Encyclopedia of Database Systems

2018 Edition
| Editors: Ling Liu, M. Tamer Özsu

Data Storage and Indexing in Sensor Networks

  • Phillip B. GibbonsEmail author
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-8265-9_112


Sensor data can either be stored local to the sensor node that collected the data (local storage), transmitted to one or more collection points outside of the sensor network (external storage), or transmitted and stored at other nodes in the sensor network (in-network storage). There are trade-offs with each of these approaches, as discussed below, depending on the volume of data collected at each sensor node, the query workload, and the resource limitations of each node. Moreover, the local and in-network storage scenarios often require in-network indexes in order to reduce the overheads of answering queries on data stored within the sensor network. Such indexes can be classified as either exact-match indexes or range indexes.

Historical Background

External storage is in some sense the default approach for sensor networks, reflecting the common scenario in which the application is interested in all the collected sensor readings. Early work in local storage includes Cougar [

This is a preview of subscription content, log in to check access.

Recommended Reading

  1. 1.
    Ee CT, Ratnasamy S, Shenker S. Practical data-centric storage. In: Proceedings of the 3rd USENIX Symposium on Networked Systems Design & Implementation; 2006. p. 325–38.Google Scholar
  2. 2.
    Ganesan D, Greenstein B, Estrin D, Heidemann J, Govindan R. Multiresolution storage and search in sensor networks. ACM Trans Storage. 2005;1(3):277–315.CrossRefGoogle Scholar
  3. 3.
    Gao J, Guibas LJ, Hershberger J, Zhang L. Fractionally cascaded information in a sensor network. In: Proceedings of the 3rd International Symposium Information Processing in Sensor Networks; 2004.p. 311–19.Google Scholar
  4. 4.
    Gibbons PB, Karp B, Ke Y, Nath S, Seshan S. IrisNet: an architecture for a worldwide sensor web. IEEE Pervasive Comput. 2003;2(4):22–33.CrossRefGoogle Scholar
  5. 5.
    Greenstein B, Estrin D, Govindan R, Ratnasamy S, Shenker S. DIFS: a distributed index for features in sensor networks. In: Proceedings of the 1st IEEE International Workshop on Sensor Network Protocols and Applications; 2003. p. 163–73.Google Scholar
  6. 6.
    Intanagonwiwat C, Govindan R, Estrin D, Heidemann J, Silva F. Directed diffusion for wireless sensor networking. IEEE/ACM Trans Network. 2003;11(1):2–16.CrossRefGoogle Scholar
  7. 7.
    Li X, Kim YJ, Govindan R, Hong W. Multi-dimensional range queries in sensor networks. In: Proceedings of the 1st International Conference on Embedded Networked Sensor Systems; 2003.p. 63–75.Google Scholar
  8. 8.
    Madden SR, Franklin MJ, Hellerstein JM, Hong W. TinyDB: an acquisitional query processing system for sensor networks. ACM Trans Database Syst. 2005;30(1):122–73.CrossRefGoogle Scholar
  9. 9.
    Mathur G, Desnoyers P, Ganesan D, Shenoy P. Capsule: an energy-optimized object storage system for memory-constrained sensor devices. In: Proceedings of the 4th International Conference on Embedded Networked Sensor Systems; 2006. p. 195–208.Google Scholar
  10. 10.
    Ratnasamy S, Karp B, Shenker S, Estrin D, Govindan R, Yin L, Yu F. Data-centric storage in sensornets with GHT, a geographic hash table. Mob Netw Appl. 2003; 8(4):427–42.CrossRefGoogle Scholar
  11. 11.
    Yao Y, Gehrke J. Query processing for sensor networks. In: Proceedings of the 1st Biennial Conference on Innovative Data Systems Research; 2003.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Computer Science Department and the Electrical and Computer Engineering DepartmentCarnegie Mellon UniversityPittsburghUSA

Section editors and affiliations

  • Le Gruenwald
    • 1
  1. 1.School of Computer ScienceUniv. of OklahomaNormanUSA