6 citations · 14 across the 7 of their papers we have counts for
7 papers
PolyLink: A Blockchain Based Decentralized Edge AI Platform for LLM Inference
Hongbo Liu, Jiannong Cao, Bo Yang +7
The rapid advancement of large language models (LLMs) in recent years has revolutionized the AI landscape. However, the deployment model and usage of LLM services remain highly cen…
Resource-efficient Parallel Split Learning in Heterogeneous Edge Computing
Mingjin Zhang, Jiannong Cao, Yuvraj Sahni +2
Edge AI has been recently proposed to facilitate the training and deployment of Deep Neural Network (DNN) models in proximity to the sources of data. To enable the training of larg…
High-efficiency Blockchain-based Supply Chain Traceability
Hanqing Wu, Shan Jiang, Jiannong Cao
Supply chain traceability refers to product tracking from the source to customers, demanding transparency, authenticity, and high efficiency. In recent years, blockchain has been w…
ENTS: An Edge-native Task Scheduling System for Collaborative Edge Computing
Mingjin Zhang, Jiannong Cao, Lei Yang +3
Collaborative edge computing (CEC) is an emerging paradigm enabling sharing of the coupled data, computation, and networking resources among heterogeneous geo-distributed edge node…
EaaS: A Service-Oriented Edge Computing Framework Towards Distributed Intelligence
Mingjin Zhang, Jiannong Cao, Yuvraj Sahni +3
Edge computing has become a popular paradigm where services and applications are deployed at the network edge closer to the data sources. It provides applications with outstanding…
Hierarchical Reinforcement Learning with Opponent Modeling for Distributed Multi-agent Cooperation
Zhixuan Liang, Jiannong Cao, Shan Jiang +2
Many real-world applications can be formulated as multi-agent cooperation problems, such as network packet routing and coordination of autonomous vehicles. The emergence of deep re…
From Multi-agent to Multi-robot: A Scalable Training and Evaluation Platform for Multi-robot Reinforcement Learning
Zhiuxan Liang, Jiannong Cao, Shan Jiang +3
Multi-agent reinforcement learning (MARL) has been gaining extensive attention from academia and industries in the past few decades. One of the fundamental problems in MARL is how…