Near Real-Time Big-Data Processing for Data Driven Applications

2017 International Conference on Big Data Innovations and Applications (Innovate-Data 2017): Proceedings 2018
Jānis Kampars, Jānis Grabis

This paper addresses the context data integration and processing problem for design of data driven application by introducing ASAPCS (Auto-scaling and Adjustment Platform for Cloud-based Systems) platform. Conceptual model, technical architecture and data integration process are described. The ASAPCS platform supports model-driven configuration, separation of context acquisition and application, utilization of various context processing algorithms and scalability. It is based on technologies that have proven to work well with big data and each part of it is horizontally scalable. ASAPCs integrates data from heterogeneous sources and aggregates raw context data and uses it to perform real-time adjustments in the data-driven application. Its application is illustrated with example of providing data store resilience.

Atslēgas vārdi
big datacloud computingdata-driven systemsstream processing
DOI
10.1109/Innovate-Data.2017.11
Hipersaite
https://ieeexplore.ieee.org/document/8316297

Kampars, J., Grabis, J. Near Real-Time Big-Data Processing for Data Driven Applications. No: 2017 International Conference on Big Data Innovations and Applications (Innovate-Data 2017): Proceedings, Čehija, Prague, 21.-23. augusts, 2017. Piscataway: IEEE, 2018, 35.-42.lpp. ISBN 978-1-5386-0961-3. e-ISBN 978-1-5386-0960-6. Pieejams: doi:10.1109/Innovate-Data.2017.11

Publikācijas valoda
English (en)