IEEE Wireless Communications and Networking Conference
26–29 March 2023 // Glasgow, Scotland, UK
Wireless Communications for Social Innovation

WS-11: Distributed and Intelligent Edge Computing for 6G Communications

WS-11: Distributed and Intelligent Edge Computing for 6G Communications

Scope
6G networks envision ubiquitous computing and connectivity which will ultimately lead to massive growth in data traffic and billions of edge nodes connected with each other. To avoid delays and single point of failure in huge networks, edge devices are now widely employed for various applications, such as intelligent transportation systems, surveillance, and home automation. However, in many scenarios, sophisticated Artificial Intelligence (AI) algorithms are required consuming significant amount of processing power and occupying large storage size which may exceed the available resources of typical edge devices. To overcome this challenge, recent delay sensitive, distributed, and intelligent trends in computing paradigms such as Tiny Machine Learning, Federated Learning, Mobile Edge Computing, Multiaccess Edge Computing, Fog Computing and Computational Offloading are under research, aiming to optimize latency, computing complexity and resourceful utilization of bandwidth, thus giving rise to a potential research direction of distributed and Intelligent Edge Computing (IEC). Due to significant tasks expected to be handled by edge devices in 6G communications, IEC is deemed to play an important role. This workshop aims invites researchers from industry and academia to share their recent findings and views on technical advances in IEC and distributed communications. Potential topics include but are not limited to:

  • IEC solutions for Beyond 5G (B5G) and 6G communication networks
  • Distributed or collaborative intelligence for B5G and 6G communication networks, such as federated learning and Tiny Machine learning
  • Over-the-air (OTA) or online learning and inference
  • AI based edge computing resource allocation and management
  • Communication protocol design for IEC
  • Security, privacy, and trust in IEC
  • Intelligent computation offloading
  • Mobility management of edge computing devices
  • Joint optimization of computing, network, and storage resources of edge devices
  • Quality of Service (QoS) aware computation offloading in edge devices
  • Key scenarios/applications for distributed IEC and communications (e.g., connected vehicles, UAVs, metaverse)
  • Testbeds and simulation platforms for IEC
  • Energy efficiency in IEC
  • Latency or bandwidth management in IEC
  • Limitations or challenges of distributed edge intelligence
  • LThe combination of latest trends such as blockchain, big data, quantum communications, smart grid with edge computing

Patrons