Skip Nav Destination
ASME Press Select Proceedings
International Conference on Advanced Computer Theory and Engineering (ICACTE 2009)
By
ISBN:
9780791802977
No. of Pages:
2012
Publisher:
ASME Press
Publication date:
2009
eBook Chapter
5 Using Dominating Set and TSP Algorithm for Data Collection with Mobile Sink in Wireless Sensor Networks
By
Tao Chen
,
Tao Chen
College of Information Systems and Management,
National University of Defense Technology
, Changsha
, China
Search for other works by this author on:
Deke Guo
,
Deke Guo
College of Information Systems and Management,
National University of Defense Technology
, Changsha
, China
Search for other works by this author on:
Xueshan Luo
,
Xueshan Luo
College of Information Systems and Management,
National University of Defense Technology
, Changsha
, China
Search for other works by this author on:
Junxian Liu
,
Junxian Liu
College of Information Systems and Management,
National University of Defense Technology
, Changsha
, China
Search for other works by this author on:
Zhen Shu
Zhen Shu
College of Information Systems and Management,
National University of Defense Technology
, Changsha
, China
Search for other works by this author on:
Page Count:
8
-
Published:2009
Citation
Chen, T, Guo, D, Luo, X, Liu, J, & Shu, Z. "Using Dominating Set and TSP Algorithm for Data Collection with Mobile Sink in Wireless Sensor Networks." International Conference on Advanced Computer Theory and Engineering (ICACTE 2009). Ed. Yi, X. ASME Press, 2009.
Download citation file:
Traditional data collection protocols suffer “hot spot” problem heavily in area around the sink node. Recently proposed schemes using mobile sinks try to balance the load with the cost of sink mobility. However, most approaches are based on unit disk graph (UDG) model, which is inaccurate in physical world. We propose an UDG-free solution for data collection with mobile sinks using dominating set and traveling salesman problem (TSP) techniques. A distributed algorithm for dominating set construction is presented, and the result set is used in approximate TSP algorithm to generate a moving path. Our solution not only reduces communication overhead, but also balances the load distribution.
Abstract
Key Words
1 Introduction
2. Network Model and Problem Definition
3. Our Solution
4. Simulations
5. Related Work
6. Conclusion
References
This content is only available via PDF.
You do not currently have access to this chapter.
Email alerts
Related Chapters
A Learning-Based Adaptive Routing for QoS-Aware Data Collection in Fixed Sensor Networks with Mobile Sinks
Intelligent Engineering Systems through Artificial Neural Networks, Volume 20
Low Energy Consumption Cluster-Based Routing Algorithm for Wireless Sensor Networks
International Conference on Electronics, Information and Communication Engineering (EICE 2012)
An Improved Wireless Sensor Networks Routing Algorithm Based on End-to-End Packet Reception Rate
International Conference on Advanced Computer Theory and Engineering, 4th (ICACTE 2011)
3D-CDHL: A Hybrid 3D Range-Free Localization Algorithm in WSN
International Conference on Advanced Computer Theory and Engineering, 4th (ICACTE 2011)
Related Articles
Home Telemedicine: Encryption is Not Enough
J. Med. Devices (June,2009)
Harvesting Wind Energy Using a Galloping Piezoelectric Beam
J. Vib. Acoust (February,2012)
Fabrication and Characterization of Flexible Substrates for Use in the Development of Miniaturized Wireless Sensor Network Modules
J. Electron. Packag (September,2006)