Interaction Net as a Representation Model of a Programming Language

  • Joaquín F. SánchezEmail author
  • Jorge Quiñones
  • Juan Manuel Corredor
Part of the Studies in Computational Intelligence book series (SCI, volume 815)


The following article presents an answer in the design of future solutions for highly interconnected environments based on the construction of a programming language, this language is a computational realization of the concept of interactions that uses the mathematical model of Interaction Nets. The purpose is to expose how this model adequately represents the needs of future challenges in the design and implementation of ad hoc networks, which are the floor of decentralized systems and the IoT (Internet of Things). It shows the conception of specific interactions and how they are written in the created language. The results show some real applications and the behavior of the tool.


Ad hoc network Programming language Knowledge representation Decentralized network 


  1. 1.
    Jara, A.J., Olivieri, A.C., Bocchi, Y., Jung, M., Kastner, W., Skarmeta, A.F.: Semantic web of things: an analysis of the application semantics for the IoT moving towards the IoT convergence. Int. J. Web Grid Serv. 10(2–3), 244–272 (2014)CrossRefGoogle Scholar
  2. 2.
    Hitzler, P., Janowicz, K.: Semantic Web (2014)Google Scholar
  3. 3.
    W.W.W. Consortium: RDF 1.1 concepts and abstract syntax (2014)Google Scholar
  4. 4.
    Buranarach, M., Supnithi, T., Thein, Y.M., Ruangrajitpakorn, T., Rattanasawad, T., Wongpatikaseree, K., Lim, A.O., Tan, Y., Assawamakin, A.: OAM: an ontology application management framework for simplifying ontology-based semantic web application development. Int. J. Softw. Eng. Knowl. Eng. 26(1), 115–145 (2016)CrossRefGoogle Scholar
  5. 5.
    Horsman, D., Kendon, V., Stepney, S.: The natural science of computing. Commun. ACM 31–34. Scholar
  6. 6.
    Fitzek, F.H., Katz, M.D.: Mobile Clouds: Exploiting Distributed Resources in Wireless, Mobile and Social Networks. Wiley, New York (2013)Google Scholar
  7. 7.
    Brody, P., Pureswaran, V.: Device Democracy: Saving the Future of the Internet of Things. IBM (2014)Google Scholar
  8. 8.
    Chih-Lin, I., Rowell, C., Han, S., Xu, Z., Li, G., Pan, Z.: Toward green and soft: a 5G perspective. IEEE Commun. Mag. 52(2), 66–73 (2014)CrossRefGoogle Scholar
  9. 9.
    Conti, M., Giordano, S.: Mobile ad hoc networking: milestones, challenges, and new research directions. IEEE Commun. Mag. 52(1), 85–96 (2014)CrossRefGoogle Scholar
  10. 10.
    Trifunovic, S., Kouyoumdjieva, S.T., Distl, B., Pajevic, L., Karlsson, G., Plattner, B.: A decade of research in opportunistic networks: challenges, relevance, and future directions. IEEE Commun. Mag. 55(1), 168–173 (2017)CrossRefGoogle Scholar
  11. 11.
    Liu, X., Li, Z., Yang, P., Dong, Y.: Information-centric mobile ad hoc networks and content routing: a survey. Ad Hoc Netw. 58, 255–268 (2017)CrossRefGoogle Scholar
  12. 12.
    Dressler, F.: Self-organization in Ad hoc Networks: Overview and Classification, vol. 7, pp. 1–12. Department of Computer Science, University of Erlangen (2006)Google Scholar
  13. 13.
    Prehofer, C., Bettstetter, C.: Self-organization in communication networks: principles and design paradigms. IEEE Commun. Mag. 43(7), 78–85 (2005)CrossRefGoogle Scholar
  14. 14.
    Fernández, M.: Models of Computation: An Introduction to Computability Theory. Springer Science & Business Media (2009)Google Scholar
  15. 15.
    Perrinel, M.: On context semantics and interaction nets. In: Proceedings of the Joint Meeting of the Twenty-Third EACSL Annual Conference on Computer Science Logic (CSL) and the Twenty-Ninth Annual ACM/IEEE Symposium on Logic in Computer Science (LICS), p. 73. ACM (2014)Google Scholar
  16. 16.
    Dressler, F.: Self-Organization in Sensor and Actor Networks. Wiley, New York (2008)Google Scholar
  17. 17.
    Chandra, T.B., Dwivedi, A.K.: Programming languages for wireless sensor networks: a comparative study. In: 2nd International Conference on Computing for Sustainable Global Development (INDIACom), pp. 1702–1708. IEEE (2015)Google Scholar
  18. 18.
    Sugihara, R., Gupta, R.K.: Programming models for sensor networks: a survey. ACM Trans. Sens. Netw. (TOSN) 4(2), 8 (2008)Google Scholar
  19. 19.
    Hill, J., Szewczyk, R., Woo, A., Hollar, S., Culler, D., Pister, K.: System architecture directions for networked sensors. ACM SIGOPS Oper. Syst. Rev. 34(5), 93–104 (2000)CrossRefGoogle Scholar
  20. 20.
    Mottola, L., Picco, G.P.: Programming wireless sensor networks: fundamental concepts and state of the art. ACM Comput. Surv. (CSUR) 43(3), 19 (2011)CrossRefGoogle Scholar
  21. 21.
    Cheong, E., Liebman, J., Liu, J., Zhao, F.: TinyGALS: a programming model for event-driven embedded systems. In: Proceedings of the 2003 ACM Symposium on Applied Computing, pp. 698–704 (2003Google Scholar
  22. 22.
    Greenstein, B., Kohler, E., Estrin, D.: A sensor network application construction kit (SNACK). In: Proceedings of the 2nd International Conference on Embedded Networked Sensor Systems ACM, pp. 69–80 (2004)Google Scholar
  23. 23.
    Welsh, M., Mainland, G.: Programming sensor networks using abstract regions. NSDI 4, 3 (2004)Google Scholar
  24. 24.
    McCartney, W.P., Sridhar, N.: Abstractions for safe concurrent programming in networked embedded systems. In: Proceedings of the 4th International Conference on Embedded Networked Sensor Systems, pp. 167–180. ACM (2006)Google Scholar
  25. 25.
    Newton, R., Welsh, M., et al.: Building up to macroprogramming: an intermediate language for sensor networks. In: Proceedings of the 4th International Symposium on Information Processing in Sensor Networks, p. 6. IEEE Press (2005)Google Scholar
  26. 26.
    Yao, Y., Gehrke, J.: The cougar approach to in-network query processing in sensor networks. ACM Sigmod Rec. 31(3), 9–18 (2002)CrossRefGoogle Scholar
  27. 27.
    Madden, S., Franklin, M.J., Hellerstein, J.M., Hong, W.: The design of an acquisitional query processor for sensor networks. In: Proceedings of the 2003 ACM SIGMOD International Conference on Management of Data, pp. 491–502. ACM (2003)Google Scholar
  28. 28.
    Gummadi, R., Gnawali, O., Govindan, R.: Macro-programming wireless sensor networks using Kairos. In: International Conference on Distributed Computing in Sensor Systems, pp. 126–140. Springer (2005)Google Scholar
  29. 29.
    Fok, C.L., Roman, G.C., Lu, C.: Rapid development and flexible deployment of adaptive wireless sensor network applications. In: 25th IEEE International Conference on Distributed Computing Systems, Proceedings. ICDCS, pp. 653–662 (2005)Google Scholar
  30. 30.
    Fok, C.L., Roman, G.C., Lu, C.: Agilla: a mobile agent middleware for sensor networks (2006)Google Scholar
  31. 31.
    Li, S., Lin, Y., Son, S.H., Stankovic, J.A., Wei, Y.: Event detection services using data service middleware in distributed sensor networks. Telecommun. Syst. 26(2–4), 351–368 (2004)CrossRefGoogle Scholar
  32. 32.
    Loo, J., Mauri, J.L., Ortiz, J.H.: Mobile Ad hoc Networks: Current Status and Future Trends. CRC Press, New York (2016)CrossRefGoogle Scholar
  33. 33.
    Qiu, T., Chen, N., Li, K., Qiao, D., Fu, Z.: Heterogeneous ad hoc networks: architectures, advances and challenges. Ad Hoc Netw. 55, 143–152 (2017)CrossRefGoogle Scholar
  34. 34.
    Camp, T., Boleng, J., Davies, V.: A survey of mobility models for ad hoc network research. Wirel. Commun. Mob. Comput. 2(5), 483–502 (2002)CrossRefGoogle Scholar
  35. 35.
    Zhang, Y., Zheng, J., Chen, H.H.: Cognitive Radio Networks: Architectures, Protocols, and Standards. CRC Press, New York (2016)Google Scholar
  36. 36.
    Dressler, F.: Self-Organization in Sensor and Actor Networks. Wiley (2008)Google Scholar
  37. 37.
    Gershenson, C.: Design and control of self-organizing systems. CopIt ArXives (2007)Google Scholar
  38. 38.
    Yanmaz, E., Yahyanejad, S., Rinner, B., Hellwagner, H., Bettstetter, C.: Drone networks: communications, coordination, and sensing. Ad Hoc Netw. 68(1–15) (2018)CrossRefGoogle Scholar
  39. 39.
    Galati, A.: Delay Tolerant Network (2010)Google Scholar
  40. 40.
    Yang, K.: Principles Design and Applications (2014)Google Scholar
  41. 41.
    Dressler, F., Akan, O.B.: A survey on bio-inspired networking. Comput. Netw. 54(6), 881–900 (2010)CrossRefGoogle Scholar
  42. 42.
    Jones, A.J., Artikis, A., Pitt, J.: The design of intelligent socio-technical systems. Artif. Intell. Rev. 39(1), 5–20 (2013)CrossRefGoogle Scholar
  43. 43.
    Pureswaran, V., Brody, P.: Device Democracy: Saving the Future of the Internet of Things. IBM Corporation (2015)Google Scholar
  44. 44.
    Wortmann, F., Flüchter, K.: Internet of Things. Bus. Inf. Syst. Eng. 57(3), 221–224 (2015)CrossRefGoogle Scholar
  45. 45.
    Dell, P.F.: Family Process vol. 21, no. 1, p. 21 (1982)Google Scholar
  46. 46.
    Dawes, R.M.: Social dilemmas. Annu. Rev. Psychol. 31(1), 169–193 (1980)CrossRefGoogle Scholar
  47. 47.
    Kollock, P.: Social dilemmas: the anatomy of cooperation. Ann. Rev. Sociol. 24(1), 183–214 (1998)CrossRefGoogle Scholar
  48. 48.
    McMurray, J.: The paradox of information and voter turnout. Pub. Choice 165(1-2), 13–23 (2015)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Joaquín F. Sánchez
    • 1
    Email author
  • Jorge Quiñones
    • 1
  • Juan Manuel Corredor
    • 1
  1. 1.Faculty of Engineering, Department of Systems Engineering and IndustrialNational University of ColombiaBogotáColombia

Personalised recommendations