LLM-Driven Agentic AI in Edge-Cloud Computing
A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Internet of Things".
Deadline for manuscript submissions: 20 August 2026 | Viewed by 18
Special Issue Editors
Interests: computer communication networks; future internet architecture; edge and cloud computing; decentralized machine learning; agentic AI and agentic web
Special Issues, Collections and Topics in MDPI journals
Interests: edge-cloud computing; edge intelligence; big data architecture; internet of things; distributed systems
Special Issues, Collections and Topics in MDPI journals
Interests: large language models for industry; agentic models for industry
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The recent rapid development of artificial intelligence has led to the emergence of the agentic AI paradigm, in which LLM-driven AI agents regularly perceive environmental dynamics, autonomously make decisions, and promptly take actions with minimal human intervention. Furthermore, AI agents may form multi-agent systems that allow collective intelligence to emerge through agent interactions. Simultaneously, the latest advances in networking technologies enable the convergence of edge and cloud computing, providing an infrastructure that comprises a device–edge–network–cloud consortium upon which various agentic AI systems will be deployed. The synergy of agentic AI and converged edge–cloud computing leads to a vision of the agentic Web—the next evolution of the Internet that integrates agentic AI systems and applications with the underlying computing and networking infrastructures, therefore forming a promising research area that is attracting increasing attention from both academia and industry.
This Special Issue aims to present the latest research progress on the intersection of agentic AI and converged edge–cloud computing. Interesting topics include, but are not limited to, the following:
- LLM training and deployment for agentic AI;
- Agentic AI system architecture and mechanisms;
- Agentic AI for industry;
- Resource-aware multi-agent system design;
- Agent coordination and orchestration in edge–cloud computing;
- Agent communication technologies and protocols;
- Edge–cloud computing for supporting agentic AI systems;
- Reliability, security, and trustworthiness of agentic AI systems in edge–cloud computing;
- Applications of agentic AI systems in a converged edge–cloud computing environment.
Prof. Dr. Qiang Duan
Prof. Dr. Zhihui Lu
Prof. Dr. Jiehan Zhou
Guest Editors
Manuscript Submission Information
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Keywords
- large language model
- agentic AI
- industrial agent
- agentic web
- multi-agent system
- agent orchestration
- agent protocols
- edge–cloud computing
- edge intelligence
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