Name
Title | ||
|---|---|---|
Performance analysis of an efficient object-based schema oriented data storage system handling health data |
Abstract | ||
|---|---|---|
Object-based cloud storage system has an important role in handling big data. All available cloud storage systems deal with scalability, reliability or durability issues. However, there is lack of work addressing data variety. In a previous paper, a basic architecture of an object-based schema oriented data storage system has been proposed which stores data in an encapsulated way. The system comprises account layer, container layer, object layer, database layer and schema layer. In this paper, the architecture proposed in our previous paper has been elaborated. For example, the communication protocols of the proposed system are explained. Moreover, this architecture is realized to test its effectiveness on health data in terms of query execution performance and flexibility on the basis of four different queries of database computation (e.g., append, read, aggregate and delete). The result set are collected on three types of datasets (table, document, file) taken from healthcare scenario. Each type of dataset consists of four different sets of data records. The performance is compared with Amazon S3 (i.e., bucket oriented object-based data storage system) and Microsoft Azure (i.e., account-container oriented object-based data storage system). Flexibility property is also analyzed with respect to these three database operations (i.e., READ, WRITE and DELETE) on three types of experimental datasets (table, document, file) with Amazon S3. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1007/s11334-019-00354-2 | Innovations in Systems and Software Engineering |
Keywords | Field | DocType |
Cloud storage system, Schema oriented, Object based, Big data, Benchmark | Result set,Systems engineering,Computer science,Computer data storage,Append,Big data,Schema (psychology),Database,Cloud storage,Communications protocol,Scalability | Journal |
Volume | Issue | ISSN |
16 | 1 | 1614-5046 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Anindita Sarkar Mondal | 1 | 0 | 1.01 |
| Sarmistha Neogy | 2 | 25 | 14.34 |
| Nandini Mukherjee | 3 | 168 | 29.88 |
| Samiran Chattopadhyay | 4 | 174 | 34.02 |