Abstract
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.
Supported by CERNET Innovation Protect(NGII20170506).
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Tanenbaum, A.S.: The Distributed Operating System, 1st edn. Electronic Industry Press, Beijing (2008). (USA) LU LI-NA, Translation
Hu, T.C.: Parallel sequencing and assembly line problems. Oper. Res. 9(6), 841–848 (1961)
Milner, R.: Functions as processes. Math. Struct. Comput. Sci. 2(2), 119–141 (1992)
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)
Wojciechowski, P.T.: Nomadic Pict: language and infrastructure design for mobile computation. ACM Trans. Program. Lang. Syst. 32(4), 0164–0925 (2010)
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)
Yu, B., Zhang, C., Li, W.J.: Pi-calculus modeling for the multi-agent collaborative system. J. Xidian Univ. 41(6), 76–82 (2014)
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)
Milner, R.: Communicating and Mobile Systems: The Pi-Calculus. Cambridge University Press, Cambridge (1999)
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)
Ilie, S., Bǎdicǎ, C.: Multi-agent approach to distributed ant colony optimization. Sci. Comput. Program. 78(6), 762–774 (2013)
Jin, C., Zhang, Y., Wang, C.: Distributed multiagent-based ant colony algorithm. Appl. Res. Comput. 35(3), 666–670 (2018)
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)
The Nomadic Pict System.http://www.cs.put.poznan.pl/pawelw/npict
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)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Li, B., Kang, H., Mei, F. (2018). Implementation of Distributed Multi-Agent Scheduling Algorithm Based on Pi-calculus. In: Qiu, M. (eds) Smart Computing and Communication. SmartCom 2018. Lecture Notes in Computer Science(), vol 11344. Springer, Cham. https://doi.org/10.1007/978-3-030-05755-8_19
Download citation
DOI: https://doi.org/10.1007/978-3-030-05755-8_19
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-05754-1
Online ISBN: 978-3-030-05755-8
eBook Packages: Computer ScienceComputer Science (R0)