Advanced
Constructing a Support Vector Machine for Localization on a Low-End Cluster Sensor Network
Constructing a Support Vector Machine for Localization on a Low-End Cluster Sensor Network
Journal of the Korea Institute of Information and Communication Engineering. 2014. Dec, 18(12): 2885-2890
  • Published : December 31, 2014
Download
PDF
Export by style
Article
Author
Metrics
Cited by
About the Authors
Moon, Sangook

Abstract
Localization of a sensor network node using machine learning has been recently studied. It is easy for Support vector machines algorithm to implement in high level language enabling parallelism. Raspberrypi is a linux system which can be used as a sensor node. Pi can be used to construct IP based Hadoop clusters. In this paper, we realized Support vector machine using python language and built a sensor network cluster with 5 Pi's. We also established a Hadoop software framework to employ MapReduce mechanism. In our experiment, we implemented the test sensor network with a variety of parameters and examined based on proficiency, resource evaluation, and processing time. The experimentation showed that with more execution power and memory volume, Pi could be appropriate for a member node of the cluster, accomplishing precise classification for sensor localization using machine learning.
Keywords
View Fulltext