ACM Home Page
Please provide us with feedback. Feedback
Trade-off between energy savings and source-to-sink delay in data dissemination for wireless sensor networks
Full text PdfPdf (394 KB)
Source International Workshop on Modeling Analysis and Simulation of Wireless and Mobile Systems archive
Proceedings of the 8th ACM international symposium on Modeling, analysis and simulation of wireless and mobile systems table of contents
Montréal, Quebec, Canada
SESSION: Sensor networks table of contents
Pages: 126 - 133  
Year of Publication: 2005
ISBN:1-59593-188-0
Authors
Habib M. Ammari  University of Texas at Arlington, Arlington, TX
Sajal K. Das  University of Texas at Arlington, Arlington, TX
Sponsors
ACM: Association for Computing Machinery
SIGSIM: ACM Special Interest Group on Simulation and Modeling
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 17,   Downloads (12 Months): 96,   Citation Count: 2
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1089444.1089467
What is a DOI?

ABSTRACT

Wireless sensor networks (WSNs) consist of large numbers of unattended sensors with limited storage, energy (battery power) and computational and communication capabilities. Because battery power is the most crucial resource for sensor nodes and delay time is a critical metric for certain WSN applications that require fast response time, data dissemination between source sensors and sinks, which is an essential activity in WSNs, should be done in an energy efficient and timely manner. In this paper, we characterize the trade-off between energy savings and source-to-sink delay in order to extend the operation of individual sensors and hence increase the lifetime of the WSN, and enable sinks to receive sensed data in a timely fashion and make appropriate decisions quickly. To this end, the proposed data dissemination protocol decomposes the transmission range of sensors into a certain number of concentric circular bands (CCBs) based on a minimal distance between consecutive forwarding sensors. Then, it provides a classification of these CCBs based on their exterior radii which will help a source sensor express its degree of interest (DoI) in minimizing two metrics, namely energy consumption and source-to-sink delay. We prove that the use of sensors nodes, which lie on or closely to the shortest path between a source and the sink, as proxy forwarders, helps minimize these two metrics. Our numerical results show that the second CCB minimizes energy consumption; the last CCB minimizes source-to-sink delay; and the middle CCBs trade off between the two metrics in disseminating the monitored data towards the sink.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
 
2
N. Bulusu, J. Heidemann, and D. Estrin. GPS-Less Low Cost Outdoor Localization for Very Small Devices. IEEE Personal Communications Magazine, vol. 7, no. 5, October 2000.
 
3
W. Choi and S. Das. A Novel Framework for Energy-Conserving Data Gathering in Wireless Sensor Networks. The 24th Conference of the IEEE Communications Society (IEEE INFOCOM 2005), Miami, Florida, USA, March 13-17, 2005.
 
4
W. Heinzelman, A. Chandrakasan, and H. Balakrishnan. An Application-Specific Protocol Architecture for Wireless Microsensor Networks. IEEE Transactions on Wireless Communications, vol. 1, no. 4, October 2002.
5
 
6
 
7
J. Luo and J.-P. Hubaux. Joint Mobility and Routing for Lifetime Elongation in Wireless Sensor Networks. Proceedings of the 24th Annual Conference of the IEEE Communications Societies (INFOCOM'05), Miami, Florida, USA, March 2005.
 
8
 
9
 
10
M. Zorzi and R. Rao. Geographic Random Forwarding (GeRaF) for ad hoc and sensor networks: energy and latency performance. IEEE Transactions on Mobile Computing, vol. 2, Oct.-Dec. 2003.


Collaborative Colleagues:
Habib M. Ammari: colleagues
Sajal K. Das: colleagues