This paper studies task offloading in infrastructure-free mobile edge computing (MEC), where end devices must autonomously discover candidate servers and make offloading decisions under dynamic connectivity and time-varying computing resources. However, the lack of centralized coordination incurs high overhead to acqui...
Xiang Li, Wen-Bin Xu, Shan Zhang et al.· IEEE Transactions on Mobile...· 0 citations
The incorporation of Mobile Edge Computing into satellite systems is a highly promising approach to enabling large-scale intelligent Internet of Things services in remote areas. However, the high-speed mobility of satellites and the extreme scarcity of on-board resources pose significant challenges, as traditional reac...
Hao-Yuan Deng, Ning-Ning Cui, Shi Chen et al.· 2026 IEEE/CIC International...· 0 citations
LFRI employs a lock-free installation mechanism that enables parallelized and efficient route installation, and reduces the route installation latency by up to 99.9% in emulations of typical LEO satellite constellations, within a performance level comparable to routing installation on physical machines.
Wenhao Lu, Zhiyuan Wang, Shan Zhang et al.· Asia-Pacific Workshop on Net...· 0 citations
A heterogeneous resource allocation strategy for cross-high and low orbit mixed satellite networks is proposed, which takes dynamic communication service demands as input and collaboratively allocates beam bandwidth, frequency, time slot, power and inter-satellite links and other heterogeneous resources.
Zhi-Hao Wang, Hongbin Luo, Zhiyuan Wang et al.· Peer-to-Peer Networking and...· 0 citations
Deploying large language models (LLMs) on edge nodes enables low-latency and privacy-preserving inference, but faces severe resource constraints under high-concurrence workloads. While existing inference systems leverage intranode key–value (KV) caching to improve efficiency, they largely neglect the unique complexitie...
Xishuo Li, Wei Jiao, Jun He et al.· IEEE Internet of Things Jour...· 0 citations
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