Runtime models based on dynamic decision networks: enhancing the decision-making in the domain of ambient assisted living applications

Luis Hernan Garcia Paucar, Nelly Bencomo

Research output: Chapter in Book/Report/Conference proceedingConference publication

Abstract

Dynamic decision-making for self-Adaptive systems (SAS) requires the runtime trade-off of multiple non-functional requirements (NFRs) -Aka quality properties-And the costsbenefits analysis of the alternative solutions. Usually, it requires the specification of utility preferences for NFRs and decisionmaking strategies. Traditionally, these preferences have been defined at design-Time. In this paper we develop further our ideas on re-Assessment of NFRs preferences given new evidence found at runtime and using dynamic decision networks (DDNs) as the runtime abstractions. Our approach use conditional probabilities provided by DDNs, the concepts of Bayesian surprise and Primitive Cognitive Network Process (P-CNP), for the determination of the initial preferences. Specifically, we present a case study in the domain problem of ambient assisted living (AAL). Based on the collection of runtime evidence, our approach allows the identification of unknown situations at the design stage.

Original languageEnglish
Title of host publicationMRT 2016 - Models@run.time
Subtitle of host publicationProceedings of the 11th International Workshop on Models@run.time, co-located with 19th International Conference on Model Driven Engineering Languages and Systems (MoDELS 2016)
EditorsSebastian Götz, Nelly Bencomo, Kirstie Bellman, Gordon Blair
PublisherCEUR-WS.org
Pages9-17
Number of pages9
Publication statusPublished - 23 Nov 2016
Event11th international workshop on Models@run.time / 19th International Conference on Model Driven Engineering Languages and Systems - San Malo, France
Duration: 3 Oct 2016 → …

Publication series

NameCEUR workshop proceedings
Volume1742
ISSN (Print)1613-0073

Conference

Conference11th international workshop on Models@run.time / 19th International Conference on Model Driven Engineering Languages and Systems
Abbreviated titleMRT 2016 / MoDELS 2016
CountryFrance
CitySan Malo
Period3/10/16 → …

Bibliographical note

Pauca, LHG & Bencomo, N : Runtime models based on dynamic decision networks: enhancing the decision-making in the domain of ambient assisted living applications. Proc. of the 11th International Workshop on Models@run.time, co-located with the 19th International Conference on Model Driven Engineering Languages and Systems (MoDELS 2016), Saint Malo, France, 4 October, ceur-ws.org/Vol-1742/MRT16_paper_12.pdf

Keywords

  • AHP
  • decision making
  • non-functional requirements trade-off
  • P-CNP
  • self-adaptation
  • uncertainty information hypothesis

Fingerprint Dive into the research topics of 'Runtime models based on dynamic decision networks: enhancing the decision-making in the domain of ambient assisted living applications'. Together they form a unique fingerprint.

  • Research Output

    • 1 Conference contribution

    Summary of the 11th international workshop on Models@run.time

    Götz, S., Bencomo, N., Bellman, K. & Blair, G., 23 Nov 2016, MRT 2016 - Models@run.time: Proceedings of the 11th International Workshop on Models@run.time, co-located with 19th International Conference on Model Driven Engineering Languages and Systems (MoDELS 2016). Götz, S., Bencomo, N., Bellman, K. & Blair, G. (eds.). CEUR-WS.org, 3 p. (CEUR workshop proceedings; vol. 1742).

    Research output: Chapter in Book/Report/Conference proceedingConference publication

    Open Access
    File

    Cite this

    Garcia Paucar, L. H., & Bencomo, N. (2016). Runtime models based on dynamic decision networks: enhancing the decision-making in the domain of ambient assisted living applications. In S. Götz, N. Bencomo, K. Bellman, & G. Blair (Eds.), MRT 2016 - Models@run.time: Proceedings of the 11th International Workshop on Models@run.time, co-located with 19th International Conference on Model Driven Engineering Languages and Systems (MoDELS 2016) (pp. 9-17). (CEUR workshop proceedings; Vol. 1742). CEUR-WS.org.