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Network Design and In-network Data Analysis for Energy-Efficient Distributed Sensing

Network Design and In-network Data Analysis for Energy-Efficient Distributed Sensing. Liang Cheng, Ph.D., Associate Professor Laboratory Of Networking Group (LONGLAB) Department of Computer Science and Engineering In Collaborations with ATLSS Colleagues. Outline.

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Network Design and In-network Data Analysis for Energy-Efficient Distributed Sensing

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  1. Network Design and In-network Data Analysis for Energy-Efficient Distributed Sensing Liang Cheng, Ph.D., Associate Professor Laboratory Of Networking Group (LONGLAB) Department of Computer Science and Engineering In Collaborations with ATLSS Colleagues

  2. Outline • Our research in distributed sensing sponsored by NSF • http://www.cse.lehigh.edu/~cheng/LONGLAB_Liang_Cheng.pdf • Wireless sensor networks for bridge monitoring • Network design for interference mitigation • Distributed in-network data analysis • Conclusions Liang Cheng, Ph.D., LONGLAB, Lehigh CSE

  3. Subsurface monitoring techniques GPR TDR air underground Sensing Area Wireless Sensor Node Wireless Sensor Node Wireless Signal Networks Crimp in cable Global Sensing Soil Moisture Sensor S. Yoon, L. Cheng, E. Ghazanfari, S. Pamukcu, and M. T. Suleiman, A radio propagation model for wireless underground sensor networks, IEEE Globecom, Houston, TX, December 2011. Liang Cheng, Ph.D., LONGLAB, Lehigh CSE

  4. Experiments: point vs. global sensing Wireless Vantage Pro2 Water Leakage #2 Water Leakage #1 Soil moisture sensor MICAz (WiSNS) Liang Cheng, Ph.D., LONGLAB, Lehigh CSE

  5. Point sensing vs. global sensing S. Yoon, E. Ghazanfari, L. Cheng, S. Pamukcu, M. T. Suleiman, Subsurface event detection and classification using wireless signal networks, Sensors, Vol. 12, No. 11, 2012. No Change Water Leakage Event #1 Water Leakage Event #2 Liang Cheng, Ph.D., LONGLAB, Lehigh CSE

  6. Outline • Our research in distributed sensing sponsored by NSF • Wireless sensor networks for bridge monitoring • Network design for interference mitigation • Distributed in-network data analysis • Conclusions Liang Cheng, Ph.D., LONGLAB, Lehigh CSE

  7. Why bridge monitoring? • Critical to the economy and public safety • FHWA 2008: 25% Liang Cheng, Ph.D., LONGLAB, Lehigh CSE

  8. Why wireless sensing? • Routine visual inspection • Wired monitoring • the Stone Cutter Bridge in Hong Kong has more than 1200 sensors Liang Cheng, Ph.D., LONGLAB, Lehigh CSE

  9. Wireless sensor network challenges • Network agility • June – September 2006 • Glen Ellen shaking magnitude 4.4 on 08/02/2006 • 3:0 • Multi-hop (2008) • 10 hours for getting 80 seconds of data (1KHz) from 56 sensors • Single-hop (2011) • 5 minutes for 240KB data from 20 sensors Liang Cheng and Shamim Pakzad, Agility of Wireless Sensor Networks for Earthquake Monitoring of Bridges, the Sixth International Conference on Networked Sensing Systems (INSS'09), Carnegie Mellon University, Pittsburgh, USA, June 17 - 19, 2009. Liang Cheng, Ph.D., LONGLAB, Lehigh CSE

  10. Energy-efficient wireless sensor networks with resource constraints • Network design • Critical radio range determination • Hidden terminal problem solution • In-network data analysis • Distributed system identification • … Liang Cheng, Ph.D., LONGLAB, Lehigh CSE

  11. Outline • Our research in distributed sensing sponsored by NSF • Wireless sensor networks for bridge monitoring • Network design for interference mitigation • Distributed in-network data analysis • Conclusions Liang Cheng, Ph.D., LONGLAB, Lehigh CSE

  12. Mitigating exposed interference • Critical radio range determination • Reduce wireless collision probability • Prolong network lifetime Liang Cheng, Ph.D., LONGLAB, Lehigh CSE

  13. Bernoulli graphs • Infinite radius, unreliable links • Bela Bollobas, Random Graphs, Cambridge University Press, 1985 • A graph consists of N nodes where edges are chosen independently and with probability p • Find the critical p ensuring a connected graph • Pc=[logN+c(N)]/N Liang Cheng, Ph.D., LONGLAB, Lehigh CSE

  14. 2D wireless networks • Finite radius, reliable links • Gupta and Kumar, Critical power for asymptotic connectivity in wireless networks, Stochastic Analysis, Control, Optimization & Applications, 1998. • A unit area containing N nodes, each having the same communication radius r • Find the critical r ensuring a connected graph • Rc=[logN+c(N)]/N Liang Cheng, Ph.D., LONGLAB, Lehigh CSE

  15. Gap between theory and practice Wireless sensor locations Rc=[logN+c(N)]/N Liang Cheng, Ph.D., LONGLAB, Lehigh CSE

  16. 1D wireless networks • Finite radius, reliable links • Li and Cheng, Determinate Bounds of Design Parameters for Critical Connectivity in Wireless Multi-hop Line Networks, IEEE WCNC 2011. • A unit length containing N nodes, each having the same communication radius r • Find the critical r ensuring a connected graph • lnN/N =< Rc <= 2lnN/N Liang Cheng, Ph.D., LONGLAB, Lehigh CSE

  17. A bridge sensor network • Finite radius, unreliable links • A unit length containing N nodes, each having the same communication radius r with link connectivity probability p • Find the critical r ensuring a connected graph • lnN/N =< Rc <= 2lnN/(pN) Liang Cheng, Ph.D., LONGLAB, Lehigh CSE

  18. Mitigating hidden interference • Hidden terminal problem • Collision at will • Aloha (1971) • Collision avoidance • IEEE 802.11 (1997) • Collision detection • ? Liang Cheng, Ph.D., LONGLAB, Lehigh CSE

  19. Messages vs. pulses Liang Cheng, Ph.D., LONGLAB, Lehigh CSE

  20. Hidden terminal revisited • Hidden terminal no longer hidden! • Collision detection Liang Cheng, Ph.D., LONGLAB, Lehigh CSE

  21. Throughput increased • J. Peng, L. Cheng, and B. Sikdar, A Wireless MAC Protocol with Collision Detection, IEEE Transactions on Mobile Computing, Vol. 6, No. 12, pp. 1357-1369, 2007. Liang Cheng, Ph.D., LONGLAB, Lehigh CSE

  22. Outline • Our research in distributed sensing sponsored by NSF • Wireless sensor networks for bridge monitoring • Network design for interference mitigation • Critical radio range determination • Hidden terminal problem solution • Distributed in-network data analysis • Distributed system identification • Conclusions Liang Cheng, Ph.D., LONGLAB, Lehigh CSE

  23. Modal parameters of dynamic systems • Eigenvalue decomposition of the state matrix (Ad) results in the matrices of eigenvalues (λi’s) and eigenvectors (ψi’s) • The natural frequencies ωi and damping ratios ζi Liang Cheng, Ph.D., LONGLAB, Lehigh CSE

  24. Traditional modal identification • Expectation-Maximization (EM) • estimates unknown parameter (Ѳ), given the measurement data (Y) in the presence of some hidden variables (Ŷ ) (Dempster, 1977) Liang Cheng, Ph.D., LONGLAB, Lehigh CSE

  25. Distributed modal identification Liang Cheng, Ph.D., LONGLAB, Lehigh CSE

  26. Evaluation results • O(1/n) consumed energy comparing to the centralized method in n-hop WSNs • S. Dorvash, S. Pakzad, and L. Cheng, An iterative modal identification algorithm for structural health monitoring using wireless sensor networks, Earthquake Spectra, Vol. 29, No. 2, pp. 339-365, May 2013. Liang Cheng, Ph.D., LONGLAB, Lehigh CSE

  27. Outline • Our research in distributed sensing sponsored by NSF • Wireless sensor networks for bridge monitoring • Network design for interference mitigation • Distributed in-network data analysis • Conclusions Liang Cheng, Ph.D., LONGLAB, Lehigh CSE

  28. Conclusions • Energy-efficient wireless sensor networks with resource constraints • Network design • Critical radio range determination (1985, 1998, 2011) • Hidden terminal problem solution (1971, 1997, 2007) • In-network data analysis • Distributed system identification (Expectation-maximization 1977, frequency responses 2004, distributed modal identification 2011) Liang Cheng, Ph.D., LONGLAB, Lehigh CSE

  29. Acknowledgement • National Science Foundation (NSF) • Commonwealth of Pennsylvania • Department of Community and Economic Development via PITA • Christian R. & Mary F. Lindback Foundation • Siavash Dorvash, Xu Li, Dr. Shamim Pakzad, Dr. Jun Peng Liang Cheng, Ph.D., LONGLAB, Lehigh CSE

  30. Q & A • cheng@cse.lehigh.edu • 610-758-5941 • Liang Cheng Computer Science & Engineering 19 Memorial Drive West, Bethlehem, PA 18015 Liang Cheng, Ph.D., LONGLAB, Lehigh CSE

  31. Evaluation Scenarios Wireless sensor locations Liang Cheng, Ph.D., LONGLAB, Lehigh CSE

  32. Resource constraints of sensor nodes • Imote2 • Transceiver: CC2420 • Battery • Rechargeable: 300 mWh/cm3 • Zinc-air: 1050-1560 mWh/cm3 • CPU: 13–416 MHz • Memory: 256kB SRAM, 32MB FLASH, 32MB SDRAM • Demo • A freshman lab project of my Eng5 students Liang Cheng, Ph.D., LONGLAB, Lehigh CSE

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