Multiple time series database on microservice architecture for IoT-based sleep monitoring system
Abstract Monitoring health status requires collecting a large amount of data from the human body. The sensor can be used to collect data from the human body. The sensor transmits data for almost every second across the internet. The challenge of the health monitoring system is the massive amount of...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2022-11-01
|
| Series: | Journal of Big Data |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40537-022-00658-4 |
| _version_ | 1797984005732171776 |
|---|---|
| author | Eko Simanjuntak Nico Surantha |
| author_facet | Eko Simanjuntak Nico Surantha |
| author_sort | Eko Simanjuntak |
| collection | DOAJ |
| description | Abstract Monitoring health status requires collecting a large amount of data from the human body. The sensor can be used to collect data from the human body. The sensor transmits data for almost every second across the internet. The challenge of the health monitoring system is the massive amount of incoming data. Therefore, a system capable of sending, storing, analyzing, and visualizing vast amounts of data is required for health monitoring. A previous study proposed microservice and event-driven architecture. It also proposed a single database for all services and a relational database management system (RDBMS) for storing time series data, which might reduce the data transmission performance and reliability. This research intends to improve the monitoring system from the previous study to accommodate a greater throughput, faster database read and write operations, and a more reliable system design. The improvement consists of multiple changes in system architecture and technology. A multi-database is proposed in the system architecture to improve system reliability. Time series database and Message Queue Telemetry Protocol (MQTT) server are proposed as an upgrade on technology. As a result, the proposed system throughput is 2.43 times faster than the old system. On database performance, the new system's database write speed is 20.95 times faster and the database read speed is 1.64 times faster than the old system. The proposed system also achieves better scalability, resilience, and independence. |
| first_indexed | 2024-04-11T06:56:06Z |
| format | Article |
| id | doaj.art-cfcb92c44b6648808adcf3406bab8270 |
| institution | Directory Open Access Journal |
| issn | 2196-1115 |
| language | English |
| last_indexed | 2024-04-11T06:56:06Z |
| publishDate | 2022-11-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Journal of Big Data |
| spelling | doaj.art-cfcb92c44b6648808adcf3406bab82702022-12-22T04:39:02ZengSpringerOpenJournal of Big Data2196-11152022-11-019111910.1186/s40537-022-00658-4Multiple time series database on microservice architecture for IoT-based sleep monitoring systemEko Simanjuntak0Nico Surantha1BINUS Graduate Program-Master of Computer Science, Bina Nusantara UniversityBINUS Graduate Program-Master of Computer Science, Bina Nusantara UniversityAbstract Monitoring health status requires collecting a large amount of data from the human body. The sensor can be used to collect data from the human body. The sensor transmits data for almost every second across the internet. The challenge of the health monitoring system is the massive amount of incoming data. Therefore, a system capable of sending, storing, analyzing, and visualizing vast amounts of data is required for health monitoring. A previous study proposed microservice and event-driven architecture. It also proposed a single database for all services and a relational database management system (RDBMS) for storing time series data, which might reduce the data transmission performance and reliability. This research intends to improve the monitoring system from the previous study to accommodate a greater throughput, faster database read and write operations, and a more reliable system design. The improvement consists of multiple changes in system architecture and technology. A multi-database is proposed in the system architecture to improve system reliability. Time series database and Message Queue Telemetry Protocol (MQTT) server are proposed as an upgrade on technology. As a result, the proposed system throughput is 2.43 times faster than the old system. On database performance, the new system's database write speed is 20.95 times faster and the database read speed is 1.64 times faster than the old system. The proposed system also achieves better scalability, resilience, and independence.https://doi.org/10.1186/s40537-022-00658-4IoTTime series databaseHealth monitoringMicroserviceMQTT protocol |
| spellingShingle | Eko Simanjuntak Nico Surantha Multiple time series database on microservice architecture for IoT-based sleep monitoring system Journal of Big Data IoT Time series database Health monitoring Microservice MQTT protocol |
| title | Multiple time series database on microservice architecture for IoT-based sleep monitoring system |
| title_full | Multiple time series database on microservice architecture for IoT-based sleep monitoring system |
| title_fullStr | Multiple time series database on microservice architecture for IoT-based sleep monitoring system |
| title_full_unstemmed | Multiple time series database on microservice architecture for IoT-based sleep monitoring system |
| title_short | Multiple time series database on microservice architecture for IoT-based sleep monitoring system |
| title_sort | multiple time series database on microservice architecture for iot based sleep monitoring system |
| topic | IoT Time series database Health monitoring Microservice MQTT protocol |
| url | https://doi.org/10.1186/s40537-022-00658-4 |
| work_keys_str_mv | AT ekosimanjuntak multipletimeseriesdatabaseonmicroservicearchitectureforiotbasedsleepmonitoringsystem AT nicosurantha multipletimeseriesdatabaseonmicroservicearchitectureforiotbasedsleepmonitoringsystem |