qos based on context-aware middleware in wireless sensor network yuan wenjie chen chao chen mingsong
TRANSCRIPT
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 RoomDen
Master Bedroom
Media Center Extender (MCX)
Kid’s Room
Media Center PC
Media Center ExtenderXbox
Longhorn PC
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
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 co
ntext database.
Necessary parts
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
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.
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.
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: T
echnologies, 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
Reference (2) 7. Sachin Adlakha, Saurabh Ganeriwal, Curt Schurgers, Mani B. Srivastava.: Poster abstra
ct: 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