ACM Home Page
Please provide us with feedback. Feedback
Optimizing lifetime for continuous data aggregation with precision guarantees in wireless sensor networks
Full text PdfPdf (729 KB)
Source IEEE/ACM Transactions on Networking (TON) archive
Volume 16 ,  Issue 4  (August 2008) table of contents
Pages 904-917  
Year of Publication: 2008
ISSN:1063-6692
Authors
Xueyan Tang  School of Computer Engineering, Nanyang Technological University, Singapore
Jianliang Xu  Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong
Publisher
IEEE Press  Piscataway, NJ, USA
Bibliometrics
Downloads (6 Weeks): 17,   Downloads (12 Months): 276,   Citation Count: 0
Additional Information:

abstract   references   index terms   collaborative colleagues  

Tools and Actions: Review this Article  
DOI Bookmark: 10.1109/TNET.2007.902699

ABSTRACT

This paper exploits the tradeoff between data quality and energy consumption to extend the lifetime of wireless sensor networks. To obtain an aggregate form of sensor data with precision guarantees, the precision constraint is partitioned and allocated to individual sensor nodes in a coordinated fashion. Our key idea is to differentiate the precisions of data collected from different sensor nodes to balance their energy consumption. Three factors affecting the lifetime of sensor nodes are identified: 1) the changing pattern of sensor readings; 2) the residual energy of sensor nodes; and 3) the communication cost between the sensor nodes and the base station. We analyze the optimal precision allocation in terms of network lifetime and propose an adaptive scheme that dynamically adjusts the precision constraints at the sensor nodes. The adaptive scheme also takes into consideration the topological relations among sensor nodes and the effect of in-network aggregation. Experimental results using real data traces show that the proposed scheme significantly improves network lifetime compared to existing methods.


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
I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, "A survey on sensor networks," IEEE Commun. Mag., vol. 40, no. 8, pp. 102-114, Aug. 2002.
2
 
3
J. Gehrke and S. Madden, "Query processing in sensor networks," IEEE Pervasive Comput, vol. 3, no. 1, pp. 45-55, Jan.-Mar. 2004.
4
5
6
7
 
8
 
9
A. Deligiannakis, Y. Kotidis, and N. Roussopoulos, "Hierarchical in-network data aggregation with quality guarantees," in Proc. EDBT'04, Mar. 2004, pp. 658-675.
 
10
11
 
12
13
14
 
15
16
 
17
Y. Yao and J. Gehrke, "Query processing for sensor networks," in Proc. CIDR'03, Jan. 2003.
18
19
 
20
21
 
22
23
 
24
 
25
26
27
 
28
 
29
30
 
31
D. Niculescu and B. Nath, "Ad hoc positioning (APS) using AoA," in Proc. IEEE INFOCOM'03, Apr. 2003, pp. 1734-1743.
 
32
O. Younis and S. Fahmy, "Distributed clustering in ad-hoc sensor networks: A hybrid, energy-efficient approach," in Proc. IEEE INFOCOM'04 , Mar. 2004, pp. 629-640.
33
 
34
C. Buragohain, D. Agrawal, and S. Suri, "Power aware routing for sensor databases," in Proc. IEEE INFOCOM'05, Mar. 2005, pp. 1747-1757.
 
35
 
36
 
37
The Network Simulator--ns-2 [Online]. Available: http://www.isi.edu/ nsnam/ns/
 
38
NRL's Sensor Network Extension to ns-2 [Online]. Available: http:// www.nrlsensorsim.pf.itd.nrl.navy.mil/
39
 
40
G. K. Zipf, Human Behavior and the Principles of Least Effort. Reading, MA: Addison-Wesley, 1949.
 
41
Live From Earth and Mars (LEM) Project [Online]. Available: http:// www.k12.atmos.washington.edu/k12/grayskies/

Collaborative Colleagues:
Xueyan Tang: colleagues
Jianliang Xu: colleagues