-------- Weitergeleitete Nachricht -------- Betreff: [TCCC-ANNOUNCE] CFP: China Communications (IF: 1.514) Feature Topic on “Collaborative Intelligence for Vehicular Internet of Things “ Datum: Thu, 11 Jun 2020 10:57:33 +0900 Von: Celimuge Wu celimuge@UEC.AC.JP Antwort an: Celimuge Wu celimuge@UEC.AC.JP An: tccc-announce@comsoc.org
Call for Papers -- China Communications Feature Topic, Vol.18, No.7, 2021 Collaborative Intelligence for Vehicular Internet of Things
http://www.cic-chinacommunications.cn/EN/column/item153.shtml
Future vehicular Internet-of-Things (IoT) systems feature a large number of devices and multi-access environments where different types of communication, computing, and storage resources must be efficiently utilized. At the same time, novel services, such as cooperative autonomous driving and intelligent transport systems (ITS), that demand unprecedented high accuracy, ultra-low latency, and large bandwidth, are emerging. These services also have an extreme variance in user requirements and resource demands with respect to time, location, and context. Hence, current research is no longer confined to improving reliable communication and system operation in the presence of highly mobile vehicles, which has been the main focus in the past. It is therefore important to empower future vehicular IoT systems with advanced features, such as real-time reactive and proactive cooperation and coordination among different agents (or decision makers), including vehicles, roadside units, base stations, pedestrians, and other entities.
Recently, artificial intelligence (AI) based approaches have been attracting great interest in empowering computer systems. Some collaborative learning approaches, such as federated learning and multi-agent systems, have been used to reduce network traffic and improve learning efficiency of some smartphone applications. In vehicular IoT systems, collaborative intelligence can be achieved via an efficient collaboration among heterogeneous entities, including vehicles, edges, and cloud. This special issue will focus on the technical challenges and the synergistic effect of collaboration among heterogeneous entities and AI in enabling intelligent perception of environment, intelligent networking, and intelligent processing of big data in vehicular IoT systems. We invite researchers to contribute their original research articles that will facilitate the development of vehicular IoT based on collaborative intelligence.
SCHEDULE Submission Deadline: October 15, 2020 Acceptance Notification (1st round): December 5, 2020 Minor Revision Due: February 5, 2021 Final Decision Due: March 5, 2021 Final Manuscript Due: April 5, 2021 Publication Date: July 15, 2021
GUEST EDITORS Celimuge Wu, The University of Electro-Communications, Japan Kok-Lim Alvin Yau, Sunway University, Malaysia Carlos Tavares Calafate, Technical University of Valencia, Spain Lei Zhong, Toyota Motor Corporation, Japan
TOPICS OF INTEREST INCLUDE, BUT ARE NOT LIMITED TO, THE FOLLOWING:
· Collaborative intelligence for sensing and perception in vehicular IoT · Collaborative intelligence for vehicular networking · Collaborative intelligence for task processing in vehicular IoT · Collaborative architecture for vehicular IoT · Collaborative learning approaches for vehicular environments · Collaborative sensing, networking, and computing for intelligent vehicular IoT · Security and privacy issues for collaborative intelligence in vehicular IoT · Federated learning for vehicular IoT · Multi-agent systems for vehicular IoT · AI-based approaches for collaborative resource allocations in vehicular IoT
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