Data Aggregation in Wireless Sensor Networks

  • Kai-Wei Fan
  • Sha Liu
  • Prasun Sinha
Part of the Signals and Communication Technology book series (SCT)

With advance in technology, sensor networks composed of small and cost effective sensing devices equipped with wireless radio transceiver for environment monitoring have become feasible. The key advantage of using these small devices to monitor the environment is that it does not require infrastructure such as electric mains for power supply and wired lines for Internet connections to collect data, nor need human interaction while deploying. These sensor nodes can monitor the environment by collecting information from their surroundings, and work cooperatively to send the data to a base station, or sink, for analysis.

However, currently there are two limitations on these sensor nodes. First, the power supply is limited. Without electric infrastructure, the nodes are powered by batteries. Once the batteries run out of energy, the nodes die. Battery replacement is not economic, and sometimes infeasible. The sensor nodes will be very cheap once they are mass production products. Deploying new sensor nodes will be more economic than human power. Sometimes the sensor network may be deployed in a hostile or unreachable environment, such as a battle field or chemical waste disposal, and therefore it is not possible for a human to replace a depleted battery.


Sensor Network Sensor Node Wireless Sensor Network Data Aggregation Forward Packet 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Chalermek Intanagonwiwat, Ramesh Govindan, and Deborah Estrin, Directed diffusion: a scalable and robust communication paradigm for sensor networks, (MobiCom 2000) pp 56-67.Google Scholar
  2. 2.
    Wendi B. Heinzelman, Anantha Chandrakasan, and Hari Balakrishnan, Energy Efficient Communication Protocol for Wireless Microsensor Networks, (33rd Hawaii International Conference on System Sciences, 2000).Google Scholar
  3. 3.
    Wendi B. Heinzelman, Anantha Chandrakasan, and Hari Balakrishnan, An Application-Specific Protocol Architecture for Wireless Microsensor Networks, (IEEE Transactions on Wireless Communications, Vol. 1, No. 4, 2002) pp 660-670.Google Scholar
  4. 4.
    Timothy J. Shepard, A channel access scheme for large dense packet radio networks, (SIG-COMM 96) pp 219-230Google Scholar
  5. 5.
    S. Lindsey, C. S. Raghavendra, PEGASIS: Power Efficient GAthering in Sensor Informa-tion Systems, (IEEE Aerospace Conference 2002), pp 1-6.Google Scholar
  6. 6.
    Samuel Madden, Michael J. Franklin, Joseph M. Hellerstein, and Wei Hong, TAG: A Tiny AGgregation Service for Ad-Hoc Sensor Networks, (ACM SIGOPS Operating Systems Review 2002) pp 131-146.Google Scholar
  7. 7.
    Chalermek Intanagonwiwat, Deborah Estrin, Ramesh Govindan, and John Heidemann, Im-pact of Network Density on Data Aggregation in Wireless Sensor Networks, (ICDCS 2002).Google Scholar
  8. 8.
    Wensheng Zhang and Guohong Cao, DCTC: dynamic convoy tree-based collaboration for target tracking in sensor networks, (IEEE Transactions on Wireless Communications, Volume 3 , Issue 5, Sept. 2004) pp 1689-1701.Google Scholar
  9. 9.
    Wensheng Zhang and Guohong Cao, Optimizing Tree Reconfiguration for Mobile Target Tracking in Sensor Networks, (INFOCOM 2004)Google Scholar
  10. 10.
    Gerard Tel, Introduction to Distributed Algorithm, (Cambridge Univ. Press, 2000)Google Scholar
  11. 11.
    Nancy Lynch, Distributed Algorithms, (Morgan Kaufmann Publishers, Inc. 1996)Google Scholar
  12. 12.
    A. Aljadhai and T. Znati, Predictive mobility support for QoS provisioning in mobile wireless environments, (IEEE J-SAC, Vol. 19, 2001)Google Scholar
  13. 13.
    Michael R. Garey and Davis S. Johnson, Computers and Intractability, a Guide to the Theory of NP-Completeness, (W. H. Freeman and Company, 1991)Google Scholar
  14. 14.
    Jennifer L. Wong, Roozbeh Jafari, and Miodrag Potkonjak, Gateway Placement for La-tency and Energy Efficient Data Aggregation, (29th Annual IEEE International Conference on Local Computer Networks, 2004) pp. 490-497Google Scholar
  15. 15.
    Nisheeth Shrivastava, Chiranjeeb Buragohain, Divyakant Agrawal, and Subhash Suri, Medians and beyond: new aggregation techniques for sensor networks, (Sensys 2004)Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Kai-Wei Fan
    • 1
  • Sha Liu
    • 1
  • Prasun Sinha
    • 1
  1. 1.Computer Science and Engineering DepartmentOhio State UniversityColumbusUSA

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