생체모방 알고리즘 기반 통신 네트워크 기술

  • Published : 2012.03.30

Abstract

수십 억년 동안 진화를 거듭해온 지구상의 생명체들은 외부의 제어 없이 독자적으로 단순한 행동 규칙에 따라 기능을 수행하여 주어진 목적의 최적해를 달성한다. 이러한 다양한 생명체의 행동 원리를 모델링하여 만든 알고리즘을 생체모방 알고리즘(Bio-Inspired Algorithm)이라 한다. 생체모방 알고리즘은 다수의 개체가 존재하며, 주변 환경이 동적으로 변하고, 가용 자원의 제약이 주어지며, 이질적인 특성을 갖는 개체들이 분잔 및 자율적으로 움직이는 환경에서 안정성, 확장성, 적응성과 같은 특징을 보여주는데, 이는 통신 네트워크 환경 및 서비스 요구사항과 유사성을 갖는다. 본 논문에서는 대표적인 생체모방 알고리즘으로 통신 및 네트워킹 기술로 사용되는 Ant Colony 알고리즘, Bee 알고리즘, Firefly 알고리즘, Flocking 알고리즘에 대해 살펴보고, 관련 프로젝트 및 연구 동향을 정리한다. 이를 통해 현재의 생체모방 알고리즘의 한계를 극복하고 미래 통신 및 네트워킹 기술이 나아갈 방향을 제시한다.

Keywords

References

  1. F. Dressler, O. B. Akan, "A Survey on Bio-inspired Networking," Computer Networks Journal (Elsevier), vol. 54, no. 6, pp. 881-900, April 2010. https://doi.org/10.1016/j.comnet.2009.10.024
  2. F. Dressler, O. B. Akan, "Bio-inspired Networking: From Theory to Practice," IEEE Communications Magazine, vol. 48, no. 11, pp. 176-183, November 2010.
  3. Craig W. Reynolds, "Flocks, herds, and schools: A distributed behavioral model", ACM Computer Graphics, vol. 21, no. 4, pp. 25-34, 1987. https://doi.org/10.1145/37402.37406
  4. Cucker, F. ; Smale, S., "Emergent Behavior in Flocks", IEEE Transactions on Automatic Control, vol. 52, no. 5, pp. 852-960, May 2007. https://doi.org/10.1109/TAC.2007.895842
  5. Hui Yu, Ji-Gui Jian, "Flocking motion control of mobile agents based on distance-dependent adjacency matrix", International Conference on Wavelet Analysis and Pattern Recognition, vol. 1, pp. 17-22, Aug. 2008.
  6. Seung-Yeal Ha, Taeyoung Ha, Jong-Ho Kim, "Emergent Behavior of a Cucker-Smale Type Particle Model With Nonlinear Velocity Couplings", IEEE Transactions on Automatic Control, vol. 55, no. 7, pp. 1679-1683, July 2010. https://doi.org/10.1109/TAC.2010.2046113
  7. Demetriou, M.A, "Distributed parameter methods for moving sensor networks in unison", American Control Conference, 2008, pp. 273-278, June 2008.
  8. Schwager, M., Slotine, J.-J., Rus, D., "Consensus learning for distributed coverage control", IEEE International Conference on Robotics and Automation, pp. 1042-1048, May 2008.
  9. Bin Xu, Kurdila, A.J., Stilwell, D.J., "Geometric ergodicity of the distributional consensus problem in vehicle network control", IEEE Conference on Decision and Control (CDC), pp. 7499-7506, Dec. 2010.
  10. "OUTLOOK: Visions and research directions for the Wireless World," WWRF(World Wide Radio Forum), no. 4, July, 2009.
  11. I. Chlamtac, M. Conti, J.J. Liu, "Mobile ad hoc networking: imperatives and challenges," Elsevier Ad Hoc Networks, vol. 1, no. 1, pp. 13-64, 2003. https://doi.org/10.1016/S1570-8705(03)00013-1
  12. Dorigo, M., Birattari, M., Stutzle, T., "Ant colony optimization", IEEE Computational Intelligence Magazine, vol. 1, no. 4, pp. 28-39, Nov. 2006. https://doi.org/10.1109/MCI.2006.329691
  13. M. Dorigo, C. Blum, "Ant colony optimization theory: A survey", Theoretical Computer Science, vol. 344, pp. 243-278, Nov. 2005. https://doi.org/10.1016/j.tcs.2005.05.020
  14. Pham DT, Ghanbarzadeh A, Koc E, Otri S, Rahim S and Zaidi M. "The Bees Algorithm," Technical Note, Manufacturing Engineering Centre, Cardiff University, UK, 2005.
  15. Karaboga.D, "An idea based on honey bee swarm for numerical optimization.", Technical Report TR06, Erciyes University, Engineering Faculty, Computer Engineering Department, 2005.
  16. G. Werner-Allen, G. Tewari, A Patel, R.Nagpal, and M. Welsh, "Firefly-Inspired Sensor Network Synchronicity with Realistic Radio Effects."InSenSys, 2005.
  17. J. Degesys, I. Rose, A Patel, R Nagpal, "Desync: Self- organizing desynchronization and tdma on wireless sensor networks, "International Conference on Information Processing in Sensor Networks, ACM, pp. 11-20, 2007.
  18. J.A. Acebron, L.L. Bonilla, C.J. Perez-Vicente, F. Ritort, R. Spigler, The Kuramoto model: "A simple paradigm for synchronization phenomena", Rev. Mod. Phys., vol. 77, pp. 137-185, 2005. https://doi.org/10.1103/RevModPhys.77.137
  19. Olfati-Saber, R., "Flocking for multi-agent dynamic systems: algorithms and theory," IEEE Transactions on Automatic Control, vol. 51, no.3, pp. 401-420, March 2006. https://doi.org/10.1109/TAC.2005.864190
  20. J. A. Carrillo, M. Fornasier, J. Rosado, and G. Toscani, "Asymptotic flocking dynamics for thekinetic cucker-smale model," SlAM Journal on Mathematical Analysis, 2010.
  21. M. Eigen, P. Schuster, "The Hypercycle: A Principle of Natural Self Organization", Springer, 1979.
  22. M. Wang, T. Suda, "The Bio-Networking Architecture: A Biologically inspired Approach to the Design of Scalable, Adaptive and Survivable/Available Network Applications", IEEE Symposium on Applications and the Internet (SAINT), 2001.
  23. J. Suzuki, T. Suda, "Adaptive Behavior Selection of Autonomous Objects in the Bio-Networking Architecture," Symposium on Autonomous Intelligent Networks and Systems, 2002.
  24. Montes de Oca M.A, Stuetzle T., Birattari M., Dorigo M. "Incremental Social Learning Applied to a Decentralized Decision-Making Mechanism: Collective Learning Made Faster," IEEE Computer Society Press, 2010.
  25. Stirling T., Wischmann S., Floreano D. "Energy-efficient indoor search by swarms of simulated flying robots without global information, " vol. 4, no. 2, pp. 117-143, Feb. 2010. https://doi.org/10.1007/s11721-010-0039-3
  26. F. Ingelrest, G. Barrenetxea, G. Schaefer, M. Vetterli, O. Couach and M. Parlange "SensorScope: Application-Specific Sensor Network for Environmental Monitoring," ACM Transactions on Sensor Networks, vol 6, no 2, 2010.
  27. C. Jardak, K. Rerkrai, A. Kovacevic, J. Riihijarvi and P. Mahonen, "Design of Large-scale Agricultural Wireless Sensor Networks: Email form the Vineyard", International Journal for Sensor Networks (IJSNET), vol. 8, no.1, 2010.