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QoS Based on Context-Aware Middleware in Wireless Sensor Network. Yuan Wenjie Chen Chao Chen Mingsong. Outline. Basic Introduction Analysis Scenarios Challenges Related Works A Prototype Why A Conceptual Middleware Conclusion. Basic introduction. Context-aware system. Family Room.
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QoS Based on Context-Aware Middleware in Wireless Sensor Network Yuan Wenjie Chen Chao Chen Mingsong
Outline • Basic Introduction • Analysis • Scenarios • Challenges • Related Works • A Prototype • Why • A Conceptual Middleware • Conclusion
Basic introduction • Context-aware system Family Room Den Media Center Extender (MCX) Media Center PC Media Center Extender Longhorn PC Xbox Kid’s Room Master Bedroom
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…
Basic introduction providing logic reasoning services to process context information Necessary parts Context Provider Context interpreter Context Database Abstracting useful contexts from heterogeneous sources, and convert them to certain representations. Storing current and past contexts for a particular subdomain. Each domain has one logic context database.
Basic introduction • QoS-Quality of Service • What is QoS? • Application perspective • Network perspective
Outline • Basic Introduction • Analysis • Scenarios • Challenges • Related Works • A Prototype • Why • A Conceptual Middleware • Conclusion
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?
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 ?
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)
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
Outline • Basic Introduction • Analysis • Scenarios • Challenges • Related Works • A Prototype • Why • A Conceptual Middleware • Conclusion
Outline • Basic Introduction • Analysis • Scenarios • Challenges • Related Works • A Prototype • Why • A Conceptual Middleware • Conclusion
QoS in Service-Oriented Context-Aware Middleware • Why? • Burst traffic (services, communications…) • quality-sensitive applications (real-time, multimedia…) • How? • Application profile • Context-awareness
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
A Middleware Prototype Fig. 1. A Conceptual Context-Aware Based QoS Middleware
Outline • Basic Introduction • Analysis • Scenarios • Challenges • Related Works • A Prototype • Why • A Conceptual Middleware • Conclusion
Conclusion • 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
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. InProc. of the 37th Annual Hawaii Int’l Conf. on System Sciences (HICSS'04). Big Island, Hawaii, (2004): 902-921
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
That’s all, thanks! 26 Oct 2006