Call for Papers

Aim and Scope

6G, the next generation communication system, is expected to satisfy unprecedented requirements on system performance in terms of throughput, latency, massive connections, and so on. In the 6G era, with the hyper-connectivity among humans and everything, we are anticipating Internet of Things (IoT) applications in various fields, including smart city, smart factory, smart home, smart grid, e-health, and smart transportation, accompanied by new services with rich experiences, such as truly immersive VR/AR/MR (XR), high-fidelity mobile hologram, and digital twins. However, in order to facilitate these emerging IoT applications, we have to discuss the following issues.

First, due to the heterogeneity of networking entities, various application requirements, and limited resources in IoT environments, greener and more advanced networking, caching, and computing technologies are required. Future IoT systems feature a larger number of devices and multi-access environments where different types of wireless spectrum, including Sub-6 GHz, Millimeter-wave, and Terahertz technologies, should be efficiently utilized. At the same time, a resource-efficient task processing architecture should be designed in order to deal with the limited storage and computational capability of mobile devices. All these requirements motivate us to investigate the collaboration among different network entities to achieve joint optimization under heterogeneous communication, caching, and computing resources. As an example, it is crucial to determine the type and amount of data to be shared, stored, and processed among the network entities with heterogeneous characteristics.

Second, the network environment and system requirements change with the space and time domains, which require intelligent approaches in perception, networking, and control. Recently, artificial intelligence (AI) based approaches have been attracting great interest in empowering computer systems. Since the centralized learning approaches face some challenges in terms of scalability, some collaborative learning approaches, such as federated learning and multi-agent systems, have been discussed recently to reduce networking overhead and improve learning efficiency.

Based on refined AI technologies, collaborative intelligence can achieve better decisions by aggregating knowledge and enabling efficient coordination among multiple agents with a light communication overhead. It is envisioned that the collaborative intelligence is the enabler for collaborative IoT systems. For instance, it enables: a) collaborative communications over different types of wireless spectrum among multiple transmitters for improving the spectrum utilization efficiency; b) collaborative caching among multiple network entities for reducing service latency; and c) collaborative computing with a resource-efficient end-edge-cloud task processing framework for satisfying diverse requirements on the tremendous amount of real-time data processing, including extremely large throughput, and ultra-low latency.

In order to enable a greener and smarter society, more research efforts should be conducted on collaborative intelligence for IoT systems to expedite the applications of emerging IoT technologies. An efficient use of cross-domain big data should be discussed, and academic-industrial collaborations should be promoted to solve the existing problems.

Topics

This special issue focuses on the technical challenges for enabling collaborative intelligence in IoT systems toward a greener and smarter society. Prospective authors are invited to submit original manuscripts that advance the state of the art on topics including, but not limited to:

• Agent theory and Green IoT applications in the 6G era
• Cognitive modeling of Green IoT systems in the 6G era
• Collaborative and distributed IoT systems and control
• Collaborative Green IoT frameworks in the 6G era
• Collaborative Green IoT technologies for 6G services
• Collaborative intelligence based on cross-domain big data for Green IoT
• Collaborative intelligence for Green IoT systems
• Collaborative intelligence security of IoT in the 6G era
• Computation-efficient collaborative intelligence approaches for IoT systems in the 6G era
• Data driven collaborative intelligence for Green IoT
• Energy-efficient collaborative intelligence approaches for IoT
• Group decision making for Green IoT systems
• Human-machine cooperation for Green IoT systems
• Intelligent collaborative processing for Green IoT
• Multi-agent systems for Green IoT in the 6G era

Submission Guidelines

Authors need to follow the manuscript format and an allowable number of pages described at the IEEE TGCN Information for Authors page. Please visit the journal submission website at Manuscript Central.

Important Dates

Manuscript Submission: 10 December 2021 10 January 2022 (Extended Deadline)
First Review Results: 10 February 2022
Second Review Results: 30 March 2022
Publication: June 2022

Guest Editors