Protocols and Analysis for Predictable Wireless Sensor Networks

Team: Chenyang Lu (PI), Mo Sha, Rahav Dor, Yong Fu

Collaborators: Octav Chipara(UI), William G. Griswold(UCSD)

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The next generation of wireless sensor networks will monitor critical infrastructure, collect vital signs from patients, and disseminate medical and planning information during emergency responses. In contrast to earlier wireless sensor networks for which best-effort services were sufficient, such systems require predictable performance and high reliability. Failure to meet these requirements may have significant adverse effects. This project aims at the development of an engineering methodology for predictable wireless sensor networks. A predictable wireless sensor network is a system for which it is possible to check that its requirements are met under reasonable assumptions regarding its workload and network properties. This project enables the development of predictable wireless sensor networks by providing developers with analytical tools to characterize and optimize the performance of sensor network systems. The intellectual merit of the project includes: (i) Statistical methods for assessing the properties of wireless sensor networks and for provisioning resources to achieve robustness in spite of node failures or temporal variations; (ii) Novel transmission scheduling techniques that ensure a system meets its reliability and real-time requirements; (iii) A new schedulability analysis that bounds network capacity and message latencies under realistic interference models; and (iv) A wireless architecture that instantiates proposed transmission scheduling techniques and the schedulability analysis. In terms of broader impacts, this project will help advance our national capability to develop performance-critical wireless systems. The PIs will teach the developed design and analytical techniques as part of wireless sensor network curriculum and share them with the research community through tutorials.

Publications

• O. Chipara, C. Lu and G.-C. Roman, Real-time Query Scheduling for Wireless Sensor Networks, IEEE Transactions on Computers, vol. 62, no. 9, pp. 1850-1865, September 2013. [PDF]

• M. Sha, G. Hackmann and C. Lu, Energy-Efficient Low Power Listening for Wireless Sensor Networks in Noisy Environments, ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN'13), April,2013. [PDF]

• B. Li, Z. Sun, K. Mechitov, G. Hackmann, C. Lu, S. Dyke, G. Agha and B. Spencer, Realistic Case Studies of Wireless Structural Control, ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS'13), April 2013. [PDF]

• M. Sha, G. Hackmann and C. Lu, Real-world Empirical Studies on Multi-Channel Reliability and Spectrum Usage for Home-Area Sensor Networks, IEEE Transactions on Network and Service Management, 10(1): 56-69, March 2013. [PDF]

• Y. Fu, M. Sha, G. Hackmann and C. Lu. Practical Control of Transmission Power for Wireless Sensor Networks, IEEE International Conference on Network Protocols (ICNP'12), October 2012. [PDF]

• R. Dor, G. Hackmann, Z. Yang, C. Lu, Y. Chen, M. Kollef and T.C. Bailey, Experiences with an End-To-End Wireless Clinical Monitoring System, Conference on Wireless Health (WH'12), October 2012. [PDF]

• A. Saifullah, C. Wu, P. Tiwari, Y. Xu, Y. Fu, C. Lu and Y. Chen, Near Optimal Rate Selection for Wireless Control Systems, IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS'12), April 2012. Best Paper Candidate. [PDF]

• C. Wu, Y. Xu, Y. Chen and C. Lu, Submodular Game for Distributed Application Allocation in Shared Sensor Networks, IEEE International Conference on Computer Communications (INFOCOM'12), March 2012. [PDF]

If you have any questions or comments, feel free to email Mo Sha at msha@wustl.edu.

Acknowledgements

This work is supported, in part, by the NSF under NeTS Grant CNS-1144552.