Conference paper Open Access
PrEstoCloud: Proactive Cloud Resources Management at the Edge for Efficient Real-Time Big Data Processing
Verginadis, Yiannis; Alshabani, Iyad; Mentzas, Gregoris; Stojanovic, Nenad
Among the greatest challenges of cloud computing is to automatically and efficiently exploit infrastructural resources in a way that minimises cloud fees without compromising the performance of resource demanding cloud applications. In this aspect the consideration of using processing nodes at the edge of the network, increases considerably the complexity of these challenges. PrEstoCloud idea encapsulates a dynamic, distributed, self-adaptive and proactively configurable architecture for processing Big Data streams. In particular, PrEstoCloud aims to combine real-time Big Data, mobile processing and cloud computing research in a unique way that entails proactiveness of cloud resources use and extension of the fog computing paradigm to the extreme edge of the network. The envisioned PrEstoCloud solution is driven by the microservices paradigm and has been structured across five different conceptual layers: i) Meta-management; ii) Control; iii) Cloud infrastructure; iv) Cloud/Edge communication and v) Devices, layers.
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Presto v2.1.pdf
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| Data volume | 8.0 MB | 8.0 MB |
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- Publication date:
- January 1, 2017
- DOI:
-
- Keyword(s):
- Big Data Processing Dynamic Resources Management Edge Computing
- Grants:
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European Commission:
- PrEstoCloud - PrEstoCloud - Proactive Cloud Resources Management at the Edge for Efficient Real-Time Big Data Processing (732339)
- License (for files):
- Creative Commons Attribution Share Alike 4.0 International