Journal of Network and Systems Management

, Volume 23, Issue 3, pp 753–793 | Cite as

Federating Policy-Driven Autonomous Systems: Interaction Specification and Management Patterns

  • Alberto Schaeffer-FilhoEmail author
  • Emil Lupu
  • Morris Sloman


Ubiquitous systems and applications involve interactions between multiple autonomous entities—for example, robots in a mobile ad-hoc network collaborating to achieve a goal, communications between teams of emergency workers involved in disaster relief operations or interactions between patients’ and healthcare workers’ mobile devices. We have previously proposed the Self-Managed Cell (SMC) as an architectural pattern for managing autonomous ubiquitous systems that comprise both hardware and software components and that implement policy-based adaptation strategies. We have also shown how basic management interactions between autonomous SMCs can be realised through exchanges of notifications and policies, to effectively program management and context-aware adaptations. We present here how autonomous SMCs can be composed and federated into complex structures through the systematic composition of interaction patterns. By composing simpler abstractions as building blocks of more complex interactions it is possible to leverage commonalities across the structural, control and communication views to manage a broad variety of composite autonomous systems including peer-to-peer collaborations, federations and aggregations with varying degrees of devolution of control. Although the approach is more broadly applicable, we focus on systems where declarative policies are used to specify adaptation and on context-aware ubiquitous systems that present some degree of autonomy in the physical world, such as body sensor networks and autonomous vehicles. Finally, we present a formalisation of our model that allows a rigorous verification of the properties satisfied by the SMC interactions before policies are deployed in physical devices.


Network management Adaptive policy Federation  Autonomic Architectural pattern 



This work was partly funded by the UK Engineering and Physical Sciences Research Council through Grant GR/S68040/01; the International Technology Alliance sponsored by the U.S. Army Research Laboratory and the U.K. Ministry of Defence under Agreement Number W911NF-06-3-0001; and the EC IST EMANICS Network of Excellence (#26854).


  1. 1.
    Lupu, E., Dulay, N., Sloman, M., Sventek, J., Heeps, S., Strowes, S., Twidle, K., Keoh, S.-L., Schaeffer-Filho, A.: AMUSE: autonomic management of ubiquitous systems for e-health. Concurr Comput Pract Exp 20(3), 277–295 (2008)CrossRefGoogle Scholar
  2. 2.
    IBM: An architectural blueprint for autonomic computing, 3rd edn. Tech. rep., IBM (2005)Google Scholar
  3. 3.
    Sloman, M., Lupu, E.: Engineering policy-based ubiquitous systems. Comput. J. 53(7), 1113–1127 (2010). doi: 10.1093/comjnl/bxp102 CrossRefGoogle Scholar
  4. 4.
    Asmare, E., Gopalan, A., Sloman, M., Dulay, N., Lupu, E.: Self-management framework for mobile autonomous systems. J. Netw. Syst. Manag. 20, 244–275 (2012). doi: 10.1007/s10922-011-9201-5 CrossRefGoogle Scholar
  5. 5.
    Schaeffer-Filho, A., Lupu, E., Dulay, N., Keoh, S.-L., Twidle, K., Sloman, M., Heeps, S., Strowes, S., Sventek, J.: Towards supporting interactions between self-managed cells. In: Proceedings of the 1st international conference on self-adaptive and self-organizing systems (SASO), IEEE Computer Society, Boston, USA, pp. 224–233 (2007)Google Scholar
  6. 6.
    Schaeffer-Filho, A., Lupu, E., Sloman, M.: Realising management and composition of self-managed cells in pervasive healthcare, in: Pervasive computing technologies for healthcare, 2009. PervasiveHealth 2009. 3rd international conference, pp. 1–8 (2009). doi: 10.4108/ICST.PERVASIVEHEALTH2009.5979
  7. 7.
    Schaeffer-Filho, A., Lupu, E., Sloman, M., Eisenbach, S.: Verification of policy-based self-managed cell interactions using alloy. In: Proceedings of the 10th IEEE international conference on policies for distributed systems and networks, POLICY’09, IEEE Press, Piscataway, NJ, USA, pp. 37–40 (2009). URL:
  8. 8.
    Ma, J., Russo, A., Broda, K., Clark, K.: Dare: a system for distributed abductive reasoning. Auton. Agent. Multi Agent Syst. 16(3), 271–297 (2008). doi: 10.1007/s10458-008-9028-y CrossRefGoogle Scholar
  9. 9.
    Hwang, C., Talipov, E., Cha, H.: Distributed geographic service discovery for mobile sensor networks. Comput. Netw. 55(5), 1069–1082 (2011). doi: 10.1016/j.comnet.2010.09.015 CrossRefGoogle Scholar
  10. 10.
    Esposito, C., Cotroneo, D., Russo, S.: On reliability in publish/subscribe services. Comput. Netw. (2013). doi: 10.1016/j.comnet.2012.10.023
  11. 11.
    Schmidt, M.-T., Hutchison, B., Lambros, P., Phippen, R.: The enterprise service bus: making service-oriented architecture real. IBM Syst. J. 44(4), 781–797 (2005). doi: 10.1147/sj.444.0781 CrossRefGoogle Scholar
  12. 12.
    Singh, J., Eyers, D.M., Bacon, J.: Disclosure control in multi-domain publish/subscribe systems. In: Proceedings of the 5th ACM international conference on Distributed event-based system, DEBS ’11, ACM, New York, NY, USA, pp. 159–170 (2011). doi: 10.1145/2002259.2002283
  13. 13.
    Zhu, Y., Keoh, S.L., Sloman, M., Lupu, E.: A lightweight policy system for body sensor networks. IEEE Trans. Netw. Serv. Manag. 6(3), 137–148 (2009)CrossRefGoogle Scholar
  14. 14.
    Keoh, S.-L., Lupu, E., Sloman, M.: Securing body sensor networks: sensor association and key management. In: Proceedings of the IEEE international conference on pervasive computing and communications, IEEE Computer Society, Los Alamitos, CA, USA, pp. 1–6 (2009). doi: 10.1109/PERCOM.2009.4912756
  15. 15.
    Craven, R., Lobo, J., Lupu, E., Russo, A., Sloman, M.: Policy refinement: Decomposition and operationalization for dynamic domains. In: 7th international conference on network and service management (CNSM). IEEE, pp. 1–9 (2011)Google Scholar
  16. 16.
    Corapi, D., Ray, O., Russo, A., Bandara, A., Lupu, E.: Learning rules from user behaviour., In: Artificial intelligence applications and innovations III, ser. IFIP international federation for information processing, Iliadis, Maglogiann, Tsoumakasis, Vlahavas, and Bramer, Eds. Springer, US, vol 296, pp. 459–468 (2009)Google Scholar
  17. 17.
    Ma, J., Broda, K., Russo, A., Lupu, E.: Distributed abductive reasoning with constraints. In: Omicini, A., Sardina, S., Vasconcelos, W. (eds.) Declarative agent languages and technologies VIII ser. Lecture Notes in Computer Science, vol. 6619. Springer, Berlin, pp. 148–166 (2011). [Online]. doi: 10.1007/978-3-642-20715-0_9
  18. 18.
    Charalambides, M., Flegkas, P., Pavlou, G., Rubio-Loyola, J., Bandara, A., Lupu, E., Russo, A., Dulay, N., Sloman, M.: Policy conflict analysis for diffserv quality of service management. IEEE Trans. Netw. Serv. Manag. 6(1), 15–30 (2009)CrossRefGoogle Scholar
  19. 19.
    Stal, M.: Web services: beyond component-based computing. Commun. ACM 45(10), 71–76 (2002). doi: 10.1145/570907.570934 CrossRefGoogle Scholar
  20. 20.
    Meyer, B.: Applying ”design by contract“. Computer 25(10), 40–51 (1992). doi: 10.1109/2.161279 CrossRefGoogle Scholar
  21. 21.
    Gamma, E., Helm, R., Johnson, R., Vlissides, J.M.: Design Patterns: Elements of Reusable Object-Oriented Software. Professional Computing Series, 1st edn. Addison-Wesley, Boston (1995) Google Scholar
  22. 22.
    Taylor, R.N., Medvidovi, N., Dashofy, I.E.: Software Architecture: Foundations, Theory, and Practice. Wiley, Hoboken (2009)CrossRefGoogle Scholar
  23. 23.
    Salah, S., Macia-Fernandez, G., Diaz-Verdejo, J.E.: A model-based survey of alert correlation techniques. Comput. Netw. (2013). doi: 10.1016/j.comnet.2012.10.022
  24. 24.
    Cinque, M., Martino, C.D., Esposito, C.: On data dissemination for large-scale complex critical infrastructures. Comput. Netw. 56(4), 1215–1235 (2012). doi: 10.1016/j.comnet.2011.11.016 CrossRefGoogle Scholar
  25. 25.
    Schaeffer-Filho, A.: Supporting management interaction and composition of self-managed cells, Ph.D. thesis, Imperial College London, London, UK (2009)Google Scholar
  26. 26.
    Jackson, D.: Alloy: a lightweight object modelling notation. ACM Trans. Softw. Eng. Methodol 11(2), 256–290 (2002). doi: 10.1145/505145.505149 CrossRefGoogle Scholar
  27. 27.
    Jackson, D.: Software Abstractions: Logic, Language, and Analysis. The MIT Press, Cambridge (2006)Google Scholar
  28. 28.
    Milner, R., Parrow, J., Walker, D.: A calculus of mobile processes, I. Inf. Comput. 100(1), 1–40 (1992). doi: 10.1016/0890-5401(92)90008-4 zbMATHMathSciNetCrossRefGoogle Scholar
  29. 29.
    Cardelli, L., Gordon, A.D.: Mobile ambients. In: Proceedings of the 1st international conference on foundations of software science and computation structure (FoSSaCS), Springer, London, UK, pp. 140–155 (1998)Google Scholar
  30. 30.
    Phillips, A.: Specifying and implementing secure mobile applications in the channel ambient system, Ph.D. thesis, Imperial College London (2006)Google Scholar
  31. 31.
    Spivey, J.M.: The Z Notation: A Reference Manual. Prentice-Hall, Inc., Upper Saddle River (1989)zbMATHGoogle Scholar
  32. 32.
    Bjørner, D., Jones, C.B. (eds.): The Vienna Development Method: The Meta-Language. Springer, London (1978)zbMATHGoogle Scholar
  33. 33.
    Lano, K.: The B Language and Method: A Guide to Practical Formal Development, 1st edn. Springer, Secaucus (1996)CrossRefGoogle Scholar
  34. 34.
    Smaragdakis, Y., Batory, D.: Mixin layers: an object-oriented implementation technique for refinements and collaboration-based designs. ACM Trans. Softw. Eng. Methodol. 11(2), 215–255 (2002). doi: 10.1145/505145.505148 CrossRefGoogle Scholar
  35. 35.
    Sanchez-Loro, X., Ferrer, J.L., Gomez, C., Casademont, J., Paradells, J.: Can future internet be based on constrained networks design principles? Comput. Netw. 55(4):893–909, special Issue on Architectures and Protocols for the Future Internet (2011). doi: 10.1016/j.comnet.2010.12.018
  36. 36.
    Sanchez-Loro, X., Gonzalez, A., Martin-De-Pozuelo, R.: A semantic context-aware network architecture. In: Future Network and Mobile Summit, Florence, pp. 1–9. IEEE (2010)Google Scholar
  37. 37.
    Martin, D., Volker, L., Zitterbart, M.: A flexible framework for future internet design, assessment, and operation. Comput. Netw. 55(4):910–918, special Issue on Architectures and Protocols for the Future Internet (2011). doi: 10.1016/j.comnet.2010.12.015
  38. 38.
    Sifalakis, M., Louca, A., Bouabene, G., Fry, M., Mauthe, A., Hutchison, D.: Functional composition in future networks. Comput. Netw. 55(4):987–998, special Issue on Architectures and Protocols for the Future Internet (2011). doi: 10.1016/j.comnet.2010.12.006
  39. 39.
    Hilaire, V., Koukam, A., Rodriguez, S.: An adaptative agent architecture for holonic multi-agent systems. ACM Trans. Auton. Adapt. Syst. 3(1), 1–24 (2008). doi: 10.1145/1342171.1342173 CrossRefGoogle Scholar
  40. 40.
    Zambonelli, F., Jennings, N.R., Wooldridge, M.: Developing multiagent systems: the Gaia methodology. ACM Trans. Softw. Eng. Methodol. 12(3), 317–370 (2003). doi: 10.1145/958961.958963 CrossRefGoogle Scholar
  41. 41.
    Cabri, G., Puviani, M., Zambonelli, F.: Towards a taxonomy of adaptive agent-based collaboration patterns for autonomic service ensembles. In: Collaboration technologies and systems (CTS), 2011 international conference, pp. 508–515 (2011). doi: 10.1109/CTS.2011.5928730
  42. 42.
    Cernuzzi, L., Molesini, A., Omicini, A., Zambonelli, F.: Adaptable multi-agent systems: the case of the gaia methodology. Int. J. Softw. Eng. Knowl. Eng. 21(04), 491–521 (2011). doi: 10.1142/S0218194011005384 CrossRefGoogle Scholar
  43. 43.
    Gregory, A.F., Biegel, G., Clarke, S., Cahill, V.: Towards a sentient object model. In: Workshop on engineering context-aware object oriented systems and environments (ECOOSE’2002) (2002)Google Scholar
  44. 44.
    Veríssimo, P., Cahill, V., Casimiro, A., Cheverst, K., Friday, A., Kaiser, J.: Cortex: towards supporting autonomous and cooperating sentient entities. In: Proceedings of European wireless 2002, Florence, Italy, pp. 595–601 (2002)Google Scholar
  45. 45.
    Holzer, A., Eugster, P., Garbinato, B.: Alps–adaptive location-based publish/subscribe. Comput. Netw. 56(12), 2949–2962 (2012). doi: 10.1016/j.comnet.2012.05.007 CrossRefGoogle Scholar
  46. 46.
    Kim, J.S., Garlan, D.: Analyzing architectural styles. J. Syst. Softw. 83(7), 1216–1235 (2010). doi: 10.1016/j.jss.2010.01.049 CrossRefGoogle Scholar
  47. 47.
    Medvidovic, N., Tajalli, H., Garcia, J., Krka, I., Brun, Y., Edwards, G.: Engineering heterogeneous robotics systems: a software architecture-based approach. Computer 44(5), 62–71 (2011). doi: 10.1109/MC.2010.368 CrossRefGoogle Scholar
  48. 48.
    Martin, R.C.: Agile Software Development: Principles, Patterns, and Practices. Prentice-Hall, Upper Saddle River (2002)Google Scholar
  49. 49.
    Liskov, B.H., Wing, J.M.: A behavioral notion of subtyping. ACM Trans. Progr. Lang. Syst. 16(6), 1811–1841 (1994). doi: 10.1145/197320.197383 CrossRefGoogle Scholar
  50. 50.
    Martin RC (2000) The open-closed principle. Cambridge University Press, New York, pp 97–112. URL
  51. 51.
    Lee, S., Wong, T., Kim, H.S.: Improving manageability through reorganization of routing-policy configurations. Comput. Netw. 56(14), 3192–3205 (2012). doi: 10.1016/j.comnet.2012.06.014 CrossRefGoogle Scholar
  52. 52.
    Lee, S., Wong, T., Kim, H.: Improving dependability of network configuration through policy classification. In: Dependable systems and networks with FTCS and DCC, 2008. DSN 2008. IEEE international conference, pp. 297–306 (2008). doi: 10.1109/DSN.2008.4630098
  53. 53.
    SEAMS ’13: Proceedings of the 8th international symposium on software engineering for adaptive and self-managing systems. IEEE Press, Piscataway (2013)Google Scholar
  54. 54.
    Schaeffer-Filho, A., Smith, P., Mauthe, A., Hutchison, D., Yu, Y., Fry, M.: A framework for the design and evaluation of network resilience management. In: Proceedings of the 13th IEEE/IFIP network operations and management symposium (NOMS 2012), IEEE Computer Society, Maui, Hawaii, USA, pp. 401–408 (2012)Google Scholar
  55. 55.
    Schaeffer-Filho, A., Smith, P., Mauthe, A., Hutchison, D.: Network resilience with reusable management patterns. IEEE Commun. Mag. 52(7) (2014)Google Scholar
  56. 56.
    Zhou, Y., Fang, Y., Zhang, Y.: Securing wireless sensor networks: a survey. IEEE Commun. Surv. Tutor. 10(3), 6–28 (2008). doi: 10.1109/COMST.2008.4625802 CrossRefGoogle Scholar
  57. 57.
    Sterbenz, J.P., Hutchison, D., Cetinkaya, E.K., Jabbar, A., Rohrer, J.P., Scholler, M., Smith, P.: Resilience and survivability in communication networks: strategies, principles, and survey of disciplines. Comput. Netw. 54(8):1245–1265, resilient and Survivable networks (2010). doi: 10.1016/j.comnet.2010.03.005
  58. 58.
    Chen, X., Makki, K., Yen, K., Pissinou, N.: Sensor network security: a survey. IEEE Commun. Surv. Tutor. 11(2), 52–73 (2009). doi: 10.1109/SURV.2009.090205 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Alberto Schaeffer-Filho
    • 1
    Email author
  • Emil Lupu
    • 2
  • Morris Sloman
    • 2
  1. 1.Institute of InformaticsFederal University of Rio Grande do SulPorto AlegreBrazil
  2. 2.Department of ComputingImperial College LondonLondonUK

Personalised recommendations