The rapid proliferation of data-intensive and delay-sensitive applications has accelerated the evolution from centralized cloud computing to mobile edge-cloud systems. However, the decentralized and heterogeneous characteristics introduce instability and complexity, making efficient scheduling increasingly challenging....
Yun-Feng Zhao, Chao Qiu, Xiao-Fei Wang et al.· IEEE Transactions on Mobile...· 0 citations
Retrieval-augmented generation (RAG) improves factuality by conditioning LLMs on retrieved evidence, yet real-world knowledge is often split across tiers: cloud-based RAG can exploit large public corpora, whereas edge-based RAG is the natural place to access private, user-specific stores. This raises a key question: ho...
Yuting Li, Shaoyuan Huang, Xiangqi Liu et al.· Proceedings of the 32nd ACM...· 0 citations
The surge of large language model (LLM) applications on personal devices imposes massive, bursty workloads on cloud serving infrastructure. While prefill-decode disaggregation improves throughput and scalability, memory-bound decode instances often suffer from persistent load imbalance, as output lengths are unknown wh...
Tian-Cheng Zhang, Yulin Chen, Yun-Feng Zhao et al.· 0 citations
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