, pp. 574-578, (2000) https://doi.org/10.1109/LCN.2000.891102
  2. M. Dorigo, E. Bonabeau, & G. Theraulaz, 'Ant Algorithms and Stigmergy', Future Generation Computer Systems, Number 16, pp. 851-871, 2000 https://doi.org/10.1016/S0167-739X(00)00042-X
  3. Dorgin, M., Gambardelia, L. M.: 'Ant colony system: A cooperative learning approach to the traveling salesman problem', IEEE Trans. on Evolutionary Computation, pp. 53-66, (1997) https://doi.org/10.1109/4235.585892
  4. Stutzle, T., Dorign, M.: 'ACO algorithms for the quadratic assignment problem', New Ideas in Optimization, pp. 33-50, McGraw Hill, (1999)
  5. G. Di Caro, & M. Dorigo, 'An adaptive multiagtent rouuting algorithm inspired by ants behavior', Proc. Intelligent Agents for Telecommunications Applications 1998, 1998
  6. G. Di Caro, & M. Dorigo, 'Mobile Agents for Adaptive Routing', Proc. of the 3lst International Conference on Systems Sciences, The Big Island of Hawaii, Jan. 1998
  7. G. Quadros, E. Monteiro, & F. Boavida, 'A QoS Metric for Packet Networks,' Proceeding of SPIE International Symposium on Voice, Video, and Data Communications Conference, Nov. 1998
  8. M. Dorigo, & G. Di Caro, 'AntNet: Distributed Stigmergetic Control forNetworks,' Journal of Artificaial Intelligence Research, Number 9, pp. 317 365, 1999
  9. Z. Wang, & J. Crowcroft, 'Quality of Service Routing for Supporting Multimedia Applications,' JSAC, pp. 228 1234, 1996
  10. C. Chu, J. Gu, X. Hou, & Q. Gu, 'A Heuristic Ant algorithm for Solving QoS Multicast Routing Problem,' Evolutionary Computation, 2002 CEC '02 Proceeding of the 2002 Congress on, Vol. 2, pp. 12-17, 2002