Fog Context Analytics
| Main Authors: | Nikos Papageorgiou, Yiannis Verginadis, Dimitris Apostolou, Gregoris Mentzas |
|---|---|
| Format: | Article eJournal |
| Terbitan: |
, 2019
|
| Online Access: |
https://zenodo.org/record/3559694 |
Daftar Isi:
- Context prediction, enabled by applying machine learning techniques on sensor measurements, is crucial for efficient auctioning and effective decision making in complex measurement systems and computing infrastructures such as fog topologies. As environmental concerns for green and low-power computing grow, the accurate classification and prediction of fog device context which is an enabler of fog infrastructure management becomes a necessity. Context prediction can support DevOps in making decisions that minimize resource utilization and power consumption while maintaining QoS. FCA enhances raw context data with inferred or predicted values of context features while avoiding machine-learning feature engineering when possible.