Skip to main content

Collective Behavior Coordination and Aggregation with Low-Cost Communication

  • Conference paper
Complex Sciences (Complex 2009)

Abstract

An important natural phenomenon surfaces that satisfactory synchronization of self-driven particles can be achieved via remarkably reduced communication cost, especially for high density particle groups with low external noise. Statistical numerical evidence illustrates that a highly efficient manner is to distribute the communication messages as evenly as possible along the whole dynamic process, since it minimizes the communication redundancy. More surprisingly, it is discovered that there exists an abnormal region in the state diagram where moderately decreasing the communication cost can even improve the synchronization performance. Significantly, another interesting fact is found that low-cost communication can help the particles aggregate into synchronized clusters, which may be beneficial to explain the forming mechanism of individuals’ aggregation phenomena over biological flocks/swarms.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Vicsek, T., Czirók, A., Ben-Jacob, E., Cohen, I., Shochet, O.: Novel type of phase transition in a system of self-driven particles. Phys. Rev. Lett. 75, 1226–1229 (1995)

    Article  MathSciNet  Google Scholar 

  2. Grégoire, G., Chaté, H.: Active and passive particles: Modeling beads in a bacterial bath. Phys. Rev. Lett. 92, 025702 (2004)

    Article  Google Scholar 

  3. Aldana, M., Dossetti, V., Huepe, C., Kenkre, V.M., Larralde, H.: Phase transitions in systems of self-propelled agents and related network models. Phys. Rev. Lett. 98, 095702 (2007)

    Article  Google Scholar 

  4. Olfati-Saber, R., Murray, R.: Consensus problems in networks of agents with switching topology and time-delays. IEEE. Trans. Autom. Control. 49, 1520–1533 (2004)

    Article  MathSciNet  Google Scholar 

  5. Akyildiz, I.F., Su, W., Sankarasubramaniam, Y., Cayirci, E.: Wireless sensor networks: a survey. Computers Network 38, 393–422 (2002)

    Article  Google Scholar 

  6. Ogren, P., Fiorelli, E., Leonard, N.E.: Cooperative control of mobile sensor networks:Adaptive gradient climbing in a distributed environment. IEEE. Trans. Autom. Control. 49, 1292–1302 (2004)

    Article  MathSciNet  Google Scholar 

  7. Arai, T., Pagello, E., Parker, L.E.: Advances in Multi-Robot Systems. IEEE Trans. Robot. Autom. 18, 655–661 (2002)

    Article  Google Scholar 

  8. Li, W., Wang, X.F.: Adaptive velocity strategy for swarm aggregation. Phys. Rev. E 75, 021917 (2007)

    Article  Google Scholar 

  9. Helbing, D., Farkas, I.J., Vicsek, T.: Simulating dynamical features of escape panic. Nature (London) 407, 487–490 (2000)

    Article  Google Scholar 

  10. Cortes, J., Bullo, F.: Coordination and geometric optimization via distributed dynamical systems (2003), Arxiv preprint math.OC/0305433

    Google Scholar 

  11. Gazi, V., Passino, K.M.: Stability analysis of swarms. IEEE. Trans. Autom. Control. 48, 692–697 (2003)

    Article  MathSciNet  Google Scholar 

  12. Moreau, L.: Stability of multiagent systems with time-dependent communication links. IEEE. Trans. Autom. Control. 50, 169–182 (2005)

    Article  MathSciNet  Google Scholar 

  13. Couzin, L.D., Krause, J., Franks, N.R., Levin, S.A.: Effective leadership and decision-making in animal groups on the move. Nature (London) 433, 513–516 (2005)

    Article  Google Scholar 

  14. Hernandez-Ortiz, J.P., Stoltz, C.G., Graham, M.D.: Transport and collective dynamics in suspensions of confined swimming particles. Phys. Rev. Lett. 95, 204501 (2005)

    Article  Google Scholar 

  15. D’ Orsogna, M.R., Chuang, Y.L., Bertozzi, A.L., Chayes, L.S.: Self-propelled particles with soft-core interactions: patterns, stability, and collapse. Phys. Rev. Lett. 96, 104302 (2006)

    Article  Google Scholar 

  16. Chaté, H., Ginelli, F., Montagne, R.: Simple model for active nematics: quasi-long-range order and giant fluctuations. Phys. Rev. Lett. 96, 180602 (2006)

    Article  Google Scholar 

  17. Zhang, H.T., Chen, M.Z.Q., Stan, G.-B., Zhou, T., Maciejowski, J.M.: Collective behavior coordination with predictive mechanisms. IEEE Circuits and Systems Magazine 3, 65–87 (2008)

    Google Scholar 

  18. Zhang, H.T., Chen, M.Z.Q., Zhou, T., Stan, G.-B.: Ultrafast consensus via predictive mechanisms. Europhys. Lett. 83, 40003 (2008)

    Article  Google Scholar 

  19. Zhang, H.T., Chen, M.Z.Q., Zhou, T.: Predictive protocol of flocks with small-world connection pattern. Phys. Rev. E (in press)

    Google Scholar 

  20. Li, W., Zhang, H.T., Chen, M.Z.Q., Zhou, T.: Singularities and symmetry breaking in swarms. Phys. Rev. E 77, 021920 (2008)

    Article  MathSciNet  Google Scholar 

  21. Zhang, J., Zhao, Y., Tian, B., Peng, L.Q., Zhang, H.T., Wang, B.H., Zhou, T.: Accelerating consensus of self-driven swarm via adaptive speed via adaptive speed. Physica A (in press) (2008), doi:10.1016/j.physa.2008.11.043

    Google Scholar 

  22. Takayasu, H.: Steady-state distribution of generalized aggregation system with injection. Phys. Rev. Lett. 63, 2563–2565 (1989)

    Article  Google Scholar 

  23. Bonabeau, E., Dagorn, L.: Possible universality in the size distribution of fish schools. Phys. Rev. E 51, 5220–5223 (1995)

    Article  Google Scholar 

  24. Huepe, C., Aldana, M.: Intermittency and clustering in a system of self-driven particles. Phys. Rev. Lett. 92, 168701 (2004)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering

About this paper

Cite this paper

Zhang, HT., Chen, M.Z.Q., Zhou, T., Cheng, Z., Yu, PZ. (2009). Collective Behavior Coordination and Aggregation with Low-Cost Communication. In: Zhou, J. (eds) Complex Sciences. Complex 2009. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 5. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02469-6_92

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-02469-6_92

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02468-9

  • Online ISBN: 978-3-642-02469-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics