Managing Sensor Data Using MapReduce

• Author(s): Rohit Gangpa ; Kung wu Park ; Kung O. Kim
• Paper ID: 1703546
• Page: 267-271
• Published Date: 01-07-2022
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 5 Issue 12 June-2022

Abstract

Recently, as the construction of a large-scale sensor network increases, a system for efficiently managing large-scale sensor data is required. In this paper, we propose a cloud-based sensor data management system with low cost, high scalability, and high efficiency. In the proposed system, sensor data is transmitted to the cloud through the cloud gateway, and abnormal situation detection and event processing are performed at this time. The sensor data sent to the cloud is stored in Hadoop HBase, a distributed column-oriented database, and processed in parallel through the MapReduce model-based query processing module. As the processed result is provided through REST-based web service, it can be linked with application programs of various platforms.

Keywords

sensor data management, cloud computing, hadoop, hbase, mapreduce.

Citations

IRE Journals:
Rohit Gangpa , Kung wu Park , Kung O. Kim "Managing Sensor Data Using MapReduce" Iconic Research And Engineering Journals Volume 5 Issue 12 2022 Page 267-271

IEEE:
Rohit Gangpa , Kung wu Park , Kung O. Kim "Managing Sensor Data Using MapReduce" Iconic Research And Engineering Journals, 5(12)