skip to main content
research-article

On the quality and value of information in sensor networks

Published: 23 July 2013 Publication History

Abstract

The increasing use of sensor-derived information from planned, ad-hoc, and/or opportunistically deployed sensor networks provides enhanced visibility to everyday activities and processes, enabling fast-paced data-to-decision in personal, social, civilian, military, and business contexts. The value that information brings to this visibility and ensuing decisions depends on the quality characteristics of the information gathered. In this article, we highlight, refine, and extend upon our past work in the areas of quality and value of information (QoI and VoI) for sensor networks. Specifically, we present and elaborate on our two-layer QoI/VoI definition, where the former relates to context-independent aspects and the latter to context-dependent aspects of an information product. Then, we refine our taxonomy of pertinent QoI and VoI attributes anchored around a simple ontological relationship between the two. Finally, we introduce a framework for scoring and ranking information products based on their VoI attributes using the analytic hierarchy multicriteria decision process, illustrated via a simple example.

References

[1]
Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., and Cayirci, E. 2002. A survey on sensor networks. IEEE Commun. 40, 8, 102--114.
[2]
Al-Karaki, J. N. and Kamal, A. E. 2004. Routing techniques in wireless sensor networks: A survey. IEEE Wireless Commun. 11, 6, 6--28.
[3]
Alonso, J. A. and Lamata, M. T. 2006. Consistency in the analytic hierarchy process: A new approach. In. J. Uncertainty, Fuzziness and Knowledge-Based Syst. 14, 4, 445--459.
[4]
Bauer, R. A., Collar, E., and Tang, V. 1992. The Silverlake Project: Transformation at IBM. Oxford University Press, Oxford, U.K.
[5]
Bennett, M. and Waltz, E. 2007. Counterdeception Principles and Applications for National Security. Artech House, Boston, MA.
[6]
Bisdikian, C., Branch, J., Leung, K. K., and Young, R. I. 2009a. A letter soup for the quality of information in sensor networks. In Proceedings of the IEEE Information Quality and Quality of Service Workshop (IQ2S'09).
[7]
Bisdikian, C., Kaplan, L. M., Srivastava, M. B., Thornley, D. J., Verma, D., and Young, R. I. 2009b. Building principles for a quality of information specification for sensor information. In Proceedings of the 12th International Conference on Information Fusion (Fusion'09).
[8]
Blasch, E., Valin, P., and Bosse, E. 2010. Measures of effectiveness for high-level fusion. In Proceedings of the 13th International Conference on Information Fusion (Fusion'10).
[9]
Blasch, E. P., Pribilski, M., Daughtery, B., Roscoe, B., and Gunsett, J. 2004. Fusion metrics for dynamic situation analysis. In Proceedings of the SPIE, Signal Processing, Sensor Fusion, and Target Recognition XIII, I. Kadar, Ed. Vol. 5429.
[10]
Burke, J., Estrin, D., Hansen, M., Parker, A., Ramanathan, N., Reddy, S., and Srivastava, M. B. 2006. Participatory sensing. In Proceeding of the World Sensor Web Workshop.
[11]
Chakraborty, S., Raghavan, K. R., Srivastava, M., Bisdikian, C., and Kaplan, L. M. 2012. Balancing value and risk in information sharing through obfuscation. In Proceedings of the 15th International Conference on Information Fusion (Fusion'12).
[12]
Chen, L., Szymanski, B. K., and Branch, J. W. 2008. Quality-driven congestion control for target tracking in wireless sensor networks. In Proceedings of the IEEE Workshop on Quality of Information for Sensor Networks (QoISN'08). 766--771.
[13]
Ehikioya, S. A. 1999. A characterization of information quality using fuzzy logic. In Proceedings of the 18th International Conference on North American Fuzzy Information Processing Society (NAFIPS), R. N. Dave and T. Sudkamp, Eds. 635--639.
[14]
English, L. P. 1999. Improving Data Warehouse and Business Information Quality: Methods for Reducing Costs and Increasing Profits. Wiley. Hoboken, NJ.
[15]
English, L. P. 2009. Information Quality Applied: Best Practices for Improving Business Information, Processes and Systems. Wiley. Hoboken, NJ.
[16]
Fasolo, E., Rossi, M., Widmer, J., and Zorzi, M. 2007. In-network aggregation techniques for wireless sensor networks: A survey. IEEE Wireless Commun. 14, 2, 70--87.
[17]
Fowler, M. 1996. Analysis Patterns: Reusable Object Models. Addison-Wesley, Boston, MA.
[18]
Gershenfeld, N., Krikorian, R., and Cohen, D. 2004. The Internet of Things. Sci. Am.
[19]
Geyik, S. C., Shah, S. Y., Szymanski, B. K., Das, S., and Zerfos, P. 2012. Market mechanisms for resource allocation in pervasive sensor applications. Pervasive Mobile Comput. 8, 3, 346--357.
[20]
Ghosh, A. and Das, S. K. 2008. Coverage and connectivity issues in wireless sensor networks: A survey. Pervasive Mobile Comput.
[21]
Gilmore, S. and Hillston, J. 1994. The PEPA workbench: A tool to support a process algebra-based approach to performance modelling. In Proceedings of the 7th International Conference on Modelling Techniques and Tools for Computer Performance Evaluation, G. Haring and G. Kotsis, Eds. Lecture Notes in Computer Science, vol. 794. Springer-Verlag, Berlin Heidalberg, 353--368.
[22]
Hart, J. K. and Martinez, K. 2006. Environmental sensor networks: A revolution in the earth system science? Earth-Science Rev. 78, 177--191.
[23]
Hossain, M. A., Atrey, P. K., and Saddik, A. E. 2007. Modeling quality of information in multi-sensor surveillance systems. In Proceedings of the IEEE Data Engineering Workshop on Ambient Intelligence, Media, and Sensing. 11--18.
[24]
Howard, R. A. 1966. Information value theory. IEEE Trans. Syst. Sci. Cybernet. 2, 1, 22--26.
[25]
Howard, R. A. 1968. The foundations of decision analysis. IEEE Trans. Syst. Sci. Cybernet. 4, 3, 211--219.
[26]
Hubbard, D. W. 2007. How to Measure Anything: Finding the Value of “Intangibles” in Business. Wiley, Hoboken, NJ.
[27]
International Telecommunication Union. 2008. Rec. ITU-T E.800: Quality of telecommunication services: Concepts, models, objectives and dependability planning; Terms and definitions related to the quality of telecommunication services.
[28]
Johnson, M. E. and Chang, K. C. 2005. Quality of information for data fusion in net centric publish and subscribe architectures. In Proceedings of the 8th International Conference on Information Fusion (Fusion'05).
[29]
Knight, S.-A. 2007. User perceptions of information quality in world wide Web information retrieval behavior. Ph.D. Dissutation, Edith Cowan University, Joondahop, Australia.
[30]
Liu, C. H., Bisdikian, C., Branch, J. W., and Leung, K. K. 2010. QoI-aware wireless sensor network management for dynamic multi-task operations. In Proceedings of the 7th IEEE International Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON'10).
[31]
Llinas, J. 2001. Assessing the Performance of Multisensor Fusion Processes. In Handbook of Multisensor Data Fusion, D. L. Hall and J. Llinas, Eds., Chapter 20, CRC Press, Boca Raton, FL.
[32]
Open Geospatial Consortium Inc., 2007. OpenGIS sensor Model Language (SensorML) implementation specification. M. Bots and A. Robin, Ed. Ref. Num. Doc: OGC 07-000, ver. 1.0.0.
[33]
Open Geospatial Consortium Inc. 2010. Geographic information: Observations and measurements. S. Cox, Ed. OpenGIS Proj. Doc: OGC 10-004r3 and ISO 19156.
[34]
Rogova, G. L. and Bosse, E. 2010. Information quality in information fusion. In Proceedings of the 13th International Conference on Information Fusion (Fusion'10).
[35]
Saaty, T. L. 1990. How to make a decision: The analytic hierarchy process. Euro. J. Oper. Res. 48, 1, 9--26.
[36]
Saaty, T. L. 2008a. Decision making with the analytic hierarchy process. Int. J. Services Sci. 1, 1, 83--98.
[37]
Saaty, T. L. 2008b. Relative measurement and its generalization in decision making why pairwise comparisons are central in mathematics for the measurement of intangible factors the analytic hierarchy/network process. Rev. R. Acad. Cien. Serie A. Mat. 102, 2, 251--318.
[38]
Sachidananda, V., Khelil, A., and Suri, N. 2010. Quality of information in wireless sensor networks: A survey. In Proceedings of the 15th International Conference on Information Quality (ICIQ'10). 193--207.
[39]
Sheth, A., Henson, C., and Sahoo, S. S. 2008. Semantic Sensor Web. IEEE Internet Comput.
[40]
Shiraishi, S., Obata, T., and Daigo, M. 1998. Properties of a positive reciprocal matrix and their applications to ahp. J. Oper. Res. Soc. Japan 41, 3, 404--414.
[41]
Sowa, J. F. and Zachman, J. A. 1992. Extending and formalizing the framework for information systems architecture. IBM Syst. J. 31, 3, 590--616.
[42]
Stankiewicz, R., Cholda, P., and Jajszczyk, A. 2011. QoX: What is it really? IEEE Commun. Mag.
[43]
Sun, Z., Liu, C. H., Bisdikian, C., Branch, J. W., and Yang, B. 2012. QoI-aware energy management in Internet-of-things sensory environments. In Proceedings of the 9th IEEE International Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON'12).
[44]
Thornley, D. J., Gillies, D. F., and Bisdikian, C. 2009a. A stochastic process algebraic abstraction of detection evidence fusion in tactical sensor networks. In Proceedings of the SPIE, Modeling and Simulation for Military Operations IV, D. A. Trevisani, Ed. Vol. 7348.
[45]
Thornley, D. J., Young, R. J., and Richardson, J. P. 2009b. Toward mission-specific service utility estimation using analytic stochastic process models. In Proceedings of the SPIE, Intelligent Sensing, Situation Management, Impact Assessment, and Cyber-Sensing, J. F. Buford, S. Mott, and G. Jakobson, Eds. Vol. 7352.
[46]
Tychogiorgos, G. and Bisdikian, C. 2011. Selecting relevant sensor providers for meeting “your” quality information needs. In Proceedings of the 12th International Conference on Mobile Data Management (MDM'11).
[47]
Waltz, E. 2003. Knowledge Management in the Intelligence Enterprise. Artech House, Boston, MA.
[48]
Waltz, E. and Llinas, J. 1990. Multisensor Data Fusion. Artech House, Boston, MA.
[49]
Wang, L. and Xiao, Y. 2006. A survey of energy-efficient scheduling mechanisms in sensor networks. Mobile Netw. Appl. 11, 723--74.
[50]
Wang, R. Y. and Strong, D. M. 1996. Beyond accuracy: What data quality means to data consumers. J. Manage. Inform. Syst.
[51]
Wei, W., He, T., Bisdikian, C., Goeckel, D., and Towsley, D. 2010. Target tracking with packet delays and losses--qoi amid latencies and missing data. In Proceedings of the 2nd International Workshop on Information Quality and Quality of Service for Pervasive Computing (IQ2S'10).
[52]
West, M. 2008. ISO 8000, standards for data and information. In Data Management & Information Quality. London, U.K.
[53]
Zahedi, S., Srivastava, M. B., Bisdikian, C., and Kaplan, L. M. 2010. Quality tradeoffs in object tracking with duty-cycled sensor networks. In Proceedings of the 31st IEEE Real-Time Systems Symposium (RTSS'10).

Cited By

View all
  • (2024)Value-based sensor and information fusionSignal Processing, Sensor/Information Fusion, and Target Recognition XXXIII10.1117/12.3014177(18)Online publication date: 7-Jun-2024
  • (2024)Value Matters: A Novel Value of Information-Based Resource Scheduling Method for CAVsIEEE Transactions on Vehicular Technology10.1109/TVT.2024.335511973:6(8720-8735)Online publication date: Jun-2024
  • (2024)Semantic Filtering and Source Coding in Distributed Wireless Monitoring SystemsIEEE Transactions on Communications10.1109/TCOMM.2024.336295172:6(3290-3304)Online publication date: Jun-2024
  • Show More Cited By

Index Terms

  1. On the quality and value of information in sensor networks

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image ACM Transactions on Sensor Networks
    ACM Transactions on Sensor Networks  Volume 9, Issue 4
    July 2013
    523 pages
    ISSN:1550-4859
    EISSN:1550-4867
    DOI:10.1145/2489253
    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: 23 July 2013
    Accepted: 01 October 2012
    Revised: 01 July 2012
    Received: 01 January 2012
    Published in TOSN Volume 9, Issue 4

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. AHP
    2. Internet of things
    3. IoT
    4. QoI
    5. Quality of information
    6. VoI
    7. analytic hierarchy process
    8. information systems
    9. metadata
    10. provenance
    11. sensor information fusion
    12. value of information

    Qualifiers

    • Research-article
    • Research
    • Refereed

    Funding Sources

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)49
    • Downloads (Last 6 weeks)8
    Reflects downloads up to 05 Mar 2025

    Other Metrics

    Citations

    Cited By

    View all
    • (2024)Value-based sensor and information fusionSignal Processing, Sensor/Information Fusion, and Target Recognition XXXIII10.1117/12.3014177(18)Online publication date: 7-Jun-2024
    • (2024)Value Matters: A Novel Value of Information-Based Resource Scheduling Method for CAVsIEEE Transactions on Vehicular Technology10.1109/TVT.2024.335511973:6(8720-8735)Online publication date: Jun-2024
    • (2024)Semantic Filtering and Source Coding in Distributed Wireless Monitoring SystemsIEEE Transactions on Communications10.1109/TCOMM.2024.336295172:6(3290-3304)Online publication date: Jun-2024
    • (2024)Real-Time Reconstruction of Markov Sources and Remote Actuation Over Wireless ChannelsIEEE Transactions on Communications10.1109/TCOMM.2024.335645672:5(2701-2715)Online publication date: May-2024
    • (2024)Knowledge Ontology of Information Quality for Information Fusion2024 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA)10.1109/CogSIMA61085.2024.10553970(39-46)Online publication date: 7-May-2024
    • (2024)Decentralized knowledge discovery using massive heterogenous data in Cognitive IoTCluster Computing10.1007/s10586-023-04154-z27:3(3657-3682)Online publication date: 1-Jun-2024
    • (2023)Fusion Orchestration Guidelines (FOG) for Collaborative Computing and Network Data FusionNAECON 2023 - IEEE National Aerospace and Electronics Conference10.1109/NAECON58068.2023.10365788(286-293)Online publication date: 28-Aug-2023
    • (2023)Applying Mission Information Requirements to Value of Information MiddlewareMILCOM 2023 - 2023 IEEE Military Communications Conference (MILCOM)10.1109/MILCOM58377.2023.10356269(188-193)Online publication date: 30-Oct-2023
    • (2023)Application-Oriented Resource Orchestration Algorithm for Connected Vehicles2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)10.1109/ITSC57777.2023.10422671(979-985)Online publication date: 24-Sep-2023
    • (2023)Real-time Remote Reconstruction of a Markov Source and Actuation over Wireless2023 IEEE International Conference on Communications Workshops (ICC Workshops)10.1109/ICCWorkshops57953.2023.10283717(1386-1391)Online publication date: 28-May-2023
    • 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