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http://dx.doi.org/10.6109/jkiice.2014.18.12.2885

Constructing a Support Vector Machine for Localization on a Low-End Cluster Sensor Network  

Moon, Sangook (Department of Electronic Engineering, Mokwon University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.18, no.12, 2014 , pp. 2885-2890 More about this Journal
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
Support vector machine; Localization; Sensor network; Hadoop;
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