International Workshop on Data Driven Intelligence for Networks and Systems
摘要截稿:
全文截稿: 2019-01-25
开会时间: 2019-05-20
会议难度:
CCF分类: 无
会议地点: Shanghai, China
Overview
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. While many advanced communication technologies have been proposed to push up the network capacity, increasing capacity alone is inadequate to deal with the traffic diversity. 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 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. This represents a great challenge in network design. This Workshop focuses on applying AI technologies to deal with the design complexity in wireless networks, 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 wireless network include, but not limited to:
Quality of Service (QoS) and Quality of Experience (QoE) support
Radio 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