Abstract
With increased deployment of IoT application on cloud platforms, assessing the performance of such application is an open problem. Currently, approaches are limited to legacy database-based applications and does not cater for the needs of IoT applications. This paper proposes, implements and validates a framework namely, IoTQGen, that can generate situation-based queries to conduct performance evaluation of IoT application hosted by cloud IoT middleware platform. The framework comprises: (i) a model to capture the query requirements of IoT applications; (ii) a data generator to generate IoT data based on specified configuration; and (iii) a set of queries designed to represent data analytic IoT applications. The framework supports different query types that can be typically used to represent and address IoT application scenarios. An important functionality of the framework is its ability to issue queries based on dynamic changes in the state of IoT entities (situations). The framework is evaluated based on two smart city use cases to highlight how the framework can be used to generate complex and dynamic queries tailored for IoT application scenarios.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2023 24th IEEE International Conference on Mobile Data Management, IEEE MDM 2023 |
| Editors | Federico Montori, Zimu Zhou, Edison Tsz Nam Chan |
| Place of Publication | Piscataway NJ USA |
| Publisher | IEEE, Institute of Electrical and Electronics Engineers |
| Pages | 352-357 |
| Number of pages | 6 |
| ISBN (Electronic) | 9798350341010 |
| ISBN (Print) | 9798350341027 |
| DOIs | |
| Publication status | Published - 2023 |
| Event | Workshop on IoT-Crowdsensing for Smart Cities 2023 - Singapore, Singapore Duration: 3 Jul 2023 → 6 Jul 2023 Conference number: 2nd https://sites.google.com/view/iotsencity2023/home (Website) https://ieeexplore.ieee.org/xpl/conhome/10214688/proceeding (Proceedings) |
Publication series
| Name | Proceedings - IEEE International Conference on Mobile Data Management |
|---|---|
| Publisher | IEEE, Institute of Electrical and Electronics Engineers |
| Volume | 2023-July |
| ISSN (Print) | 1551-6245 |
| ISSN (Electronic) | 2375-0324 |
Conference
| Conference | Workshop on IoT-Crowdsensing for Smart Cities 2023 |
|---|---|
| Abbreviated title | IoTSenCity 2023 |
| Country/Territory | Singapore |
| City | Singapore |
| Period | 3/07/23 → 6/07/23 |
| Internet address |
Keywords
- benchmarks
- cloud platforms
- IoT
- IoT middlewares
- IoT queries
- performance evaluation
- situations
