An Efficient Data Collection Approach for Wireless Sensor Networks
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 33122
An Efficient Data Collection Approach for Wireless Sensor Networks

Authors: Hanieh Alipour, Alireza Nemaney Pour

Abstract:

One of the most important applications of wireless sensor networks is data collection. This paper proposes as efficient approach for data collection in wireless sensor networks by introducing Member Forward List. This list includes the nodes with highest priority for forwarding the data. When a node fails or dies, this list is used to select the next node with higher priority. The benefit of this node is that it prevents the algorithm from repeating when a node fails or dies. The results show that Member Forward List decreases power consumption and latency in wireless sensor networks.

Keywords: Data Collection, Wireless Sensor Network, SensorNode, Tree-Based

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1073607

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2413

References:


[1] K. Maraiya, K. Kant, and N. Gupta, "Architectural Based Data Aggregation Techniques in Wireless Sensor Network: A Comparative Study," International Journal on Computer Science and Engineering (IJCSE), vol. 3, no. 3, pp.1131-1134, 2002.
[2] S. Lindsey, C.S. Raghavendra, "PEGASIS: Power-Efficient Gathering in Sensor Information Systems," Proceedings of IEEE on Conference Aerospace, Los Angeles, CA. 2002, pp. 3-8.
[3] X. ZHANG, Data Collection in Wireless Sensor Networks, PhD thesis Electrical and Computer Engineering in the Graduate College of the University of Illinois at Chicago, 2009, pp. 11-20.
[4] A. Förster, and A.L. Murphy, "Optimal Cluster Sizes for Wireless Sensor Networks: An Experimental Analysis," In Proceedings of ADHOCNETS, 2009, pp.49-63.
[5] H. Li, H. Yi Yu, and A. Liu, "A Tree Based Data Collection Scheme for Wireless Sensor Network" Proceedings of IEEE International Conference on Mobile Communications and Learning Technologies, (ICN/ICONS/MCL2006), Mauritius, 2006, pp.119-124.