A Model-Driven Framework for Architectural Evaluation of Mobile Software Systems

1. A Model-Driven Framework for Architectural Evaluation of Mobile Software Systems George Edwards gedwards@usc.edu Dr. Nenad Medvidovic neno@usc.edu Center for Software Engineering University of Southern California

2. Project Overview • Motivation • Provide a “tailorable infrastructure” for evaluating, refining, and validating software architectures for mobile software systems. • Investigate the consequences of architectural decisions. • Weigh architectural trade-offs. • Validate the achievement of quality attributes. • Approach • Develop a software architecture modeling and simulation tool chain that leverages the Model-Driven Engineering (MDE) approach to system design. • Focus on concerns of particular relevance to mobile software systems. • Implement a mapping between architectural constructs and simulation constructs. • Modeling language based on xADL, an extensible architecture description language. • Simulators based on adevs, a discrete event simulation engine.

3. The Extensible Modeling and Simulation Toolchain • xADL extensionsare implemented as GME metamodels. • Define domain-specific modeling concepts, including elements, relationships, views, and constraints. • Software architecture modelsare created in GME. • Provides an intuitive mechanism for building complex models. • Automatically enforces the language rules. • Plug-insinterpret, transform and analyze architecture models. • Generate discrete-event simulations that provide data about a system’s run-time characteristics.

4. xADL Extensions • POWER • Includes computational and communication energy costs. • RELIABILITY • Includes failure probabilities and recovery times. • DATA • Includes data types and sizes. • BEHAVIOR • Includes tasks and states. PowerxADL Metamodel (includes Structure, Data, and Power extensions)

5. Example Model

6. The xADL-to-adevs Transformation • Transforming architecture models into discrete event simulations allows run-time properties to be observed and quantified. • Achieved via xADL-to-adevs mapping. • GME plug-ins implement the mapping and instrument the generated code to record the appropriate measurements.

7. Discrete Event Simulators • Latency • Requires Structure and Types, Data, and Behavior extensions. • Provides, for each required interface, the response time for each invocation. • Reliability • Requires Structure and Types, Data, Behavior, and Reliability extensions. • Provides the time and type of failures and the recovery time. • Power Consumption • Requires Structure and Types, Data, Behavior, and Power extensions. • Provides the energy consumption of each host (i.e., remaining battery power) over time.

8. Ongoing and Future Work • Improve accuracy of simulation measurements. • e.g., overlay software models on a high-fidelity wireless network simulator. • Enhance the DATA modeling extension. • e.g., provide support for A/V streams. • Enhance the BEHAVIOR modeling extension. • e.g., provide support for threading and queuing. • Validate simulation results through comparison to a real system. • Create integrated simulations consisting of both simulated and real (operational) components. • e.g., “test harnesses” for implemented components. • Implement automatic conversion between xADL XML schemas and GME metamodels.