1. QoS Based on Context-Aware Middleware in Wireless Sensor Network Yuan Wenjie Chen Chao Chen Mingsong

2. Outline Basic Introduction Analysis Scenarios Challenges Related Works A Prototype Why A Conceptual Middleware Conclusion

3. Basic introduction Context-aware system Family Room Den Master Bedroom Media Center Extender (MCX) Kid’s Room Media Center PC Media Center Extender Xbox Longhorn PC

4. Basic introduction Context computing context ---- network connectivity, bandwidth, nearby resources… user context ---- user’s profile, location, behavior preference… physical context ---- lighting, noise, temperature... temporal context ---- time, delay, duration…

5. Basic introduction Context Provider Abstracting useful contexts from heterogeneous sources, and convert them to certain representations. Context interpreter providing logic reasoning services to process context information Context Database Storing current and past contexts for a particular subdomain. Each domain has one logic context database. Necessary parts

6. Basic introduction QoS-Quality of Service What is QoS? Application perspective Network perspective

7. Outline Basic Introduction Analysis Scenarios Challenges Related Works A Prototype Why A Conceptual Middleware Conclusion

8. Scenarios Consider following cases for a smart space with various location sensors deployed: Population bursts… System crashes due to overload? Or let’s make a little compromise? Multiple services available, Ultrasonic, RFID, pressure sensor, webcam… Which one to choose?

9. Scenarios(2) Consider following cases for a smart space with various location sensors deployed: Real-time position tracking… time-sensitive and bandwidth-hungry Can system performance be smoothed? User-optimized QoS, intent-capturing, behavior prediction, … Can system schedules and initializes services on its own initiative ?

10. QoS Challenges Resource Communication ability (bandwidth, buffer,…) Computing ability (processors, memory spaces,…) Energy Traffic Unbalanced traffic (large set of sources, small number of sinks) Traffic heterogeneity (different reading rates for different sensors)

11. QoS features in context-aware middleware To address above problems, in middleware layer, our QoS should be: supporting priority resource-aware and energy-aware time-aware user-optimized

12. Outline Basic Introduction Analysis Scenarios Challenges Related Works A Prototype Why A Conceptual Middleware Conclusion

13. Related Works NameMiddleware Based Context- Aware QoS Factors Description [ 7]No Density Accuracy Delay Lifetime It is just focused on the design phase of the application of WSN. MidFusionYesNoDensity Lifetime Fault-tolerant A middleware architecture that uses Bayesian theory paradigm to support sensor network applications performing information fusion. MILANYesNoLifetime Energy Bandwidth A middleware linking network and applications, which is suited for application adaptation and tackles very well the challenges of QoS requirements.

14. Related Works NameMiddleware Based Context- Aware QoS Factors Description ESRTYesNoEnergyESRT is a novel transport solution developed to achieve reliable event detection in WSN with minimum energy expenditure. It brings up the concept of non-end-to-end service. DMSYes Accuracy Delay The proposed architecture is designed to improve productivity levels of medical practitioners through the use of software agents. [ 12 ]Yes Accuracy Delay The middleware provides an abstraction layer between applications and the underlying network infrastructure and it also keeps the balance between application QoS requirements and the network lifetime.

15. Outline Basic Introduction Analysis Scenarios Challenges Related Works A Prototype Why A Conceptual Middleware Conclusion

16. QoS in Service-Oriented Context-Aware Middleware Why? Burst traffic (services, communications…) quality-sensitive applications (real-time, multimedia…) How? Application profile Context-awareness

17. Selected QoS Factors Data dissemination Protocols, Priority, Traffic Resource Service, Location, Bandwidth, Active sensor nodes Energy Energy –efficient Application behavior patterns Temporal context Service differentiation

18. A Middleware Prototype Fig. 1. A Conceptual Context-Aware Based QoS Middleware

19. Outline Basic Introduction Analysis Scenarios Challenges Related Works A Prototype Why A Conceptual Middleware Conclusion

20. Growing demands of QoS in WSN applications Context-awareness enables new thrusts in QoS Relevant researches are still in early stage Our prototype needs further implementation

21. References 1. A. Ganz, Z. Ganz, and K. Wongthavarawat.: Multimedia Wireless Networks: Technologies, Standards, and QoS. Prentice Hall, Upper Saddle River, NJ (2004) 2. Capra, L., Emmerich, W., Mascolo, C.: CARISMA: Context-Aware Reflective Middle System for Mobile Applications. IEEE Transac. On Software Engineering, 19(10). (2003): 929-945 3. Guanling Chen, David Kotz.: A Survey of Context-Aware Mobile Computing Research. Technical Report TR2000-381, Department of Computer Science, Dartmouth College (2000) 4. D. Chen and P.K. Varshney.: QoS Support in Wireless Sensor Networks: A Survey. In Proc. of the International Conference on Wireless Networks, ICWN '04. Vol.1, (2004) 227-233 5. T. Gu, HK. Pung and DZ. Zhang.: Toward an OSGi- Based Infrastructure for Context-Aware Applications. IEEE Pervacive Computing, (2004) 6. M. Younis, K. Akayya, M. Eltowiessy, and A.Wadaa.: On Handling QoS Traffic in Wireless Sensor Networks. In Proc. of the 37th Annual Hawaii Int’l Conf. on System Sciences (HICSS'04). Big Island, Hawaii, (2004): 902-921

22. Reference (2) 7. Sachin Adlakha, Saurabh Ganeriwal, Curt Schurgers, Mani B. Srivastava.: Poster abstract: density, accuracy, delay and lifetime tradeoffs in wireless sensor networks-a multidimensional design perspective. In Proc. of the 1st international conference on Embedded networked sensor systems. Los Angeles, California, USA. (2003): 296 – 297 8. Alex, H. Kumar, M. Shirazi, B.: MidFusion: middleware for information fusion in sensor network applications. In Proc. of Intelligent Sensors, Sensor Networks and Information Processing Conference. (2004) :617-622 9. Heizelman, W. et al.: Middle to Support Sensor Network Applications. IEEE Network Magazine Special Issue. (2004) 10. Y. Sankarasubramaniam, B. Akan and I. F. Akyildiz.: ESRT: Event to Sink Reliable Transport in Wireless Sensor networks. In MobiHoc2003, Annapolis, Maryland, (2003) 11. J. O'Donoghue, J. Herbert and R. Kennedy.: Data Consistency Within a Pervasive Medical Environment. In Proc. of of IEEE Sensors 2006. Korea. (2006) 12. Flávia C. Delicato, Paulo F. Pires, Luiz Rust, Luci Pirmez, José Ferreira de Rezende.: Reflective middleware for wireless sensor networks. In Proc. of the 2005 ACM symposium on Applied computing. Santa Fe, New Mexico. (2005): 1155 - 1159 13. Weiser, M. The Computer for the 21st Century. Scientific American. 265(3), (1991): 94- 104 14. Satyanarayanan.: Pervasive Computing: Vision and Challenges. IEEE PCM. (2001): 10-17

23. That’s all, thanks! 26 Oct 2006