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Structures generated in a multiagent system performing information fusion in peer-to-peer resource-constrained networks

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Abstract

There has recently been a major advance with respect to how information fusion is performed. Information fusion has gone from being conceived as a purely hierarchical procedure, as is the case of traditional military applications, to now being regarded collaboratively, as holonic fusion, which is better suited for civil applications and edge organizations. The above paradigm shift is being boosted as information fusion gains ground in different non-military areas, and human–computer and machine–machine communications, where holarchies, which are more flexible structures than ordinary, static hierarchies, become more widespread. This paper focuses on showing how holonic structures tend to be generated when there are constraints on resources (energy, available messages, time, etc.) for interactions based on a set of fully intercommunicating elements (peers) whose components fuse information as a means of optimizing the impact of vagueness and uncertainty present message exchanges. Holon formation is studied generically based on a multiagent system model, and an example of its possible operation is shown. Holonic structures have a series of advantages, such as adaptability, to sudden changes in the environment or its composition, are somewhat autonomous and are capable of cooperating in order to achieve a common goal. This can be useful when the shortage of resources prevents communications or when the system components start to fail.

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References

  1. Alston A, Beautement P, Dodd L (2005) Implementing edge organizations: exploiting complexity (part 1: a framework for the characterization of edge organizations and their environments)

  2. Akyildiz I, Su W, Sankarasubramaniam Y, Cayirci E (2002) Wireless sensor networks: a survey. Comput Netw 38(4):393–422

    Article  Google Scholar 

  3. Alberts DS, Hayes RE (2005) Power to the Edge. Command and control in the information age, 3rd edn. Command and Control Research Program (CCRP), Washington, USA

    Google Scholar 

  4. Alston A, Beautement P, Dodd L (2005) Implementing edge organizations: exploiting complexity (part 1: a framework for the characterization of edge organizations and their environments). In: 10th international command and control research and technology symposium McLean, Virginia

  5. Andrade J, Ares J, Garcia R, Martinez MA, Pazos J, Suarez S (2015) A game theory based approach for building holonic virtual enterprises. IEEE Trans Syst Man Cybern Syst 45(2):291–302

    Article  Google Scholar 

  6. Bellavista P, Giannelli C, Lagkas T, Sarigiannidis P (2018) Multi-domain SDN controller federation in hybrid FIWI-MANET networks. Eurasip J Wirel Commun Netw. https://doi.org/10.1186/s13638-018-1119-0.

    Article  Google Scholar 

  7. Benaskeur AR, Irandoust H, McGuire P, Brennan R (2007) Holonic control-based sensor management. In: 2007 10th international conference on information fusion, pp 1–8. https://doi.org/10.1109/ICIF.2007.4407975

  8. Boström H, Andler SF, Brohede M, Johansson R, Karlsson A, Laere J, Niklasson L, Nilsson M, Persson A, Ziemke T (2007) On the definition of information fusion as a field of research

  9. Botti V, Giret A (2008) ANEMONA: a multi-agent methodology for holonic manufacturing systems. Advanced manufacturing. Springer, New York

    Google Scholar 

  10. Botti V, Giret A (2008) ANEMONA: a multi-agent methodology for holonic manufacturing systems. Owner: h Added to JabRef: 2015.10.05

  11. Bujari A, Conti M, De Francesco C, Palazzi CE (2019) Fast multi-hop broadcast of alert messages in VANETs: an analytical model. Ad Hoc Netwo 82:126–133. https://doi.org/10.1016/j.adhoc.2018.07.024.

    Article  Google Scholar 

  12. Cao Y, Sun Z (2013) Routing in delay/disruption tolerant networks: a taxonomy, survey and challenges. IEEE Commun Surv Tutor 15(2):654–677

    Article  Google Scholar 

  13. Chalkiadakis G (2012) Cooperative game theory: basic concepts and computational challenges. IEEE Intell Syst 27(3):86–90

    Article  Google Scholar 

  14. Chalkiadakis G, Elkind E, Wooldridge M (2011) Computational aspects of cooperative game theory (synthesis lectures on artificial intelligence and machine learning). Morgan & Claypool Publishers, San Rafael

    MATH  Google Scholar 

  15. Chen M, Gonzalez S, Vasilakos A, Cao H, Leung VC (2011) Body area networks: a survey. Mob.Netw Appl 16(2):171–193

    Article  Google Scholar 

  16. Curiel I (1997) Cooperative game theory and applications. Cooperative games arising from combinatorial optimization problems, Theory and decision library C, 1st edn. Springer, New York

    MATH  Google Scholar 

  17. Dervin B (1998) Sense-making theory and practice: an overview of user interests in knowledge seeking and use. J Knowl Manag 2(2):36–46. https://doi.org/10.1108/13673279810249369

    Article  Google Scholar 

  18. Fischer K, Schillo M, Siekmann J (2003) Holonic multiagent systems: a foundation for the organisation of multiagent systems. In: MarÃk V, McFarlane D, Valckenaers P (eds) Holonic and multi-agent systems for manufacturing, lecture notes in computer science, vol 2744. Springer, Berlin, pp 71–80

    Chapter  Google Scholar 

  19. Fischer K, Schillo M, Siekmann J (2003) Holonic multiagent systems: a foundation for the organisation of multiagent systems. International conference on industrial applications of holonic and multi-agent systems. Springer, Berlin, pp 71–80

    Google Scholar 

  20. Foo PH, Ng GW (2013) High-level information fusion: an overview. J Adv Inf Fusion 8(1):33–72

    Google Scholar 

  21. Frankel J, Pepper T (2000) The gnutella protocol specification v0.4 (document revision 1.2). http://www.content-networking.com/papers/gnutella-protocol-04.pdf

  22. Gerber C, Siekmann J, Vierke G (1999) Holonic multi-agent systems. DFKI Research Report RR-99-03, Kaiserslautern

  23. Habib C, Makhoul A, Darazi R, Couturier R (2018) Health risk assessment and decision-making for patient monitoring and decision-support using wireless body sensor networks. Inf Fus 47:10–22. https://doi.org/10.1016/j.inffus.2018.06.008

    Article  Google Scholar 

  24. Horling B, Lesser V (2004) A survey of multi-agent organizational paradigms. Knowl Eng Rev 19(4):281–316. https://doi.org/10.1017/S0269888905000317

    Article  Google Scholar 

  25. Jiagao W, Yue M, Linfeng L (2018) Cost-efficient dynamic quota-controlled routing in multi-community delay-tolerant networks. Int J Distrib Sens Netw 14(5):1–13. https://doi.org/10.1177/1550147718776227

    Article  Google Scholar 

  26. Karagiannis G, Altintas O, Ekici E, Heijenk G, Jarupan B, Lin K, Weil T (2011) Vehicular networking: A survey and tutorial on requirements, architectures, challenges, standards and solutions. IEEE Commun Surv Tutor 13(4):584–616. https://doi.org/10.1109/SURV.2011.061411.00019

    Article  Google Scholar 

  27. Koestler A (1982) The ghost in the machine. Random House, New York

    Google Scholar 

  28. Lichman M (2013) UCI machine learning repository. http://archive.ics.uci.edu/ml. Accessed July 2018

  29. Mařík V, Schirrmann A, Trentesaux D, Vrba P (2015) Industrial applications of holonic and multi-agent systems. In: Proceedings of 7th international conference, HoloMAS 2015, Valencia, Spain, September 2–3, 2015. Lecture notes in computer science. Springer International Publishing. https://books.google.com.uy/books?id=EhNcCgAAQBAJ. Accessed July 2018

  30. Mařík V, Vrba P, Leitão P (2011) Holonic and multi-agent systems for manufacturing. In: 5th international conference on industrial applications of holonic and multi-agent systems, HoloMAS 2011, Toulouse, France, August 29–31, 2011, Proceedings. Lecture notes in computer science. Springer, Berlin. https://books.google.com.uy/books?id=DmSrCAAAQBAJ. Accessed July 2018

  31. Mathews J (1996) Holonic organisational architectures. Hum Syst Manag 15(1):27–54

    Article  Google Scholar 

  32. Mc.Hugh P, Merli GW (1995) Beyond Business process reengineering—towards the holonic enterprise. Wiley, New York

    Google Scholar 

  33. Meer HD, Koppen C (2005) Characterization of self-organization. Lecture notes in computer science. Springer, New York

    Google Scholar 

  34. Meer HD, Koppen C (2005) Self-organization in peer-to-peer systems. Lecture notes in computer science. Springer, New York

    Google Scholar 

  35. Misra S, Woungang I, Misra SC (eds) (2009) Guide to wireless ad hoc networks. Computer communications and networks. Springer, London

    Google Scholar 

  36. Mujeeb Ur R, Sheeraz A, Sarmad Ullah K, Shabana B, Ahmed SH (2018) Performance and execution evaluation of vanets routing protocols in different scenarios. EAI Endorsed Trans Energy Web, 5(17):1-5 (2018) (17), 1. https://doi.org/10.4108/eai.10-4-2018.154458. http://proxy.timbo.org.uy:443/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=edsdoj&AN=edsdoj.7e4cae33bf04ee682d86fccac0ad5ed&lang=es&site=eds-live. Item Citation: . EAI Endorsed Trans Energy Web, 5(17):1–5 (2018) Related material: https://doaj.org/toc/2032-944X Publication Type: Academic Journal; Source: EAI Endorsed Trans Energy Web, 5(17):1–5 (2018); Language: English; Format: electronic resource; Publication Date: 20180401; Rights: Journal Licence: CC BY; Imprint: European Alliance for Innovation (EAI), 2018

  37. Nakamura EF, Loureiro AAF, Boukerche A, Zomaya AY (2014) Localized algorithms for information fusion in resource constrained networks. Inf Fusion 15:2–4 Special Issue: Resource Constrained Networks

    Article  Google Scholar 

  38. Napster. www.Napster.com. Accessed July 2018

  39. Padgham L, Winikoff M (2005) Appendix C: the AUML notation. Wiley, Hoboken, pp 205–213. https://doi.org/10.1002/0470861223.app3

    Book  Google Scholar 

  40. Paggi H, Soriano J, Lara JA (2018) A multi-agent system for minimizing information indeterminacy within information fusion scenarios in peer-to-peer networks with limited resources. Inf Sci 451–452:271–294. https://doi.org/10.1016/j.ins.2018.04.019

    Article  MathSciNet  Google Scholar 

  41. Paggi Straneo H, Alonso Amo F, Crespo del Arco JS (2010) Informatics world network, cohesion and complex system structure. Systemics and informatics world network SIWN 2010

  42. Raol JR (2015) Data fusion mathematics. Theory and practice. CRC Press, Boca Raton

    Book  Google Scholar 

  43. Schwaiger A, Stahmer B (2005) Probabilistic holons for efficient agent-based data mining and simulation. Springer, Berlin, pp 50–63. https://doi.org/10.1007/11537847-5

    Book  Google Scholar 

  44. Simon H (1996) The sciences of the artificial. MIT Press. https://books.google.com.uy/books?id=k5Sr0nFw7psC. Accessed July 2018

  45. Soriano FJ (2003) Modelo de arquitectura para gestion cooperativa de sistemas y servicios distribuidos basado en agentes autonomos. Thesis

  46. Stutzbach D, Rejaie R (2006) Understanding churn in peer-to-peer networks. In: Proceedings of the ACM SIGCOMM Internet Measurement Conference, IMC, pp 189–202. https://doi.org/10.1145/1177080.1177105

  47. Sugiyama S (2007) Basic concept in service science with holon. citeulike-article-id:2982892. Accessed July 2018

  48. Tavli B, Heinzelman W (2006) Mobile ad hoc networks. Energy-efficient real-time data communications. Springer, Berlin

    MATH  Google Scholar 

  49. Turnbull S (2000) The governance of firms controlled by more than one board: theory development and examples. Thesis

  50. Ulieru M (2002) Emergence of holonic enterprises from multi-agent systems: a fuzzy-evolutionary approach. Frontiers in AI and applications series. IOS Press, pp 187–215

  51. Valckenaers P, Van Brussel H (2005) Fundamental insights into holonic systems design. Springer, Berlin, pp 11–22. https://doi.org/10.1007/11537847-2

    Book  Google Scholar 

  52. Valencia-Jiménez JJ, Fernández-Caballero A (2008) Holonic multi-agent system model for fuzzy automatic speech/speaker recognition. In: Agent and multi-agent systems: technologies and applications: second KES international symposium, KES-AMSTA 2008, Incheon, Korea, March 26–28, 2008. Proceedings, pp 73–82. Springer, Berlin

  53. Vu QH, Lupu M, Ooi BC (2010) Peer-to-peer computing. Principles and applications, 1st edn. Springer-Verlag, Berlin

    Book  Google Scholar 

  54. Guo Y, Yin C, Li M, Ren X, Liu P (2018) Mobile e-commerce recommendation system based on multi-source information fusion for sustainable e-business. Sustainability 10(1):147

    Article  Google Scholar 

  55. Yancai X, Yujia W, Zhengtao D (2018) The application of heterogeneous information fusion in misalignment fault diagnosis of wind turbines. Energies 11(7):1655 (2018) (7), 1655. https://doi.org/10.3390/en11071655. http://proxy.timbo.org.uy:443/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=edsdoj&AN=edsdoj.25415979f1df4131b83675b29e81dda7&lang=es&site=eds-live. Item Citation: Energies 11(7):1655 (2018) Related Material: http://www.mdpi.com/1996-1073/11/7/1655 Related Material: https://doaj.org/toc/1996-1073 Publication Type: Academic Journal; Source: Energies 11(7):1655 (2018); Language: English; Format: electronic resource; Publication Date: 20180601; Rights: Journal Licence: CC BY; Imprint: MDPI AG, 2018

  56. Zhong H, Shao L, Cui J, Xu Y (2018) An efficient and secure recoverable data aggregation scheme for heterogeneous wireless sensor networks. J Parallel Distrib Comput 111(C):1–12. https://doi.org/10.1016/j.jpdc.2017.06.019

    Article  Google Scholar 

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  1. Horacio Paggi

    Present address: ETS de Ingenieros Informáticos, Universidad Politécnica de Madrid, Campus de Montegancedo, 28660, Boadilla del Monte (Madrid), Spain

Authors and Affiliations

  1. ETS de Ingenieros Informáticos, Universidad Politécnica de Madrid, Campus de Montegancedo, 28660, Boadilla del Monte (Madrid), Spain

    Javier Soriano

  2. Universidad a Distancia de Madrid (UDIMA), Carretera de La Coruña, KM. 38,500 Vía de Servicio, no 15 28400 Collado Villalba, Madrid, Spain

    Juan A. Lara

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  1. Horacio Paggi
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Correspondence to Horacio Paggi.

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Paggi, H., Lara, J.A. & Soriano, J. Structures generated in a multiagent system performing information fusion in peer-to-peer resource-constrained networks. Neural Comput & Applic 32, 16367–16385 (2020). https://doi.org/10.1007/s00521-018-3818-1

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