ACM Home Page
Please provide us with feedback. Feedback
Convergent SparseDT topology control protocol in dense sensor networks
Full text PdfPdf (389 KB)
Source ACM International Conference Proceeding Series; Vol. 304 archive
Proceedings of the 2nd international conference on Scalable information systems table of contents
Suzhou, China
SESSION: Sensor networks and systems table of contents
Article No. 34  
Year of Publication: 2007
ISBN:978-1-59593-757-5
Authors
Chengdong Jiang  University of Science and Technology of China, Hefei, P. R. China
Guoliang Chen  University of Science and Technology of China, Hefei, P. R. China
Sponsors
SIGARCH: ACM Special Interest Group on Computer Architecture
SIGIR: ACM Special Interest Group on Information Retrieval
SIGMULTIMEDIA: ACM Special Interest Group on Multimedia
Publisher
Bibliometrics
Downloads (6 Weeks): 3,   Downloads (12 Months): 15,   Citation Count: 0
Additional Information:

abstract   references   index terms   collaborative colleagues  

Tools and Actions: Review this Article  

ABSTRACT

When a sensor network is deployed for monitoring a protected region, topology control is usually used to save energy consumption, especially in a dense deployment. In this paper, we propose a new and simple topology control protocol, Convergent SparseDT, which controls the network density pretty well, and disposes of some important faults of classical topology control protocols while working with dense sensor network. It is a compromise between the energy consumption, network congestion and the area coverage. It guarantees the coverage of most of the monitored area with almost negligible communication and computing overhead. The performance of this protocol is thoroughly analyzed and simulated in NS2 simulator.


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
Computational geometry algorithm library, July 2006.
 
2
The mathworks - matlab and simulink for technical computing, 2006.
 
3
Maxima, a computer algebra system, December 2006.
 
4
The network simulator - ns2, September 2006.
 
5
D. Brillinger. The calculation of cumulants via conditioning. Journal Annals of the Institute of Statistical Mathematics, 21(1), December 1969.
 
6
 
7
G. W. Collins, II. The Foundations of Celestial Mechanics. Pachart Foundation dba Pachart Publishing House, 1989/2004.
 
8
 
9
C. De Simone, M. Diehl, M. Jünger, P. Mutzel, G. Reinelt, and G. Rinaldi. Exact ground states of two-dimensional ±J Ising spin glasses. Journal of Statistical Physics, 84:1363--1371, 1996.
 
10
U. Feige, D. Peleg, and G. Kortsarz. The dense k-subgraph problem. Algorithmica, 29(3):410--421, 2001.
 
11
W. Feller. An introduction to probability theory and its applications. - Vol. 1. John Wiley & Sons, 1968.
 
12
 
13
A. Ghosh and S. K. Das. A distributed greedy algorithm for connected sensor cover in dense sensor networks. In V. K. Prasanna, S. S. Iyengar, P. G. Spirakis, and M. Welsh, editors, DCOSS, volume 3560 of Lecture Notes in Computer Science, pages 340--353. Springer, 2005.
 
14
P. Hall. Introduction to the Theory of Coverage Processes. John Wiley and Sons, New York, 1988.
 
15
R. Hassin, S. Rubinstein, and A. Tamir. Approximation algorithms for maximum dispersion. Oper. Res. Lett., 21(3):133--137, 1997.
 
16
E. T. Jaynes. Probability Theory - The Logic of Science. Cambridge University Press, Cambridge, 2003.
 
17
C.-D. Jiang and G.-L. Chen. Double barrier coverage in dense sensor networks. Technical report, University of Science and Technology of China, 2007. in communication.
 
18
J. A. Lane. The central limit theorem for the poisson shot-noise process. Journal of Applied Probability, 21(2):287--301, 1984.
 
19
B. Liu and D. Towsley. A study of the coverage of large-scale sensor networks. In The First IEEE International Conference on Mobile Ad hoc and Sensor Systems(MASS04), 2004.
 
20
V. Raghunathan, C. Schurgers, S. Park, and M. B. Srivastava. Energy-aware wireless microsensor networks. IEEE Signal Processing Magazine, pages 40--50, Mar. 2002.
21
 
22
E. W. Weisstein. Lambert w-function. From MathWorld-A Wolfram Web Resource.
23
 
24
 
25
H. Zhang and J. Hou. Maintaining sensing coverage and connectivity in large sensor networks. Journal of Wireless Ad Hoc and Sensor Networks, 1(1):89--124, 2005.

Collaborative Colleagues:
Chengdong Jiang: colleagues
Guoliang Chen: colleagues