Abstract
The introduction of Cyber-Physical Systems (CPS) in the industry through the digitalization of equipment, also known as Digital Twins, allows for a more customized production. Due to high market fluctuation, the implementation of a CPS should guarantee a high flexibility in both hardware and software levels to achieve a high responsiveness of the system. The software reconfiguration, specifically, introduces a question: “With heterogeneous equipment with different capabilities - namely processing and memory capabilities - where a certain software module should execute?”; that question fits on the task/resource allocation area applied to CPS software reconfiguration. Although in task allocation issue several approaches address such a problem, only a few of them focus on CPS resources optimization. Given that, an approach based on the Dutch Auction algorithm is proposed, implemented at the CPS level enables the software reconfiguration of the CPS according to the existing equipment resources. This approach, besides the optimization of the CPS resources and the energy consumption, transforms the CPS in more reliable and fault-tolerant systems. As shown by the results, despite the demonstration of its suitability in task/resource allocation problems in decentralized architectures, the proposed approach also as a major advantage of quickly finding a near-optimal solution.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Zhang, J., Yao, X., Zhou, J., Jiang, J., Chen, X.: Self-organizing manufacturing: current status and prospect for industry 4.0. In: 2017 5th International Conference on Enterprise Systems (ES). IEEE (2017). https://doi.org/10.1109/es.2017.59
Zhang, Y., Guo, Z., Lv, J., Liu, Y.: A framework for smart production-logistics systems based on CPS and industrial IoT. IEEE Trans. Industr. Inf. 14(9), 4019–4032 (2018). https://doi.org/10.1109/tii.2018.2845683
O’Brien, P.D., Nicol, R.C.: FIPA - towards a standard for software agents. BT Technol. J. 16(3), 51–59 (1998). https://doi.org/10.1023/A:1009621729979
Smith, R.G.: the contract net protocol: high-level communication and control in a distributed problem solver. IEEE Trans. Comput. C–29(12), 1104–1113 (1980). https://doi.org/10.1109/tc.1980.1675516
Bellifemine, F., Poggi, A., Rimassa, G.: JADE – A FIPA-compliant agent framework. In: Proceedings of PAAM, London, vol. 99, p. 33 (1999)
de Freitas, B.K., Venturini, L.F., Domingues, M.A., da Rosa, M.A., Issicaba, D.: Exploiting PADE to the simulation of multiagent restoration actions. In: 2019 11th International Symposium on Advanced Topics in Electrical Engineering (ATEE). IEEE (2019). https://doi.org/10.1109/atee.2019.8724852
Ye, D., Zhang, M., Vasilakos, A.V.: A survey of self-organization mechanisms in multiagent systems. IEEE Trans. Syst. Man Cybern.: Syst. 47(3), 441–461 (2017). https://doi.org/10.1109/tsmc.2015.2504350
Krishna, V.: Auction Theory. Academic Press, Cambridge (2009)
Fatima, S.S., Wooldridge, M.: Adaptive task resources allocation in multi-agent systems. In: Proceedings of the Fifth International Conference on Autonomous Agents, AGENTS 2001, pp. 537–544. Association for Computing Machinery, New York (2001). https://doi.org/10.1145/375735.376439
Wurman, P.R., Wellman, M.P., Walsh, W.E.: A parametrization of the auction design space. Games Econ. Behav. 35(1–2), 304–338 (2001). https://doi.org/10.1006/game.2000.0828
Chapman, A.C., Micillo, R.A., Kota, R., Jennings, N.R.: Decentralised dynamic task allocation: a practical game: theoretic approach. In: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2, AAMAS 2009, pp. 915–922. International Foundation for Autonomous Agents and Multiagent Systems, Richland (2009)
Wang, L., Wang, Z., Hu, S., Liu, L.: Ant colony optimization for task allocation in multi-agent systems. China Commun. 10(3), 125–132 (2013). https://doi.org/10.1109/cc.2013.6488841
Macarthur, K.S., Str, R., Ramchurn, S.D., Jennings, N.R.: A distributed anytime algorithm for dynamic task allocation in multi-agent systems. In: In Proceedings of AAAI, pp. 356–362 (2011)
dos Santos, D.S., Bazzan, A.L.C.: Distributed clustering for group formation and task allocation in multiagent systems: a swarm intelligence approach. Appl. Soft Comput. 12(8), 2123–2131 (2012). https://doi.org/10.1016/j.asoc.2012.03.016
Schlegel, T., Kowalczyk, R.: Towards self-organising agent-based resource allocation in a multi-server environment. In: Proceedings of the 6th International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2007. Association for Computing Machinery, New York (2007). https://doi.org/10.1145/1329125.1329147
An, B., Lesser, V., Sim, K.M.: Strategic agents for multi-resource negotiation. Auton. Agent. Multi-Agent Syst. 23(1), 114–153 (2010). https://doi.org/10.1007/s10458-010-9137-2
Pitt, J., Schaumeier, J., Busquets, D., Macbeth, S.: Self-organising common-pool resource allocation and canons of distributive justice. In: 2012 IEEE Sixth International Conference on Self-adaptive and Self-organizing Systems. IEEE (2012). https://doi.org/10.1109/saso.2012.31
Kash, I., Procaccia, A.D., Shah, N.: No agent left behind: dynamic fair division of multiple resources. J. Artif. Intell. Res. 51, 579–603 (2014)
Fettig, A., Lefkowitz, G.: Twisted Network Programming Essentials. O’Reilly Media, Inc., Newton (2005)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Pereira, E., Reis, J., Gonçalves, G., Reis, L.P., Rocha, A.P. (2022). Dutch Auction Based Approach for Task/Resource Allocation. In: Machado, J., Soares, F., Trojanowska, J., Yildirim, S. (eds) Innovations in Mechatronics Engineering. icieng 2021. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-79168-1_30
Download citation
DOI: https://doi.org/10.1007/978-3-030-79168-1_30
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-79167-4
Online ISBN: 978-3-030-79168-1
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)