Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
research-article

Packet-level attestation (PLA): A framework for in-network sensor data reliability

Published: 01 April 2013 Publication History

Abstract

Wireless sensor networks (WSN) show enormous potential for collection and analysis of physical data in real-time. Many papers have proposed methods for improving the network reliability of WSNs. However, real WSN deployments show that sensor data-faults are very common. Several server-side data reliability techniques have been proposed to detect these faults and impute missing or erroneous data. Typically, these techniques reduce the lifetime of the network due to redundant data transmission, increase latency, and are computation and storage intensive. Herein, we propose Packet-Level Attestation (PLA), a novel framework for sensor data reliability assessment. It exploits the spatial correlation of data sensed at nearby sensors. The method does not incur additional transmission of control message between source and sink; instead, a verifier node sends a validation certificate as part of the regular data packet. PLA was implemented in TinyOS on TelosB motes and its performances was assessed. Simulations were performed to determine its scalability. It incurs only an overhead of 1.45% in terms of packets transmitted. Fault detection precision of the framework varied from 100% to 99.48%. Comparisons with existing methods for data reliability analysis showed a significant reduction in data transmission, prolonging the network lifetime.

References

[1]
Avrora 2008. The AVR simulation and analysis framework. http://compilers.cs.ucla.edu/avrora/. (Last. accessed 11/10).
[2]
Balzano, L., and Nowak, R. 2007. Blind calibration of sensor networks. In Proceedings of the 6th International Conference on Information Processing in Sensor Networks (IPSN'07). 79--88.
[3]
Brickell, E., Camenisch, J., and Chen, L. 2004. Direct anonymous attestation. In Proceedings of the 11th ACM Conference on Computer and Communications Security (CCS'04). 132--145.
[4]
Bychkovskiy, V., Megerian, S., Estrin, D., and Potkonjak, M. 2003. A collaborative approach to in-place sensor calibration. In Proceedings of the 2nd International Conference on Information Processing in Sensor Networks (IPSN'03). 301--316.
[5]
Chipara, O., Lu, C., Bailey, T. C., and Roman, G.-C. 2010. Reliable clinical monitoring using wireless sensor networks: Experiences in a step-down hospital unit. In Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems (SenSys'10). 155--168.
[6]
Commerce, B. E., Jsang, A., and Ismail, R. 2002. The beta reputation system. In Proceedings of the 15th Bled Electronic Commerce Conference. 324--337.
[7]
Corke, P., Wark, T., Jurdak, R., Hu, W., Valencia, P., and Moore, D. 2010. Environmental wireless sensor networks. Proc. IEEE 98, 11, 1903--1917.
[8]
Crossbow 2010. Data sheet from Crossbow. http://www.xbow.com/Products/productdetails.aspx?sid=252. (Last accessed 3/10).
[9]
Deshpande, A., Guestrin, C., Madden, S. R., Hellerstein, J. M., and Hong, W. 2004. Model-driven data acquisition in sensor networks. In Proceedings of the 13th International Conference on Very Large Data Bases (VLDB'04). 588--599.
[10]
Elnahrawy, E. and Nath, B. 2003. Cleaning and querying noisy sensors. In Proceedings of the 2nd ACM International Conference on Wireless Sensor Networks and Applications (WSNA'03). 78--87.
[11]
Fan, Y.-C. and Chen, A. L. P. 2010. Efficient and robust schemes for sensor data aggregation based on linear counting. IEEE Trans. Parallel Distrib. Syst. 21, 11, 1675--1691.
[12]
Gnawali, O., Fonseca, R., Jamieson, K., Moss, D., and Levis, P. 2009. Collection tree protocol. In Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems (SenSys'09). 1--14.
[13]
Guestrin, C., Bodik, P., Thibaux, R., Paskin, M., and Madden, S. 2004. Distributed regression: An efficient framework for modeling sensor network data. In Proceedings of the 3rd International Symposium on Information Processing in Sensor Networks (IPSN'04). 1--10.
[14]
Guo, S., Zhong, Z., and He, T. 2009. Find: Faulty node detection for wireless sensor networks. In Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems (SenSys'09). 253--266.
[15]
Han, J. 2005. Data Mining: Concepts and Techniques. Morgan Kaufmann Publishers Inc., San Francisco, CA.
[16]
Hellerstein, J. M., Hong, W., Madden, S., and Stanek, K. 2003. Beyond average: Toward sophisticated sensing with queries. In Proceedings of the 2nd International Conference on Information Processing in Sensor Networks (IPSN'03). 63--79.
[17]
IEEE. 2006. IEEE Standard 802.15.4. http://www.ieee.org/index.html.
[18]
Ingelrest, F., Barrenetxea, G., Schaefer, G., Vetterli, M., Couach, O., and Parlange, M. 2010. Sensorscope: Application-specific sensor network for environmental monitoring. ACM Trans. Sen. Netw. 6, 17, 1--32.
[19]
Intel. 2004. Intel lab sensor data. http://db.csail.mit.edu/labdata/labdata.html.
[20]
Kamal, A. R. M., Razzaque, M. A. A., and Nixon, P. 2010. 2pda: Two-phase data approximation in wireless sensor network. In Proceedings of the 7th ACM Workshop on Performance Evaluation of Wireless Ad Hoc, Sensor, and Ubiquitous Networks (PE-WASUN'10). 1--8.
[21]
Ko, J., Lim, J. H., Chen, Y., Musvaloiu-E, R., Terzis, A., Masson, G. M., Gao, T., Destler, W., Selavo, L., and Dutton, R. P. 2010. Medisn: Medical emergency detection in sensor networks. ACM Trans. Embed. Comput. Syst. 10, 11, 1--29.
[22]
Koushanfar, F. and Potkonjak, M. 2005. Markov chain-based models for missing and faulty data in mica2 sensor motes. In Proceedings of the IEEE Sensors Conference.
[23]
Krishnamachari, B. and Iyengar, S. 2004. Distributed bayesian algorithms for fault-tolerant event region detection in wireless sensor networks. IEEE Trans. Comput. 53, 241--250.
[24]
Lee, H., Keshavarzian, A., and Aghajan, H. 2010. Near-lifetime-optimal data collection in wireless sensor networks via spatio-temporal load balancing. ACM Trans. Sen. Netw. 6, 26, 1--32.
[25]
Lim, J. C. and Bleakley, C. 2010. Robust data collection and lifetime improvement in wireless sensor networks through data imputation. In Proceedings of the 5th International Conference on Systems and Networks Communications (ICSNC). 64--69.
[26]
Liu, C., Wu, K., and Pei, J. 2007. An energy-efficient data collection framework for wireless sensor networks by exploiting spatiotemporal correlation. IEEE Trans. Parallel Distrib. Syst. 18, 1010--1023.
[27]
Liu, Y., Liu, K., and Li, M. 2010. Passive diagnosis for wireless sensor networks. IEEE/ACM Trans. Netw. 18, 4, 1132--1144.
[28]
Marti, S., Giuli, T. J., Lai, K., and Baker, M. 2000. Mitigating routing misbehavior in mobile ad hoc networks. In Proceedings of the 6th Annual International Conference on Mobile Computing and Networking (MobiCom'00). 255--265.
[29]
Moeller, S., Sridharan, A., Krishnamachari, B., and Gnawali, O. 2010. Routing without routes: The backpressure collection protocol. In Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN'10). 279--290.
[30]
Mukhopadhyay, S., Schurgers, C., Panigrahi, D., and Dey, S. 2009. Model-based techniques for data reliability in wireless sensor networks. IEEE Trans. Mobile Comput. 8, 4, 528--543.
[31]
Ni, K., Ramanathan, N., Chehade, M. N. H., Balzano, L., Nair, S., Zahedi, S., Kohler, E., Pottie, G., Hansen, M., and Srivastava, M. 2009. Sensor network data fault types. ACM Trans. Sen. Netw. 5, 25, 1--29.
[32]
Puccinelli, D. and Haenggi, M. 2010. Reliable data delivery in large-scale low-power sensor networks. ACM Trans. Sen. Netw. 6, 28, 1--41.
[33]
Ramanathan, N., Balzano, L., Burt, M., Estrin, D., Harmon, T., Harvey, C., Jay, J., Kohler, E., Rothenberg, S., and Srivastava, M. 2006. Rapid deployment with confidence: Calibration and fault detection in environmental sensor networks. CENS Tech. Rep. 62.
[34]
Sesnorscope 2008. EPFL SensorScope Project. http://sensorscope.epfl.ch/index.php/Environmental_Data. (Last accessed 11/10).
[35]
Sharma, A. B., Golubchik, L., and Govindan, R. 2010. Sensor faults: Detection methods and prevalence in real-world datasets. ACM Trans. Sen. Netw. 6, 23, 1--39.
[36]
Srinivasan, K. and Levis, P. 2006. RSSI is under appreciated. In Proceedings of the 3rd Workshop on Embedded Networked Sensors (EmNets'06).
[37]
Staddon, J., Balfanz, D., and Durfee, G. 2002. Efficient tracing of failed nodes in sensor networks. In Proceedings of the 1st ACM International Workshop on Wireless Sensor Networks and Applications (WSNA'02). 122--130.
[38]
Szewczyk, R., Mainwaring, A., Polastre, J., Anderson, J., and Culler, D. 2004. An analysis of a large scale habitat monitoring application. In Proceedings of the 2nd International Conference on Embedded Networked Sensor Systems (SenSys'04). 214--226.
[39]
Tavakoli, A., Kansal, A., and Nath, S. 2010. On-line sensing task optimization for shared sensors. In Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN'10). 47--57.
[40]
TinyOS 2010. TinyOS documentation. http://docs.tinyos.net/index.php/Main_Page. (Last accessed 1/10).
[41]
Titzer, B. L., Lee, D. K., and Palsberg, J. 2005. Avrora: Scalable sensor network simulation with precise timing. In Proceedings of the 4th International Symposium on Information Processing in Sensor Networks (IPSN'05). 477--482.
[42]
Tolle, G., Polastre, J., Szewczyk, R., Culler, D., Turner, N., Tu, K., Burgess, S., Dawson, T., Buonadonna, P., Gay, D., and Hong, W. 2005. A macroscope in the redwoods. In Proceedings of the 3rd International Conference on Embedded Networked Sensor Systems (SenSys'05). 51--63.
[43]
Tulone, D. and Srivastava, M. 2007. Inspect: A general framework for on-line detection and diagnosis of sensor faults. In Proceedings of the 2nd International Conference on Internet Technologies & Applications (ITA).
[44]
Vuran, M. C., Akan, Ö. B., and Akyildiz, I. F. 2004. Spatio-temporal correlation: Theory and applications for wireless sensor networks. Comput. Netw. 45, 245--259.
[45]
Xu, N., Rangwala, S., Chintalapudi, K. K., Ganesan, D., Broad, A., Govindan, R., and Estrin, D. 2004. A wireless sensor network for structural monitoring. In Proceedings of the 2nd International Conference on Embedded Networked Sensor Systems (SenSys'04). 13--24.
[46]
Zhao, F. and Guibas, L. J. 2004. Wireless Sensor Networks: An Information Processing Approach 1st Ed. Elsivier, NY, Chapter 1, 4--10.

Cited By

View all
  • (2020)Trustworthy Data Acquisition and Faulty Sensor Detection using Gray Code in Cyber-Physical System2020 IEEE 23rd International Conference on Computational Science and Engineering (CSE)10.1109/CSE50738.2020.00016(58-65)Online publication date: Dec-2020
  • (2020)Improving Energy Efficiency With Content-Based Adaptive and Dynamic Scheduling in Wireless Sensor NetworksIEEE Access10.1109/ACCESS.2020.30269398(176495-176520)Online publication date: 2020
  • (2019)Trust Based Data Gathering in Wireless Sensor NetworkWireless Personal Communications: An International Journal10.1007/s11277-019-06491-y108:3(1697-1717)Online publication date: 1-Oct-2019
  • Show More Cited By

Index Terms

  1. Packet-level attestation (PLA): A framework for in-network sensor data reliability

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image ACM Transactions on Sensor Networks
    ACM Transactions on Sensor Networks  Volume 9, Issue 2
    March 2013
    532 pages
    ISSN:1550-4859
    EISSN:1550-4867
    DOI:10.1145/2422966
    Issue’s Table of Contents
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Journal Family

    Publication History

    Published: 01 April 2013
    Accepted: 01 November 2011
    Revised: 01 November 2011
    Received: 01 April 2011
    Published in TOSN Volume 9, Issue 2

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. Wireless sensor networks
    2. data collection
    3. data reliability
    4. routing
    5. sensor data
    6. sensor faults
    7. sensor network

    Qualifiers

    • Research-article
    • Research
    • Refereed

    Funding Sources

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)7
    • Downloads (Last 6 weeks)1
    Reflects downloads up to 17 Feb 2025

    Other Metrics

    Citations

    Cited By

    View all
    • (2020)Trustworthy Data Acquisition and Faulty Sensor Detection using Gray Code in Cyber-Physical System2020 IEEE 23rd International Conference on Computational Science and Engineering (CSE)10.1109/CSE50738.2020.00016(58-65)Online publication date: Dec-2020
    • (2020)Improving Energy Efficiency With Content-Based Adaptive and Dynamic Scheduling in Wireless Sensor NetworksIEEE Access10.1109/ACCESS.2020.30269398(176495-176520)Online publication date: 2020
    • (2019)Trust Based Data Gathering in Wireless Sensor NetworkWireless Personal Communications: An International Journal10.1007/s11277-019-06491-y108:3(1697-1717)Online publication date: 1-Oct-2019
    • (2018)Data Reconstruction in Wireless Sensor Networks From Incomplete and Erroneous ObservationsIEEE Access10.1109/ACCESS.2018.28641266(45493-45503)Online publication date: 2018
    • (2017)Sensor Data Modeling for Data Trustworthiness2017 IEEE Trustcom/BigDataSE/ICESS10.1109/Trustcom/BigDataSE/ICESS.2017.330(909-916)Online publication date: Aug-2017
    • (2017)Intelligent fault management system for wireless sensor networks with reduction of power consumption2017 IEEE 26th International Symposium on Industrial Electronics (ISIE)10.1109/ISIE.2017.8001471(1521-1527)Online publication date: Jun-2017
    • (2017)A non-cooperative non-zero-sum game-based dependability assessment of heterogeneous WSNs with malware diffusionJournal of Network and Computer Applications10.1016/j.jnca.2017.05.00391:C(26-35)Online publication date: 1-Aug-2017
    • (2017)A Hybrid Trust Management Scheme for Wireless Sensor NetworksWireless Personal Communications: An International Journal10.1007/s11277-017-4772-497:4(5137-5170)Online publication date: 1-Dec-2017
    • (2016)Reliability Evaluation for Clustered WSNs under Malware PropagationSensors10.3390/s1606085516:6(855)Online publication date: 10-Jun-2016
    • (2016)Modeling of multihop wireless sensor networks with MAC, queuing, and cooperationInternational Journal of Distributed Sensor Networks10.1155/2016/52587422016(3-3)Online publication date: 1-Jan-2016
    • Show More Cited By

    View Options

    Login options

    Full Access

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Figures

    Tables

    Media

    Share

    Share

    Share this Publication link

    Share on social media