Design and Evaluation of Lifelog Mashup Platform with NoSQL Database

Abstract

To support mashup of heterogeneous lifelog services, we have previously implemented the lifelog common data model (LLCDM). The previous LLCDM was implemented with MySQL, where various types of application-specific data (e.g., numeric values, text, JSON or XML) were all stored in a column in a schemaless text format. Any query with application-specific data had to be managed by individual applications. It had also a scalability issue as the data size grew. To cope with the limitations, this paper re-engineers the LLCDM with MongoDB NoSQL database. We extensively use the document-oriented semi-strucuted data schema of MongoDB for representing the column. We also re-implement Web-API for the LLCDM which allows queries with both application-specific and neutral attributes. We evaluate performance and complexity of the new system through application development with real sensor data.