M-Caemon: Modified Cloud Access Execution and Monitoring for Big Data Analytics of Health Sensor System

摘要

This paper aims to design and implement a flexible architectural system to analyze and access the heath sensor data with converging technologies such as Body Sensor Networks, IoT, Cloud computing and Big Data analytics. The available cloud resources enable the Body Sensor Networks to store and analyze the vast amount of data produced by them. Body Sensor Cloud is designed using IoT technology. Body Sensor Cloud operates as a facilitator for Big body sensor Data analytics. In the current application these four techniques formed as the convincing combination. Hadoop Distributed File Systems (HDFS) is proposed to be employed to store the body sensor data on to sensor cloud for further analysis. The analytics is carried out using machine learning approach on top of the MapReduce technique. This paper describes a public sensor cloud delivery model through cloud data analytics for body sensor services. The proposed architecture acts as a Modified Cloud Access Execution and Monitoring environment for body sensor systems and is able to retort to the demanded health sensor client applications (Physician) with greater flexibility.