Important Dates
Paper Submission Deadline: 20 January 2021 19 February 2021 [FIRM]
Notification of Acceptance: 20 February 2021 22 March 2021
Camera-ready Papers: 1 March 2021 31 March 2021 8 April 2021 (FIRM)
The first DDINS: https://icc2019.ieee-icc.org/w
The second DDINS: https://infocom2020.ieee-infoc
Paper submission link: https://www.edas.info/newPaper.php?c=27867
The extended selected accepted papers in this workshop will be recommended for publications in Series on Data Driven Intelligence, Sustainability, and Systems, Intelligent and Converged Networks （journal jointly published by International Telecommunication Union (ITU) and Tsinghua University Press (TUP)）http://icn.tsinghuajournals.com/EN/column/item1649.shtml
Network traffic is expected to grow exponentially in the next decade thanks to the advances in smart devices, Internet of Things (IoT) and cloud computing. Not only the volume of the traffic is increasing, the characteristics of the traffic are also becoming more diverse. To properly manage traffic diversity, different but coherent strategies are needed at different protocol layers, and this often results in complex designs in the network which are difficult to deploy and manage. The recent advancement in artificial intelligence (AI) technology has provided a promising approach to deal with complex problems faced in the network and/or systems design and operation. The trend towards highly integrated networks with diverse underlying access technologies to support simultaneously multiple vertical industries has demanded complex operation in the network and/or systems. This represents a great challenge in network and/or systems design.
This Workshop focuses on applying AI technologies to deal with the networks and/or systems, particularly the machine learning techniques that are based on empirical or simulated data. Topics that may apply data driven intelligence to manage the complexity of a smart networks and/or systems include, but not limited to:
- Data driven intelligence supported approaches and technologies
- Data driven intelligence supported applications and systems
- Quality of Service (QoS) and Quality of Experience (QoE) support
- Resource allocation and transmission scheduling
- Medium access control design
- Data centers and cloud systems
- Radio access technology selection
- Spectrum sharing in intra- and inter-tier HetNets
- Traffic load estimation and resource reservation
- User mobility prediction and handover support
- Network fault detection and self-healing
- Network self-configuration and self-organization
- Intrusion detection and self-protection
- Machine learning relevant topics
- Relevant analysis and modelling
- Relevant surveys
