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The DAEMON H2020 european project develops and implements innovative and pragmatic approaches to Network Intelligence (NI) design that enable high performance, sustainable and extremely reliable zero-touch network system. DAEMON designs an end-to-end NI-native architecture for Beyond 5G (B5G) that fully coordinates NI-assisted functionalities.
While current efforts at integrating NI in mobile networks aim at tweaking machine learning solutions so that they fit networking environments, DAEMON upends the approach, and seeks to update the network architecture so that it natively supports NI operations.
DAEMON designates a concrete list of key network functionalities for which it will devise and implement NI algorithms capable of taking full advantage of the proposed NI-native architecture, and spanning varied planes, domains and operation timescales
DAEMON will challenge current practices in machine learning for network automation, and innovate the way NI is conceived, by leveraging emerging trends in AI and re-thinking how AI is applied to the network infrastructure environment.
DAEMON will provide objective evidences of the advantage of a structured, deep, and sensible integration of NI into network infrastructures. This will be achieved by meeting a comprehensive range of Key Performance Indicators (KPIs) on the performance, reliability and sustainability of the proposed solutions, in realistic experimental or measurement data-driven settings.
DAEMON will produce the necessary standards, patents and contributions to industry fora in order to:
- Attract industry to use the project technology.
- Foster the widespread adoption of the technology beyond the manufacturers and operators of the consortium.
- Protect the project findings to secure the commercial advantage of the project partners.
It will also produce top-quality publications to ensure the long-term impact of the project results on research and development community focused on B5G systems.
NEW @h2020daemon asset from @NEC_EMEA and @TUDELFT in the IEEE International Conference on Communications (@IEEEICC ‘21) titled “Experimental Evaluation of Power Consumption in Virtualized Base Stations": #h2020daemon #H2020 @EU_H2020 @5GPPPRead More
NEW @h2020daemon asset from @IMDEA_Software in the Association for the Advancement of Artificial Intelligence (@AAAI ‘21) titled “CloudLSTM: A Recurrent Neural Model for Spatiotemporal Point-cloud Stream Forecasting": #h2020daemon #H2020 @EU_H2020 @5GPPPRead More
NEW @h2020daemon publication from @InfoUMA in IEEE Internet of Things Journal titled “Energy-efficient Deployment of IoT Applications in Edge-based Infrastructures: A Software Product Line Approach". Access @ZENODO_ORG: #h2020daemon #H2020 @EU_H2020 @5GPPPRead More
NEW @h2020daemon publication from @NEC in IEEE Transactions on Mobile Computing Journal titled “vrAIn: Deep Learning based Orchestration for Computing and Radio Resources in Vran". Available at: #h2020daemon #H2020 @EU_H2020 @5GPPPRead More
NEW @h2020daemon publication from @IMEC in the IEEE/IFIP Int. Workshop on Analytics for Network and Service Management (@AnNet '21) titled “When Deep Learning May Not Be The Right Tool For Traffic Classification": #h2020daemon #H2020 @EU_H2020 @5GPPPRead More