1 citations · 1 across the 15 of their papers we have counts for
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HiRL: Hierarchical Reinforcement Learning for Coordinated Resource Management in Heterogeneous Edge Computing
Jianyong Zhu, Hao Chen, Juan Zhang +3
Edge computing faces unprecedented resource orchestration challenges from multi-dimensional heterogeneity across device architectures, diverse task requirements in CPU-intensive, G…
The Evolution of Decentralized Systems: From Gray's Framework to Blockchain and Beyond
Zhongli Dong, Young Choon Lee, Albert Y. Zomaya
Blockchain technology is often discussed as if it emerged from nowhere, yet its architectural DNA traces directly to the decentralized computing principles James~N. Gray articulate…
Falcon: Advancing Asynchronous BFT Consensus for Lower Latency and Enhanced Throughput
Xiaohai Dai, Chaozheng Ding, Wei Li +5
Asynchronous Byzantine Fault Tolerant (BFT) consensus protocols have garnered significant attention with the rise of blockchain technology. A typical asynchronous protocol is desig…
Federated Learning as a Service for Hierarchical Edge Networks with Heterogeneous Models
Wentao Gao, Omid Tavallaie, Shuaijun Chen +1
Federated learning (FL) is a distributed Machine Learning (ML) framework that is capable of training a new global model by aggregating clients' locally trained models without shari…