Skip to main content

QoS management for dependable sensory environments

Abstract

Sensory environments for healthcare are commonplace nowadays. A patient monitoring system in such an environment deals with sensor data capture, transmission and processing in order to provide on-the-spot support for monitoring the vulnerable and critical patients. A fault in such a system can be hazardous on the health of the patient. Therefore, such a system must be dependable and ensure reliability, fault-tolerance, safety and other critical aspects, in order to deploy it in real scenario. Also, the management of the infrastructure resources must be efficient and the eventual system reconfiguration must be reliably performed. This paper encounters some of these issues and proposes a component platform with specific support for several QoS aspects, namely fault tolerance, safe inter-component communication and resource management. The platform adopts the Service Component Architecture (SCA) model and defines a Data Distribution Service (DDS) binding, which provides the fault tolerance and the required safety-ensuring techniques and measures, as defined in the IEC 61784-3-3 standard. As a proof of concept, a distributed home care application that improves the medical assistance in case of fire detection is presented.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

References

  1. (2007) “IEC 61784-3-3: industrial communication networks - Profiles - Part 3-3: functional safety fieldbuses - Additional specifications for CFP 3,” ed: IEC

  2. Agirre A, Estévez E, Marcos M (2011) QoS enabled application management platform over DDS, presented at the Proceedings of the Middleware Workshop on Posters and Demos Track, Lisbon, Portugal

  3. Agirre A, Estévez E, Marcos M (2012) Fault tolerant component management platform over Data Distribution Service, In: 1st IFAC Conference on Embedded Systems, Computational Intelligence and Telematics in Control (CESCIT), Wurzburg, pp. 218-223

  4. Agirre A, Estevez E, Marcos M (2014) Resource management support for SCA based distributed applications, presented at the ETFA 2014

  5. Agirre A, Marcos M, Estevez E (2012) Distributed applications management platform based on service component architecture, In: Emerging Technologies & Factory Automation (ETFA), 2012 I.E. 17th Conference on, pp. 1-4

  6. Agirre A, Parra J, Estevez E, Marcos M (2014) QoS aware platform for dependable sensory environments, In: Multimedia and Expo Workshops (ICMEW), 2014 I.E. International Conference on, pp. 1-5

  7. Agirre A, Perez J, Priego R, Marcos M, Estevez E (2013) SCA extensions to support safety critical distributed embedded systems, In: Emerging Technologies & Factory Automation (ETFA), 2013 I.E. 18th Conference on, pp. 1-4

  8. Almeida L, Fischmeister S, Anand M, Lee I (2007) “A dynamic scheduling approach to designing flexible safety-critical systems,” presented at the Proceedings of the 7th ACM & IEEE international conference on Embedded software, Salzburg, Austria

  9. Apache Tuscany. Available: http://tuscany.apache.org/

  10. Audsley N, Burns A, Richardson M, Tindell K, Wellings AJ (1993) Applying new scheduling theory to static priority pre-emptive scheduling. Softw Eng J 8:284–292

    Article  Google Scholar 

  11. Autosar website. Available: http://www.autosar.org/

  12. Bruyninckx H, Soetens P, Koninckx B (2003) The real-time motion control core of the OROCOS project, pp. 2766-2771

  13. Buttazzo GC, Lipari G, Caccamo M, Abeni L (2002) Elastic scheduling for flexible workload management. Comput IEEE Trans 51:289–302

    Article  Google Scholar 

  14. Chan M, Estève D, Escriba C, Campo E (2008) A review of smart homes—Present state and future challenges, Computer Methods and Programs in Biomedicine, vol. 91, pp. 55-81, 7//

  15. Chen IY, Huang CC (2005) A service-oriented agent architecture to support telecardiology services on demand. J Med Biol Eng 25:73–79

    Google Scholar 

  16. Consortium TO (2004) “The fractal component model specification,” ed

  17. Cook DJ, Augusto JC, Jakkula VR (2009) Ambient intelligence: technologies, applications, and opportunities, Pervasive and Mobile Computing, vol. 5, pp. 277-298, 8//

  18. Crnkovic I, Sentilles S, Vulgarakis A, Chaudron MRV (2011) A classification framework for software component models. Softw Eng IEEE Trans 37:593–615

    Article  Google Scholar 

  19. D’Mello DA, Ananthanarayana VS (2010) Dynamic selection mechanism for quality of service aware web services. Enterp Inf Syst 4:23–60

    Article  Google Scholar 

  20. Holborn PG, Nolan PF, Golt J (2003) An analysis of fatal unintentional dwelling fires investigated by London Fire Brigade between 1996 and 2000, Fire Safety J, vol. 38, pp. 1-42, 2//

  21. IEC (2004/2005) “IEC 61499: Function blocks for industrial process measurement and control systems, Parts 1 - 4,” ed

  22. Ji Eun K, Rogalla O, Kramer S, Hamann A (2009) Extracting, specifying and predicting software system properties in component based real-time embedded software development, In: Software Engineering - Companion Volume, 2009. ICSE-Companion 2009. 31st International Conference on, pp. 28-38

  23. Joseph M, Pandya P (1986) Finding response times in a real-time system. Comput J 29:390–395

    MathSciNet  Article  Google Scholar 

  24. Laws S, Combellack M, Feng R, Mahbod H, Nash S (2011) Tuscany SCA in Action

  25. Liu CL, Layland JW (1973) Scheduling algorithms for multiprogramming in a hard-real-time environment. J ACM 20:46–61

    MathSciNet  Article  MATH  Google Scholar 

  26. Luck H (1997) Remarks on the state of the art in automatic fire detection, Fire Safety J, vol. 29, pp. 77-85, 9//

  27. Malohlava M, Hnetynka P, Bures T (2013) SOFA 2 Component Framework and Its Ecosystem, Electronic Notes in Theoretical Computer Science, vol. 295, pp. 101-106, 5/9/

  28. Marcos M, Estévez E, Jouvray C, Kung A (2011) An Approach to use MDE in Dynamically Reconfigurable Networked Embedded SOAs, presented at the 18th IFAC World Congress, Milano, Italy

  29. Mohagheghi P (2004) The impact of software reuse and incremental development on the quality of large systems, PhD, Department of Computer and Information Science Norwegian University of Science and Technology

  30. Mori M, Li F, Dorn C, Inverardi P, Dustdar S (2011) Leveraging state-based user preferences in context-aware reconfigurations for self-adaptive systems,“ vol. 7041 LNCS, ed, pp. 286-301

  31. Nehmer J, Becker M, Karshmer A, Lamm R (2006) Living assistance systems: an ambient intelligence approach, presented at the Proceedings of the 28th international conference on Software engineering, Shanghai, China

  32. OASIS (2007) “Service Component Architecture,” ed

  33. OASIS (2011) “Service component architecture assembly model specification version 1.1,” ed

  34. OASIS (2011) “SCA Policy Framework Version 1.1,” ed

  35. OMG (2007) “Data Distribution Service for Real-time Systems v1.2,” ed

  36. OMG (2007) “Data distribution service for real-time systems v1.2,” ed

  37. Pedreiras P, Almeida L (2003) “The Flexible Time-Triggered (FTT) Paradigm: An Approach to QoS Management in Distributed Real-Time Systems,” presented at the Proceedings of the 17th International Symposium on Parallel and Distributed Processing

  38. Pedreiras P, Gai P, Almeida L, Buttazzo GC (2005) FTT-ethernet: a flexible real-time communication protocol that supports dynamic QoS management on ethernet-based systems. IEEE Trans Ind Inform 1:162–172

    Article  Google Scholar 

  39. Plsek A, Loiret F, Merle P, Seinturier L (2008) A component framework for java-based real-time embedded systems, presented at the Proceedings of the 9th ACM/IFIP/USENIX International Conference on Middleware, Leuven, Belgium

  40. Pop T, Hnětynka P, Hošek P, Malohlava M, Bureš T (2013) Comparison of component frameworks for real-time embedded systems, Knowledge and Information Systems, pp. 1-44, 2013/04/02

  41. Poza JL, Posadas JL, Simó JE (2009) QoS-based middleware architecture for distributed control systems, vol. 50, Corchado JM, Rodriguez S, Llinas J, Molina JM, Eds., ed, pp. 587-595

  42. Rekik R, Hasnaoui S (2009) “Application of a CAN BUS transport for DDS middleware,” in 2nd International Conference on the Applications of Digital Information and Web Technologies, ICADIWT 2009, London, pp. 766-771

  43. Richter S, Wahler M, Kumar A (2011) A framework for component-based real-time control applications, In: 13th Real-Time Linux Workshop, Prague, Czech Republic, Prague

  44. Roldán JMD, Cia TG, Bermúdez RM (1999) “El paciente quemado grave,” In: Principios de Urgencias, Emergencias y Cuidados Críticos, ed: Alhulia SL, p. 1570

  45. Seinturier L, Merle P, Fournier D, Dolet N, Schiavoni V, Stefani JB (2009) “Reconfigurable SCA Applications with the FraSCAti Platform,” In: Services Computing, 2009. SCC '09. IEEE International Conference on, pp. 268-275

  46. Seinturier L, Merle P, Rouvoy R, Romero D, Schiavoni V, Stefani J-B (2011) A component-based middleware platform for reconfigurable service-oriented architectures, Software: practice and experience, pp. n/a-n/a

  47. Shirazi B, Kumar M, Sung BY (2004) QoS middleware support for pervasive computing applications, In: System Sciences, 2004. Proceedings of the 37th Annual Hawaii International Conference on, p. 10 pp

  48. Silva LCD, Morikawa C, Petra IM (2012) State of the art of smart homes. Eng Appl Artif Intell 25:1313–1321

    Article  Google Scholar 

  49. Strasser T, Rooker M, Ebenhofer G, Zoitl A, Sunder C, Valentini A et al. (2008) Framework for Distributed Industrial Automation and Control (4DIAC), In: Industrial Informatics, 2008. INDIN 2008. 6th IEEE International Conference on, pp. 283-288

  50. Strunk A (2010) QoS-aware service composition: a survey, In: 8th European Conference on Web Services, ECOWS 2010, Ayia Napa, pp. 67-74

  51. Wegdam M (2003) Dynamic reconfiguration and load distribution in component middleware. University of Twente, Enschede

    Google Scholar 

  52. Yang H, Kim M, Karenos K, Ye F, Lei H (2009) Message-oriented middleware with QoS awareness, vol. 5900 LNCS, ed. Stockholm, pp. 331-345

Download references

Acknowledgments

This work was financed in part by the University of the Basque Country (UPV/EHU) under project UFI 11/28, by the Regional Government of the Basque Country under Project IT719-13, and by the MCYT&FEDER under project DPI 2012-37806-C02-01. Also, the authors would like to extend their sincere appreciation to the Deanship of Scientific Research at King Saud University for its funding of this International Research Group (IRG14-28).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jorge Parra.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Agirre, A., Parra, J., Armentia, A. et al. QoS management for dependable sensory environments. Multimed Tools Appl 75, 13397–13419 (2016). https://doi.org/10.1007/s11042-015-2781-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-015-2781-4

Keywords

  • Quality of service
  • Service component architecture
  • Data distribution service
  • Fault tolerance
  • Safety