1. Automating Context-Aware Application Development Ted McFadden and Karen Henricksen CRC for Enterprise Distributed Systems Technology (DSTC) Jadwiga Indulska School of Information Technology and Electrical Engineering, The University of Queensland

2. Motivation Need powerful yet generic abstractions and infrastructure for context-aware systems We have developed: Context modelling concepts (graphical and logical) Preference model to capture context-dependent requirements Programming models/toolkit Context and preference management infrastructure Shortcomings of the generic approach: APIs and data structures are not the most natural to use repetitive, boiler-plate code is required Changes in the context model often imply modification of code

3. Motivation (continued) Solution - provide tools to: customise generic infrastructure for particular context models automate the generation of repetitive code Benefits of this approach: improved error checking improved ability to evolve context models independently of applications increased opportunity for modifying aspects of the infrastructure with minimal impact on applications

4. Generic infrastructure for context-aware systems Application 1Application 2 Application n Context Programming Toolkit Application layer Toolkit layer Context and preference management layer Context gathering layer Context Manager Preference Manager Context Database Situation Database Preference Database Context Gateway Sensors Legend Elvin notification RMI JDBC

5. Infrastructure components Programming toolkit layer: Supports two programming models: Situation-based triggering: using a variant of the ECA model Branching: selection from set of candidate choices based on: context context-dependent preferences Context manager: Controls repositories of context and situation information Supports context query, update, notification of changes Allows querying of model meta-data (for context tools)

6. Infrastructure components (continued) Preference manager: Controls repositories of user and system preferences/policies Evaluates preferences with respect to a context Supports dynamic preference modification Context gateway: Interprets notifications from sensors Provides a mapping to the fact representation used by the context manager

7. Additional tool support To reduce the coding effort required to use the generic infrastructure, we have developed additional tools for generating: scripts to load and remove context models from the context databases model-specific classes for context manipulation model-specific classes for transmitting context notifications over a content-based publish-subscribe router

8. Approach Tools rely on a context schema representation of our context models This is a SQL-like textual representation of context fact types and situations Schema is parsed by a common back-end schema compiler, which can be connected to arbitrary front-ends

9. Context schema notation CREATE CONTEXT SCHEMA DSTC.PACE.COMM... CREATE DOMAIN PersonID AS Identity... CREATE DOMAIN ChannelID AS Identity... CREATE PROFILED FACT TYPE PersonHasChannel ( KEY ( person PersonID, channel ChannelID ) )... CREATE ALT SENSED FACT TYPE PersonLocatedAtPlace QUALITY(Certainty) ( person PersonID KEY, place PlaceName ALTROLE )... CREATE PROFILED TEMPORAL FACT TYPE PersonEngagedInActivity DEPENDS(PersonLocatedAt) ( person PersonID KEY, activity ActivityName )... CREATE SITUATION Occupied(person PersonID): exists activity. PersonEngagedInActivity[person,activity]. activity = “meeting” or activity = “on.phone”

10. Context schema tool family Context Schema Context Schema Compiler Intermediary Form Context Management Mapping Tool Model-Specific Library Tool Elvin Notification Library Tool Future Tools SQL Database Schema Common Tool Back End Tool Outputs Elvin Classes Fact Binding Classes Domain Classes Task Specific Tool Front Ends

11. Context management mapping tool Generates database administration scripts for our context manager (SQL-based) Context modelling concepts translated into: database constraints metadata Addresses deployment issues (namespaces) CREATE SCHEMA DSTC_PACE_COMM; CREATE DOMAIN DSTC_PACE_COMM.PersonID AS VARCHAR(255)... CREATE TABLE DSTC_PACE_COMM.PersonHasChannel( person DSTC_PACE_COMM.PersonID, channel DSTC_PACE_COMM.ChannelID, PRIMARY KEY (person, channel) ); CREATE TABLE DSTC_PACE_COMM.PersonLocatedAtPlace( person DSTC_PACE_COMM.PersonID, place DSTC_PACE_COMM.PlaceName, qCertainty DSTC_PACE_COMM.Certainty, PRIMARY KEY (person, place) ); CREATE TABLE DSTC_PACE_COMM.PersonEngagedInActivity( person DSTC_PACE_COMM.PersonID, activity DSTC_PACE_COMM.ActivityName, fStartTime TIMESTAMP, fEndTime TIMESTAMP, PRIMARY KEY (person, fStartTime) ); …

12. Model-specific library generator Generates custom code for context manipulation for a given context model Advantages: Eliminates boiler-plate code for common usage cases Catch more errors at compile time Strongly typed methods Catch more errors at run-time Generate validation code IDE integration

13. Elvin notification library tool Context events are often sent as Elvin notifications Tool provides: model-specific code to automate event emission and reception model-specific context gateway that feeds context events into context manager Operates as follows: 1. Tool generates a context interface (sample Java interface shown below) 2. Elvin stub generator is run over interface to generate emitter and collector stubs (Java, Python) 3. Tool generates context gateway Supports flexible (n:m) messaging

14. Conclusions Generic infrastructures for context-aware systems are essential but can be cumbersome to use To overcome this problem, we: adopt a model-driven development approach provide a suite of tools for automatically generating repetitive, boiler- plate code Tools rely on a textual schema notation and a common schema compiler We currently generate: scripts to load/remove context models from context databases model-specific classes for context manipulation model-specific classes for transmitting context notifications

15. Conclusions (continued) Future work: mapping to OWL to enable reasoning over models for: validation interoperation additional tools