1 / 17

Architecture-Driven Self-Adaptation and Self-Management in Robotics Systems

Architecture-Driven Self-Adaptation and Self-Management in Robotics Systems. By George Edwards, Joshua Garcia, Farshad Tajalli, Daniel Popescu, Nenad Medvidovic, Gaurav Sukhatme, Brad Petrus. Presentation by Joshua Garcia and Farshad Tajalli. Today’s Software Systems. 24/7 systems

kyrene
Download Presentation

Architecture-Driven Self-Adaptation and Self-Management in Robotics Systems

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Architecture-Driven Self-Adaptation and Self-Management in Robotics Systems By George Edwards, Joshua Garcia, Farshad Tajalli, Daniel Popescu, Nenad Medvidovic, Gaurav Sukhatme, Brad Petrus Presentation by Joshua Garcia and Farshad Tajalli

  2. Today’s Software Systems • 24/7 systems • Long-lived, decentralized, heterogeneous, mobile, ubiquitous Self-awareness and Self-adaptation

  3. Software Architecture for Robotics Self-awareness and Self-adaptation J. Georgas and R. Taylor. Policy-based self-adaptive architectures: a feasibility study in the robotics domain. In Proceedings of SEAMS 2008, pages 105–112. ACM New York, NY, USA, 2008. D. Sykes et al. From goals to components: a combined approach to self-management. In Proceedings of SEAMS 2008, pages 1–8. ACM New York, NY, USA, 2008. D. Kim et al. SHAGE: a framework for self-managed robot software. In Proceedings of SEAMS 2006, pages 79–85. ACM New York, NY, USA, 2006.

  4. Layered Architecture

  5. Approach • Layered Architecture • Component-based Approach • Meta-level Components vs. Application Components • Meta-level Component Types • Collector, Analyzer, Admin • Meta-level Component Layering • Meta-level components form a control loop on the lower level architecture • Implementation Support for Meta-level component types and layers

  6. Approach Advantages • Architectural Awareness • Architectural awareness of components in the layer below • Self-adaptation support for meta-level component types • Self-adaptation support for qualities of service • Support for Adaptive Reference Architectures

  7. Meta-Level Components • Meta-Level Components Types • Collector • Analyzer • Admin

  8. Collector • Read access to lower architecture • A collection of Monitors • added to the Components and Connectors in the lower layer • exceptions, variables and events • Collector aggregates the monitored data • Flexibility of monitor installation

  9. Analyzer • Read access to lower architecture • A collection of Policies • Policies are evaluated against monitored data received from Collectors • Triggers adaptations and reconfigurations • Directs Admins to modify the lower architecture

  10. Admin • Read\Write access to lower architecture • Adapts the lower architecture • Add, delete, connect, disconnect • Reconfigures the lower architecture components, connectors and etc.

  11. Layered Architecture

  12. Fault Tolerance Example

  13. Implementation Support – Prism-MW • Meta-level component type adaptation • Robotics-specific meta-level component types Meta-level Component

  14. Three Layer Reference Model

  15. Application to Three Layer Reference Model

  16. Application Scenario

  17. Conclusion • Meta-level component types and layering • Support for qualities of service • Ensures correct functionality and system stability • Implementation support for meta-level component types and layers • Support for adaptive reference architectures

More Related