1. 1 Component-Based Dynamic QoS Adaptation Praveen Sharma, George Heinman, Joseph Loyall, Prakash Manghwani, Matthew Gillen, Jianming Ye, Krishnakumar Balasubramanian TAO Workshop July 16, 2004

2. 2 Overview UAV-OEP/Capstone Demo – PCES Objective: Operational Capabilities and Technical Story Demo Architecture and End-to-End QoS Management Constituent Technologies in the Demo –CIAO Components –Qosket Components Empirical Evaluation based on CCMPerf Modeling and Synthesis Summary Publications

3. 3 UAV-OEP/Capstone Demo –PCES Objective: Operational Capabilities: Time critical target engagement, Combined USAF and Army operations Technical Story: Dynamic end-to-end mission-driven QoS management,Software engineering of DRE systems

4. 4 Demonstration Architecture SimUCAV SimUAVSimC2Army FEC

5. 5 System resource manager determines allocation of resources to participants and roles Assigns a weight to each role based on its relative importance (from the blue controller) Divides the total amount of resources (e.g., Mbps or %CPU) by the number of participants in all roles multiplied by their weight to get a resource unit Each participant is allocated a resource unit times the weight of its role System resource manager pushes policy to each participant (SimUAVs and SimUCAVs) Role Relative importance Resource allocation Min and Max allowed (from mission requirements) Local resource manager determines how best to utilize allocated resources Diffserv Code Point (based on relative importance of role) CPU reservation Shaping data to fit allocated CPU and bandwidth: rate, size (cropping or scale), compression Chooses based on resource allocation and mission needs of the role Local resource manager configures qoskets to enforce resource management Qoskets control resources and shape imagery Diffserv Code Point CPU reservation Rate, compression level, amount to scale or crop Dynamic End-to-End QoS Management

6. 6 Constituent Technologies (1/2) Component-based middleware –CIAO components –Functional components SimUAV sender, SimUAV receiver –Qosket components CPU reservation (CPU broker Qosket) Network priority (Diffserv Qosket) Application/Data management –Image compression –Rate shaping and pacing –Scaling –Cropping

7. 7 Functional Components Qosket Components QoS Management Components Constituent Technologies (2/2) Multi-layer QoS management – System resource manager – Local resource manager Modeling and synthesis using DQME, CADML

8. 8 Presented at CBSE 7 We prototyped this one in the QuO software – Works with existing assembly tools – Allows QoS to be distributed where needed – The assembly of Qoskets can run in a single component server unless necessitated by application to run otherwise – Are general QoS provisioning components, i.e., can be reused with any other application with minimum changes – Implemented for CIAO and Prism and used in the Demo Approaches to encapsulating QoS behaviors as components Encapsulate QoS artifacts as components Encapsulate one QoS artifact for each component Create Specialized CCM container Encapsulate all QoS control into single, centralized controller Qosket Components

9. 9 This is the model we use in Demonstration 3, because it is more representative of a UAV pushing imagery Qosket Component Performance Based on CCMPerf Component version of the distributed UAV software includes –Functionality components (i.e., senders, distributors, receivers) –Qosket components Two alternatives for sending imagery using components –Event push, data pull (similar to the Prism model) –Event push with image payload Event push, Data pull Model Event push with image payload Event push data pullEvent with payload No qosket Qosket component; no adaptation Qosket component with scaling Insertion of an extra component added modest overhead –4.2% and 2.6%, respectively The adaptation provided by the qosket component more than makes up for the extra component overhead –Scaling the image reduces the latency by 33.5 – 37.8%

10. 10 Modeling and Synthesis: How We Constructed the Demonstration Modeling and Synthesis: How We Constructed the Demonstration Assembly of the system using CADML –Generated XML CAD file –Transitioning to use PICML End-to-end QoS using DQME –Used for documentation and design –Code generation work in progress Application of MoBIES tools Default Default Default imageEvt outgoing_Evt incoming_Evt imageEvt policyChangeEvent policy_evt incoming_Evt outgoing_Evt incoming_Evt outgoing_Evt incoming_Evt outgoing_Evt resourceAllocationEvt resource_evt scalingQosPredictor qosLevels scalingQosket currentLevelValue croppingQosket currentLevelValue compressionQosket currentLevelValue diffservQosket currentLevelValue compressionQosPredictor qosLevels croppingQosPredictor qosLevels CADML model (one SimUAV visible) CAD file (XML) DQME Modeling

11. 11 Publications Joseph Loyall, Jianming Ye, Sandeep Neema, and Nagabhushan Mahadevan. Model-Based Design of End-to-End Quality of Service in a Multi- UAV Surveillance and Target Tracking Application. Second RTAS Workshop on Model-Driven Embedded Systems (MoDES '04), Toronto, Canada, May 25- 28, 2004. George T. Heineman and William T. Councill, Component-Based Software Engineering: Putting the Pieces Together, Addison Wesley, June 2001. Jianming Ye, Joseph P. Loyall, Richard Shapiro, Sandeep Neema, N. Mahadevan, S. Abdelwahed, M. Koets,and W. Denise. A Model-Based Approach to Designing QoS Adaptive Applications. 2004. Submitted for publication. Praveen K. Sharma, Joseph P. Loyall, George T. Heineman, Richard E. Schantz, Richard Shapiro, Gary Duzan Component-Based Dynamic QoS Adaptations in Distributed Real-Time and Embedded Systems – submitted to DOA

12. 12 Summary We have developed a complex DRE application built using components –Functional components, Qosket components and QoS Management components to provide Dynamic end-to-end mission-driven QoS management Time critical target engagement Combined USAF and Army operations Components assembled using CADML, DQME Qosket Components –Key to end-to-end QoS Management –Combines CIAO and QuO technology Modeling Tools –Easy to assemble, reusable in different scenarios Minimal overhead for increased flexibility and control