Abstract
With the advent of Ambient Intelligence (AmI) as an inter-disciplinary methodology which ranges from Ubiquitous and Pervasive computing to Artificial Intelligence with the final aim to create a sensitive and responsive environment, the focus is moving towards integrated solutions of the encompassed technologies. Multi-Agent System (MAS) approach, characterized by a set of autonomous intelligent agents which can cooperate in order to achieve a common goal, can help the development of AmI integrated solutions. In this paper, we present a distributed MAS environment, Multi-Agent Specialized system (MASs), which supports the development of integrated AmI solutions. An application scenario considering the case of continuous Big Data processing is shown.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
The foundation for intelligent agent. http://www.fipa.org/repository/standardspecs.html
Augusto, J.C., McCullagh, P.J.: Ambient intelligence: concepts and applications. Comput. Sci. Inf. Syst. 4(1), 1–27 (2007)
Belghache, E., Georgé, J.P., Gleizes, M.P.: Towards an adaptive multi-agent system for dynamic big data analytics. In: 2016 International IEEE Conferences on Ubiquitous Intelligence & Computing (UIC/ATC/ScalCom/CBDCom/IoP/SmartWorld), pp. 753–758. IEEE (2016)
Bellifemine, F., Caire, G., Poggi, A., Rimassa, G.: Jade: a software framework for developing multi-agent applications lessons learned. Inf. Softw. Technol. 50(1–2), 10–21 (2008)
Bordini, R.H., Hübner, J.F., Wooldridge, M.: Programming Multi-agent Systems in AgentSpeak using Jason, vol. 8. Wiley, Hoboken (2007)
Cao, L., Gorodetsky, V., Mitkas, P.A.: Agent mining: the synergy of agents and data mining. IEEE Intell. Syst. 24(3), 64–72 (2009)
Di Marzo Serugendo, G., Gleizes, M.P., Karageorgos, A.: Self-organising software: from natural to artificial adaptation (2011)
Garcia-Molina, H.: Elections in a distributed computing system. IEEE Trans. Comput. 1, 48–59 (1982)
Jagadish, H., et al.: Big data and its technical challenges. Commun. ACM 57(7), 86–94 (2014)
Marz, N., Warren, J.: Big Data: Principles and Best Practices of Scalable Real-time Data Systems. Manning Publications Co., New York (2015)
Morrelli Massimiliano, C.M.: Nuova frontiera della classificazione testuale: big data e calcolo distribuito, pp. 1–20 (2019)
Pal, G., Li, G., Atkinson, K.: Multi-agent big-data lambda architecture model for e-commerce analytics. Data 3(4), 58 (2018)
Palpanas, T.: Big sequence management: a glimpse of the past, the present, and the future. In: Freivalds, R.M., Engels, G., Catania, B. (eds.) SOFSEM 2016. LNCS, vol. 9587, pp. 63–80. Springer, Heidelberg (2016). https://doi.org/10.1007/978-3-662-49192-8_6
Piette, F., Caval, C., Dinont, C., Seghrouchni, A.E.F., Taillibert, P.: A multi-agent approach for the deployment of distributed applications in smart environments. Intelligent Distributed Computing X. SCI, vol. 678, pp. 37–46. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-48829-5_4
Pokahr, A., Braubach, L., Lamersdorf, W.: Jadex: a BDI reasoning engine. In: Bordini, R.H., Dastani, M., Dix, J., El Fallah Seghrouchni, A. (eds.) Multi-Agent Programming. MSASSO, vol. 15, pp. 149–174. Springer, Boston, MA (2005). https://doi.org/10.1007/0-387-26350-0_6
Seghrouchni, A.E.F., Florea, A.M., Olaru, A.: Multi-agent systems: a paradigm to design ambient intelligent applications. In: Essaaidi, M., Malgeri, M., Badica, C. (eds.) Intelligent Distributed Computing IV, pp. 3–9. Springer, Heidelberg (2010)
Twardowski, B., Ryzko, D.: Multi-agent architecture for real-time big data processing. In: 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), vol. 3, pp. 333–337. IEEE (2014)
Winikoff, M.: Jack™ intelligent agents: an industrial strength platform. In: Bordini, R.H., Dastani, M., Dix, J., El Fallah Seghrouchni, A. (eds.) Multi-Agent Programming. MSASSO, vol. 15, pp. 175–193. Springer, Boston, MA (2005). https://doi.org/10.1007/0-387-26350-0_7
Zoumpatianos, K., Palpanas, T.: Data series management: Fulfilling the need for big sequence analytics. In: 2018 IEEE 34th International Conference on Data Engineering (ICDE), pp. 1677–1678. IEEE (2018)
Acknowledgements
Funding/Support: This work was supported by the Horizon 2020-PON 2014/2020 project B.4.M.A.S.S “Big Data for Multi-Agent Specialized System”.
Contribution: The MASs environment has been developed by Ingegneria dei Sistemi Department, Network Contacts, Molfetta, Italy.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Shashaj, A., Mastrorilli, F., Morrelli, M., Pansini, G., Iannucci, E., Polito, M. (2019). A Distributed Multi-Agent System (MAS) Application For continuous and Integrated Big Data Processing. In: Chatzigiannakis, I., De Ruyter, B., Mavrommati, I. (eds) Ambient Intelligence. AmI 2019. Lecture Notes in Computer Science(), vol 11912. Springer, Cham. https://doi.org/10.1007/978-3-030-34255-5_27
Download citation
DOI: https://doi.org/10.1007/978-3-030-34255-5_27
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-34254-8
Online ISBN: 978-3-030-34255-5
eBook Packages: Computer ScienceComputer Science (R0)
