1. Fine-Grain Adaptation Using Context Information Iqbal Mohomed Department of Computer Science University of Toronto Advisor: Prof. Eyal de Lara HotMobile 2007: Doctoral Consortium

2. Challenge One size does not fit all

3. Challenge One size does not fit all Adaptation can help! Challenge: How to pick appropriate adaptation? Existing techniques based on rules/constraints do not consider relevance of content

4. Thesis Use context information to determine relevance of content and adapt based on this information We investigate two domains: Web Adaptation Remote Health Monitoring

5. Web Adaptation: Factors to Consider Usage Context

6. Web Adaptation: Factors to Consider Usage Context Varying Relevance

7. Web Adaptation: Factors to Consider Usage Context Varying Relevance Multiple Usage

8. Web Adaptation: Factors to Consider Usage Context Varying Relevance Multiple Usage Situational Content E.g. Type of device, characteristics of available wireless link, user’s location

9. Web Adaptation: Factors to Consider Usage Context Varying Relevance Multiple Usage Situational Content E.g. Type of device, characteristics of available wireless link, user’s location For fine-grain adaptation, content must be tailored for both usage context and situational context!

10. Prediction 10KB 20KB Adaptation Proxy Mobile 1 Taking Usage Context Into Account Application Server 2 Server 1 Improve Fidelity Mobile 2 Application 40KB

11. Tailoring Content to Situational Context Content

12. Tailoring Content to Situational Context Content

13. Remote Health Monitoring Bluetooth, ZigBee, etc. Wifi, GPRS, etc.

14. Remote Health Monitoring Context-Aware Filtering can significantly reduce the amount of data transmitted Use context information to judge what sensor readings are expected Vary fidelity of transmitted data based on whether sensor readings conform to expectations Bluetooth, ZigBee, etc. Wifi, GPRS, etc.

15. Next Steps Web Adaptation Can we reduce the amount of interaction required, while still providing fine-grain adaptation? How well will our techniques work on a large scale in the real-world, over an extended period of time?

16. Next Steps Web Adaptation Can we reduce the amount of interaction required, while still providing fine-grain adaptation? How well will our techniques work on a large scale in the real-world, over an extended period of time? Remote Health Monitoring Can we use context-information to save energy (in ways other than reducing the amount of data)?

17. Next Steps Web Adaptation Can we reduce the amount of interaction required, while still providing fine-grain adaptation? How well will our techniques work on a large scale in the real-world, over an extended period of time? Remote Health Monitoring Can we use context-information to save energy (in ways other than reducing the amount of data)? Graduate! And live happily ever after …

18. Conclusions Use context information to determine relevance of data in a given situation When resources are constrained, optimize based on relevance Examples: When bandwidth is costly, or low link-throughput: Perform aggressive fidelity reduction on less relevant images Transmit averages when sensor readings conform to norms When screen real-estate is limited: Simplify web page by removing irrelevant images

19. Conclusions Use context information to determine relevance of data in a given situation When resources are constrained, optimize based on relevance Examples: When bandwidth is costly, or low link-throughput: Perform aggressive fidelity reduction on less relevant images Transmit averages when sensor readings conform to norms When screen real-estate is limited: Simplify web page by removing irrelevant images Collaborators: @ UofT; Prof. Eyal de Lara, Jin Zhang, Jim Cai, Sina Chavoshi and Alvin Chin @ IBM Watson: Dr. Maria Ebling, William Jerome, Dr. Archan Misra

20. Conclusions Use context information to determine relevance of data in a given situation When resources are constrained, optimize based on relevance Examples: When bandwidth is costly, or low link-throughput: Perform aggressive fidelity reduction on less relevant images Transmit averages when sensor readings conform to norms When screen real-estate is limited: Simplify web page by removing irrelevant images