Exploring Netgptenabled Dynamic Resource Management For Mobile D2d In Industrial Iot Baotong Chen Haiquan Liang Jiafu Wan Chuangjian Wang Xuguo Yan Xuhui Xia Salman A Alqahtani by Baotong Chen & Haiquan Liang & Jiafu Wan & Chuangjian Wang & Xuguo Yan & Xuhui Xia & Salman A. Alqahtani 101109/MNET20253532655 instant download after payment.

Abstract—AI large model-centered intelligent applications ChatGPT to Sora [1-3]. Device-to-Device (D2D) holds promises to revolutionize network quality of service (QoS).communication enables direct interaction between mobile therefore, the deployment and utilization of such models in the devices without routing through a Base Station (BS) or core Industrial Internet of Things (Industrial IoT) are considered asnetwork [4]. The Industrial IoT environment is reflected by a an increasingly pressing priority. In particular, the integration of significant number of D2D terminals. Modern 5G smart Generative AI (GenAI) into Industrial IoT, with a focus on factory should accommodate millions of connection requests, establishing a robust NetGPT network architecture that leverages Mobile Edge Computing (MEC) and Device-to-Device and the widespread D2D access inevitably leads to increased (D2D) collaboration has been subjected to significant academic signaling overhead and computational delays. Mobile devices attention. Accordingly, this paper explores the optimization of such as AGVs and transfer robots exhibit high power dynamic network resource management in mobile D2D networks consumption, significant data transmission volumes, varied through the innovative application of NetGPT. First, a NetGPTdata types, and significant mobility during operation. based system architecture for network resource management is Accordingly, the communication continuity of D2D proposed. Thereafter, mobile D2D network model is established with a detailed account of NetGPT training and NetGPT fusion. communication in this context poses significant challenges for Finally, the workload scheduling strategy in industrial IoT based network resource management in the Industrial IoT on Stackelberg game model is formulated though multi-agent ecosystem.GenAI and present the NetGPT-based orchestration of task coGenAI models incorporate parameters numbering in the offloading for mobile network nodes.…