A Energy Saving Routing Algorithm Based on Shortest Path Tree

Run Liu Wang; Yun Hui Yi

doi:10.4028/www.scientific.net/AMR.986-987.1345

Paper Titles

A Power Control Technology Adapting to Temperature Change
p.1323

Magnetic Field Analysis for the Dual-Stator Toroidal Motor with Hybrid Excitation
p.1328

The Constant Voltage Composite Control Method of the SVC with Unbalanced Load Compensation
p.1332

The Effect of Dead Zone Mode on Electric Vehicle PWM Speed Control System
p.1337

A Energy Saving Routing Algorithm Based on Shortest Path Tree
p.1345

A Low Power Way-Predicting D-Cache with Partial Tag Comparison Filter
p.1350

A Model Based on BP Neural Network for Audible Noise Prediction
p.1356

A Review of Regional Reactive Power Optimization Techniques
p.1360

Applications of Cloud Model Migration Particle Swarm Optimization and Gaussian Penalty Function in Reactive Power Optimization
p.1365

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 986-987A Energy Saving Routing Algorithm Based on...

A Energy Saving Routing Algorithm Based on Shortest Path Tree

Abstract:

The optimal energy saving routing algorithm proposed in this paper is based on the shortest path tree. This algorithm introduces the concept of node classification and builds the weight function based on link energy consumption factor, neighbor node’s residual energy factor and type weight and so on. It uses different weight factor according to different types of nodes, and finally generates the shortest path tree, all nodes send data to sink node along the shortest path tree. The simulation results show that the algorithm can prolong the network life time, balance energy consumption of each node, and reduce the average network delay.

You might also be interested in these eBooks

Energy Research and Power Engineering 2014

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 986-987)

Pages:

1345-1349

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.986-987.1345

Citation:

Cite this paper

Online since:

July 2014

Authors:

Run Liu Wang*, Yun Hui Yi

Keywords:

Energy Saving, Routing, Wireless Sensor Network (WSN)

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] Akyildiz I F, Su W L, Sankarasubramaniam Y, et al. A Survey on Sensor Networks [J]. IEEE Communications Magazine, 2009, 40(10), 112-116.

Google Scholar

[2] Yick J，Mukherjee B, Ghosal D. Wireless Sensor Network Survey [J]. Computer Networks, 2010, 52(12), 2292-2330.

DOI: 10.1016/j.comnet.2008.04.002

Google Scholar

[3] Yi S, Heo J, Cho Y. Power-Efficient and Adaptive Clustering Hierarchy Protocol for Wireless Sensor Networks [J]. Computer Communications, 2011, (30), 2842-2852.

DOI: 10.1016/j.comcom.2007.05.034

Google Scholar

[4] Mhatre V, Rosenberg C. Design Guideline for Wireless Sensor Networks: Communication, Clustering and Aggregation [J]. Journal of Ad Hoc Networks, Elsevier Science, 2011, 2(1), 45-63.

DOI: 10.1016/s1570-8705(03)00047-7

Google Scholar

[5] Chee-Yee Chong, Srikanta P. Sensor Networks: Evolution, Opportunities, and Challenges [C]. Proc. of the IEEE International Conference on Local computer Network, 2013, 9, 1247-1256.

DOI: 10.1109/jproc.2003.814918

Google Scholar

[6] AnH O, Fahmy S, Korpeoglu I. Power Efficient Data Gathering and Aggregation in Wireless Sensor Networks [C]. SIGMD Record, 2012, 2(4), 66-71.

Google Scholar

[7] Stanislava S, Henizelman W B. Cluster Head Election Techniques for Coverage Preservation in Wireless Sensor Networks [J]. Ad Hoc Networks, 2011, 5(7), 955-972.

DOI: 10.1016/j.adhoc.2008.08.006

Google Scholar