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QoS Based on Context-Aware Middleware in Wireless Sensor Network

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Title: QoS Based on Context-Aware Middleware in Wireless Sensor Network


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
Media Center Extender (MCX)
Media Center PC
Media Center Extender
Longhorn PC
Xbox
Kids Room
Master Bedroom
4
Basic introduction
  • Context
  • computing context
  • ----network connectivity, bandwidth, nearby
    resources
  • user context
  • ----users profile, location, behavior
    preference
  • physical context
  • ----lighting, noise, temperature...
  • temporal context
  • ----time, delay, duration

5
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.
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 lets 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
Name Middleware Based Context-Aware QoS Factors Description
7 No No Density Accuracy Delay Lifetime It is just focused on the design phase of the application of WSN.
MidFusion Yes No Density Lifetime Fault-tolerant A middleware architecture that uses Bayesian theory paradigm to support sensor network applications performing information fusion.
MILAN Yes No Lifetime 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
Name Middleware Based Context-Aware QoS Factors Description
ESRT Yes No Energy ESRT 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.
DMS Yes Yes Accuracy Delay The proposed architecture is designed to improve productivity levels of medical practitioners through the use of software agents.
12 Yes 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
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

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 Intl 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
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    Korea. (2006)
  • 12. Flávia C. Delicato, Paulo F. Pires, Luiz
    Rust, Luci Pirmez, José Ferreira de Rezende.
    Reflective middleware for wireless sensor
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  • 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
Thats all, thanks!
  • 26 Oct 2006
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