CoCA: A Collaborative Context-Aware Service Platform for Pervasive Computing

1. CoCA: A Collaborative Context-Aware Service Platform for Pervasive Computing Dejene Ejigu , Marian Scuturici , Lionel Brunie Laboratoire LIRIS-UMR-CNRS 5205, INSA de Lyon, 7 avenue Jean Capelle, 69621 Villeurbanne cedex, France IDS Lab. Presented by Sang-Keun Lee

2. Introduction • Nowadays… • The emergence of a computing model for mobile ad-hoc networks in pervasive environments • The wide spread of pervasive enabling technologies and the availability of computing enabled handheld appliances • However, the user should not be disturbed by such devices • Context awareness is among the core components of these IDS Lab.

3. Introduction • Basic elements of a pervasive computing environment • stores knowledge and decisions corresponding to the context instance into knowledge repository for future reference. • Pervasive Environment is characterized by • dynamicity, heterogeneity and ubiquity of users, devices and resources, ad-hoc connection among the devices and sensors • GCoM modeling deals with • how context data is collected, organized, represented, stored and presented • CoCA service • interprets and aggregates the low level context values to a more meaningful high level context • performs reasoning about the context and passes decisions about the actions to be triggered IDS Lab.

4. Introduction The objective in this work is to propose and investigate architecture for context-aware services focusing on context reasoning in pervasive computing environment using semantic ontology and collaborative approaches. IDS Lab.

5. Related Works • Application specific approaches • Abowd G., Atkeson, Hong C.,J., Long S., Kooper R., Pinkerton M.“Cyberguide: A Mobile Context-Aware Tour Guide”, Wireless Networks, 3:421--433, 1997 • Kindberg T., Barton J.“A web-based nomadic computing system”, Computer Networks, 35(4):443–456, 2001. • Priyantha N., Miu A., Balakrishnan H., Teller S. “The Cricket Compass for Context-Aware Applications”, Proc. of 7th Annual ACM/IEEE International Conference on Mobile Computing and Networking (MobiCom 2001), Rome, Italy, July 2001. • Major contributions / does not allow ad-hoc communications • context-aware services are based on ad-hoc models and Dertouzos M., “The Oxygen Project” Scientific American, Vol. 281(2), Aug 99, pp. 52-63. • Cerqueira R., Hess C. K., Roman M., and. Campbell, R. H. “Gaia: A Development Infrastructure for Active Spaces”, Workshop on Application Models and Programming Tools for Ubiquitous Computing in conj. with UBICOMP 01, Sep 01. • Semantic web technology • Chen H., Finin T., Joshi A. “An ontology for context-aware pervasive computing environments”, Special Issue on Ontologies for Distributed Systems, Knowledge Engineering Review, Acapulco MX, August 2003. • Context ontology for reasoning and representation • Wang X., Zhang D. Q., Gu T., Pung H. K.“Ontology Based Context Modeling and Reasoning using OWL”, workshop on context modeling and reasoning at IEEE International Conference on Pervasive Computing and Communication , Orlando, Florida, March 2004. • Service based framework/ middle ware solution • Gu T., Pung H. K., Zhang D. Q. “A Service-Oriented Middleware for Building Context-Aware Services”, Journal of Network and Computer Applications, 28, 2005, pp. 1–18. • Others • MARKS, RCSM IDS Lab.

6. Related Works • CoCA: A Collaborative Context-Aware Service Platform for Pervasive ComputingEjigu, Dejene   Scuturici, Marian   Brunie, Lionel   Lab. LIRIS, UMR-CNRS, Villeurbanne; • An Ontology-Based Approach to Context Modeling and Reasoning in Pervasive ComputingEjigu, Dejene Scuturici, Marian Brunie, Lionel Lab. LIRIS-UMR-CNRS, INSA de Lyon; • Hybrid Approach to Collaborative Context-Aware. Service Platform for Pervasive Computing. Dejene Ejigu. Laboratoire LIRIS-UMR-CNRS 5205 • Semantic approach to context management and reasoning in ubiquitous context-aware systems Ejigu, Dejene Scuturici, Marian Brunie, Lionel Laboratoire LIRIS-UMR-CNRS, 5205 IDS Lab.

7. The CoCA Service Platform It Keeps the rules in the rule repository It consists of domain dependent/independent ontology • The Platform aims at acquiring and utilizing context information to provide appropriate services • E.g) A cell phone is always set to vibrating mode when its holder is in the library It filters and sends useful contexts to the context repository • Interface Manager • Manages a UI and interface between the CoCA platform and other modules • Data Source • Responsible to provide necessary data to the core service (GCoM) • Core Service • Responsible to provide the core context aware service after reasoning on the components • Supplementary Service • Knowledge discovery & Collaboration service Reasoning -> Decision & Action Interpretation, Aggregation IDS Lab.

8. The CoCA Service Platform • The Platform uses Contexts, rules, and ontology combined as an input IDS Lab.

9. Discussions and Usage Scenario • Activity diagram shows details of invocation and flow of activities in the CoCA service platform • 2x2 partitions in the diagram show the services and the units responsible for each activity • Protégé ontology development tools and Jena framework API’s are used to implement • Scenario – Pervasive Campus Aware Smart Onlooker example (PCASO) • Scenario of a university campus where research students and professors are involved • Regular meetings, informal and spontaneous meetings and discussions are important for the advancement of their work • Discussion can take place among two or more depending on the relevance of their work IDS Lab.

10. Questions • When do they make such a meeting? • How can only those available are informed about someone else’s interest to discuss about a specific subject matter during his tea break? • How can a student know when his professor is in the tea room, in his office? • What type of messaging method is appropriate to send such information to a particular person located at a particular place at a particular time? IDS Lab.

11. Ontology, Context, Rules, … IDS Lab.

12. Ontology, Context, Rules, … • In GCoM model • Ontology representation using OWL • Context representation using RDF • Rule representation using Jena • Sample Query to select the phone for which the action has to be triggered/fired for “Silent” mode setting can be given as: IDS Lab.

13. Trace of Reasoning Process IDS Lab.

14. Peer Collaborations in the Neighborhood • Storage and processing of context data to knowledge is Highly resource intensive • Ubiquitous devices have scarce resources • Collaboration manager in the CoCA service platform lets devices share resources like context, rules, ontology, processor, memory, etc. to solve computing problems IDS Lab.

15. Conclusion and Future Work • The authors proposed a data independent collaborative context-aware service platform • Prototype has been implemented • Hybrid Approach to Context-aware Service Platform (2008.1) • Combine RDB & Ontology approaches • What is the difference between CoCA and Our approach (a.k.a Alliver) IDS Lab.

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