Scope
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 system. Not only the volume of the traffic is increasing, the characteristics of the traffic are also becoming more diverse. While many advanced communication technologies and novel system architecture have been proposed to push up the system performance and network capacity, increasing complexity has led to management difficulty. To properly manage system and network complexity, different but coherent strategies are needed at different protocol layers which challenge the traditional design based on human intelligence. The recent advancement in artificial intelligence (AI) technology has provided a promising approach to deal with complex problems faced in the network design and operation.
The trend towards highly integrated systems and networks with diverse underlying access technologies to support simultaneously multiple vertical industries has demanded complex operation in the network. This represents a great challenge in the system and network design. This workshop focuses on applying AI technologies to deal with the design complexity in various types of networks and systems, particularly the machine learning techniques that are based on empirical or simulated data.
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We seek original completed and unpublished work not currently under review by any other journal/ magazine/conference. Topics of interest include, but are 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
- Network self-configuration and self-organization
- Intrusion detection and self-protection
- Green communication and networks
- Relevant surveys
Workshop Web Page
https://ddinsws.wordpress.com/
Important Dates
- Workshop Paper Submission Deadline: 20 January 2024
- Paper Acceptance Notification: 6 March 2024
- Camera Ready: 15 March 2024
- Accepted Author Registration Deadline: 15 March 2024
Submission Link
https://ws03icc2024workshop-ddins.edas.info/
Workshop Chairs
- Chee Yen (Bruce) Leow, Universiti Teknologi Malaysia, Malaysia (bruceleow@utm.my)
- Chuan Heng Foh, University of Surrey, UK (c.foh@surrey.ac.uk)
- Lingjia Liu, Virginia Polytechnic Institute and State University, USA (ljliu@vt.edu)
