Driven by the ongoing advancement of intelligent transportation systems (ITSs), conventional vehicular networks have rapidly evolved into a data-intensive vehicular Internet of Things (IoT) ecosystem. However, relying on traditional bit-level offloading in unmanned aerial vehicle (UAV)-assisted IoT networks creates sev...
Xiao-Teng Yang, Jie Feng, Li-Chuan Ma et al.· IEEE Internet of Things Jour...· 0 citations
With the rapid development of the Internet of Things (IoT) and edge computing, the scale and complexity of modern networks have increased significantly, driving the demand for distributed fault diagnosis. Federated learning (FL) effectively addresses the issues of data privacy and dispersion by enabling edge devices to...
Jing-Ting Mei, Yang Yang, Celimuge Wu et al.· IEEE Transactions on Cogniti...· 0 citations
High-capacity satellite network is the cornerstone of future space-air-ground integrated networks. However, the satellite uplink transmissions still face critical challenges, including severe path loss, complex multi-user interference, and payload constraints. Recently, Reconfigurable Intelligent Surfaces (RIS) and Flu...
Kai Feng, Runke Fan, Tianheng Xu et al.· IEEE Open Journal of the Com...· 0 citations
Timely anomaly detection in Industrial Internet of Things (IIoT) monitoring requires robust modeling of noisy multivariate sensor streams. Although decomposition-derived residuals provide a potentially useful auxiliary view for multivariate time-series anomaly detection (MTSAD), they are not clean anomaly surrogates in...
Guangxia Xu, Zhuo Ye, Xing Huang et al.· IEEE Internet of Things Jour...· 0 citations
Root cause localization is critical for ensuring service reliability in cloud-edge collaborative microservice systems. In practical scenarios, multiple microservice systems are often hybrid-deployed on shared infrastructure, which poses three challenges for existing methods. First, concurrent systems generate substanti...
Yechen He, Yang Yang, Lanlan Rui et al.· IEEE Transactions on Cogniti...· 0 citations
Artificial Intelligence-Generated Content (AIGC) has developed rapidly, with Diffusion Models (DMs) gaining wide attention for their superior image generation capabilities. However, the high computational cost of inference limits their deployment in resource-constrained environments such as edge computing. Cloud-edge c...
Yu Song, Yin-Lin Ren, Shao-Yong Guo et al.· IEEE Transactions on Cogniti...· 0 citations
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