Abstract
![CDATA[Existing platforms fall short in providing effective solutions for big data analytics while the demands for processing large quantities of data in real-time are increasing. Moving data analytics towards where the data is generated and stored could be a solution for addressing this issue. In this paper, we propose a solution referred as FOG-engine, which is integrated into IoTs near the ground and facilitates data analytics before offloading large amounts of data to a central location. In this work, we introduce a model for data analytic using FOG-engines and discuss our plan for evaluating its efficacy in terms of several performance metrics such as processing speed, network bandwidth, and data transfer size.]]
| Original language | English |
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| Title of host publication | DASC-PICom-DataCom-CyberSciTech 2016: Proceedings of 2016 IEEE Cyber Science and Technology Congress (CyberSciTech 2016), 2016 IEEE 14th International Conference on Dependable, Autonomic and Secure Computing (DASC 2016), 2016 IEEE 14th International Conference on Pervasive Intelligence and Computing (PICom 2016), and 2016 IEEE 2nd International Conference on Big Data Intelligence and Computing (DataCom 2016), 8-10 August 2016, Auckland, New Zealand |
| Publisher | IEEE |
| Pages | 640-646 |
| Number of pages | 7 |
| ISBN (Print) | 9781509040650 |
| DOIs | |
| Publication status | Published - 2016 |
| Event | IEEE International Conference on Big Data Intelligence and Computing - Duration: 8 Aug 2016 → … |
Conference
| Conference | IEEE International Conference on Big Data Intelligence and Computing |
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| Period | 8/08/16 → … |
Keywords
- big data
- cloud computing
- internat of things