Small data in iot: An mcs perspective
| Author | Azmy, Sherif B. |
| Author | Sneineh, Ruslan Abu |
| Author | Zorba, Nizar |
| Author | Hassanein, Hossam S. |
| Available date | 2024-07-14T07:57:24Z |
| Publication Date | 2019 |
| Publication Name | EAI/Springer Innovations in Communication and Computing |
| Resource | Scopus |
| Identifier | http://dx.doi.org/10.1007/978-3-319-93557-7_11 |
| ISSN | 25228595 |
| Abstract | The unprecedented advances in wireless technology have led to the development of the IoT and numerous associated sub-paradigms, such as wireless sensor networks (WSNs), software-defined networks, mobile crowdsensing (MCS), and others. In this book chapter, we provide the reader an overview of the significance of small-scale data in the IoT within the bounds of the MCS paradigm. We motivate the scenarios where small data might exist, and we discuss its susceptibility to the errors. We provide the reader with a thorough investigation of the impact of one-sided outliers on small data sets. In addition, we present some of the potential techniques to deal with the outliers, making small data robust to errors and thus applicable to practical scenarios. |
| Sponsor | Acknowledgements This work was made possible by NPRP grant NPRP 9-185-2-096 from the Qatar National Research Fund (a member of the Qatar Foundation). The statements made herein are solely the responsibility of the authors. |
| Language | en |
| Publisher | Springer |
| Subject | Abnormal Outliers Breakdown Point Mobile Crowdsensing (MCS) Small Data Problem Spatiotemporal Cell |
| Type | Book chapter |
| Pagination | 209-229 |
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Electrical Engineering [2544 items ]