Implementation of Distributed Multi-Agent Scheduling Algorithm Based on Pi-calculus

  • Bairun Li
  • Hui Kang
  • Fang MeiEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11344)


Currently, efficient use of distributed resources is a research hotspot. Considering that the structure of a distributed communication system is prone to change and many distributed algorithms are still based on the serial underlying model, this paper proposes a distributed multi-agent model based on Pi-calculus. This model takes advantage of Pi-calculus parallel computing, including using channels to transfer information. Besides this, the model combines multi-agent technology to further improve parallelism, enabling distributed resources to be used more efficiently. This paper uses the classic algorithm of heterogeneous scheduling in distributed environments, the heterogeneous earliest finish time (HEFT) algorithm as an example to apply the model by creating different topologies of the task scheduling graph. And then implement the model with Nomadic Pict using channels to transmit information and assigning tasks to multiple agents. We can prove that the distributed multi-agent model based on Pi-calculus can make use of distributed resources more efficiently compared with traditional C++ language combined with multithreading and Socket communication mechanisms assigning tasks to multiple clients.


Distributed Task scheduling Pi-calculus Multi-Agent HEFT 


  1. 1.
    Tanenbaum, A.S.: The Distributed Operating System, 1st edn. Electronic Industry Press, Beijing (2008). (USA) LU LI-NA, TranslationGoogle Scholar
  2. 2.
    Hu, T.C.: Parallel sequencing and assembly line problems. Oper. Res. 9(6), 841–848 (1961)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Milner, R.: Functions as processes. Math. Struct. Comput. Sci. 2(2), 119–141 (1992)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Topcuoglu, H., Hariri, S., Wu, M.Y.: Performance-effective and low-complexity task scheduling for heterogeneous computing. IEEE Trans. Parallel Distrib. Syst. 13(3), 260–274 (2002)CrossRefGoogle Scholar
  5. 5.
    Wojciechowski, P.T.: Nomadic Pict: language and infrastructure design for mobile computation. ACM Trans. Program. Lang. Syst. 32(4), 0164–0925 (2010)Google Scholar
  6. 6.
    Mukun, C., Kiang, M.Y.B.D.I.: BDI agent architecture for multi-strategy selection in automated negotiation. J. Univ. Comput. Sci. 18(10), 1379–1404 (2012)Google Scholar
  7. 7.
    Yu, B., Zhang, C., Li, W.J.: Pi-calculus modeling for the multi-agent collaborative system. J. Xidian Univ. 41(6), 76–82 (2014)Google Scholar
  8. 8.
    Stavrinides, G.L., Karatza, H.D.: Scheduling multiple task graphs with end-to-end deadlines in distributed real-time systems utilizing imprecise computations. J. Syst. Softw. 83(6), 1004–1014 (2010)CrossRefGoogle Scholar
  9. 9.
    Milner, R.: Communicating and Mobile Systems: The Pi-Calculus. Cambridge University Press, Cambridge (1999)zbMATHGoogle Scholar
  10. 10.
    Jing-mei, L.I., Dong-wei, S.U.N., Qi-long, H.A.N.: Research on static task scheduling based on heterogeneous chip multi-processor. J. Chin. Comput. Syst. 12(34), 2770–2774 (2014)Google Scholar
  11. 11.
    Ilie, S., Bǎdicǎ, C.: Multi-agent approach to distributed ant colony optimization. Sci. Comput. Program. 78(6), 762–774 (2013)CrossRefGoogle Scholar
  12. 12.
    Jin, C., Zhang, Y., Wang, C.: Distributed multiagent-based ant colony algorithm. Appl. Res. Comput. 35(3), 666–670 (2018)Google Scholar
  13. 13.
    Sewell, P., Wojciechowski, P.T., Unyapoth, A.: Nomadic Pict: programming languages, communication infrastructure overlays, and semantics for mobile computation. ACM Trans. Program. Lang. Syst. (TOPLAS) 32(4), 12 (2010)CrossRefGoogle Scholar
  14. 14.
  15. 15.
    Zafar, K., Baig, R., Bukhari, N., et al.: Route planning and optimization of route using simulated ant agent system. Int. J. Comput. Appl. 4(8), 457–478 (2010)Google Scholar

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© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.JiLin UniversityChangChunChina

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