Orchis: Consistency-Driven Data
Quality Maintenance in Networked Sensor Systems
new fabrication and
integration technologies reduce the cost and size of wireless sensors,
observation and control of our physical world will expand dramatically
the temporally and spatially dense monitoring afforded by wireless
networks technology. Several applications such as habitat monitoring,
system, environment sampling, and structure monitoring, have been
showing the promising future of wide range of applications of networked
success is nonetheless determined by whether the sensor networks
can provide a high quality stream of data
over a long period. The inherent feature of unattended and
deployment of networked sensors in a malicious environment, however,
challenges to the underlying systems. These challenges are further
by the fact that sensor systems are usually seriously energy
previous efforts focus on devising techniques to save the sensor node
and thus extend the lifetime of the whole sensor network. However, with
deployments of real sensor systems, in which the main function is to
interesting data and to share with peers, data quality has been
becoming a more
important issue in the design of sensor systems. We argue that the
quality of data should reflect the
timeliness and accuracy of collected data that
are presented to interested
recipients who make the final decision based on these data. Therefore,
task of deceptive data detection and filtering (i.e., data quality
maintenance) plays a vital role in the success
of data collection.
In this project, we undertake a novel approach that
detects deceptive data through considering the consistency requirements
data, and study the relationship between the quality of data and the
communication and energy-efficient design of networked sensor systems.
project consists of four components, including (1) formal models for
consistency and data dynamics, (2) APIs to manage the data consistency,
to detect deceptive data and improve the quality of collected data, and
several cross-layer protocols to support data consistency and filtering
deceptive data. These four components are integrated into a prototype
called Orchis. We have
applied this approach to SPA,
a smartphone assisted chronic illness self-management with
particiaptory sensing, sponsored by Swedish Council for Working Life
and Social Research (2009-2012).
Safwan Al-Omari (now at
Jordan University of Science and Technology)
Kewei Sha (Now at
Oklahoma City University)
Zhan, Weisong Shi and Julia Deng, SensorTrust: A
Resilient Trust Model for Wireless Sensing Systems, Elsevier Pervasive and Mobile Computing, in
- Safwan Al-Omari and Weisong Shi, Incremental
Sensor Node Deployment for Low Cost and Highly Available WSNs,
in Proceedings of MSN 2010, December 20-22, 2010, Hangzhou, China.
- Shinan Wang, Weisong Shi, Bengt B. Arnetz
and Clairy Wiholm, SPARTAN:
A Framework for Smart Phone Assisted Real-Time Healthcare Network Design,
in Proceedings of CollaborateCom 2010, Chicago, Oct 2010.
Shi and Xueyan Tang, Data Quality Management in Wireless
Sensor Networks: Guest Editorial, in International Journal
of Sensor Networks, Vol. 7, No. 3, 2010.
- Kewei Sha, Shinan Wang and Weisong
Role-Differentiated Cooperative Deceptive Data Detection and Filtering
in VANETs, IEEE Transactions on Vehicular Technologies,
Vol. 59, No. 3, pp. 1183-1190, March 2010.
- Guoxing Zhan, Weisong Shi and Julia Deng, SensorTrust: A Resilient Trust Model for
Wireless Sensing Systems, in Proceedings of the ACM SenSys
2009 (poster abstract), Berkeley, CA, November 4-6, 2009.
- Shinan Wang, Kewei Sha and Weisong
Detection and Filtering in WSNs, in
the 8th ACM/IEEE International Conference on Information Processing in
Sensor Networks (IPSN 2009) (two page summary), April 13-16, 2009,
- Kewei Sha, Technical Report
MIST-TR-2008-012, Ph.D. Dissertation: Orchis: Consistency-Driven Data Quality
Management in Sensing Systems
- Kewei Sha, Guoxing Zhan,
Safwan Al-Omari, Tim Calappi, Weisong Shi and Carol Miller, Data Quality and Failures Characterization
of Sensing Data in Environmental Applications, in
Proceedings of CollaborateCom 2008, November 2008.
- Junzhao Du and Weisong Shi, App-MAC: An Application-Aware
Event-Oriented MAC Protocol for Multimodality
Wireless Sensor Networks, IEEE Transactions on Vehicular
Technology, Vol. 57, No. 6, November 2008. (A full technical
report version is here).
- Kewei Sha and Weisong Shi, Consistency-Driven
Data Quality Management in Wireless Sensor Networks, Journal of Parallel and Distributed
Computing, Vol. 68, No. 9, pp. 1207-1221, September 2008.
Al-Omari and Weisong Shi, Incremental Sensor Network Node Deployment
for Low Cost and Highly Available WSNs, Technical report
MIST-TR-2008-002, March 2008.
- Carol J.
Miller, Weisong Shi, and Donald Carpenter, Bridge Scour Assessment
Using the SESAMES Sensor System, accepted by the 2nd International
Workshop on Opto-electronic Sensor-based Monitoring in Geo-engineering
(OSMD), Nanjing, China, Oct 18-19, 2007.
Weisong Shi, Availability
Modeling and Analysis of Autonomous In-Door WSNs, in Proceedings of the
4th IEEE International Conference on Mobile
Ad-Hoc and Sensor Systems (MASS), Pisa,
Itlay, Oct 8-11, 2007. (Accept rate: 25%, 67 out of 265).
Sha and Weisong Shi, Modeling Data Consistency in
Wireless Sensor Networks,
in Workshop Proceedings of
ICDCS 2007 (WWASN 2007), Toronto, June 25-29, 2007. (Accept rate: 30%).
Al-Omari, Junzhao Du, and Weisong Shi,
A Sensor Core Framework for Cross-Layer Design (extended
Proceedings of the 3rd International Conference on Quality-of-Service
in Wired/Wireless Networks (QShine 2006), Waterloo, Canada, August 7-9,
Sha and Weisong Shi, On the Effects of Consistency in
Data Operations in Wireless Sensor Networks, in
Proceedings of the IEEE 12th International Conference on Parallel and
Distributed Systems (ICPADS '2006), Minneapolis, USA, July
- Kewei Sha
and Weisong Shi, Modeling
the Lifetime of Wireless Sensor Networks,
Letters, Vol 3, pp. 126-135, 2005.