Lyapunov-based lightweight AI agent achieves O(N) complexity for joint PQC-NOMA allocation in edge systems, with claimed 46x speedup over SCA and improved throughput in simulations.
Dnn partitioning, task offloading, and resource allocation in dynamic vehicular networks: A lyapunov-guided diffusion-based rein- forcement learning approach,
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The paper introduces CoCaR for joint submodel caching and request routing with dynamic DNNs in MEC, reporting 46% higher average inference precision in simulations and at least 32.3% QoE gain for its online variant.
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Lightweight Quantum Agent for Edge Systems: Joint PQC and NOMA Resource Allocation
Lyapunov-based lightweight AI agent achieves O(N) complexity for joint PQC-NOMA allocation in edge systems, with claimed 46x speedup over SCA and improved throughput in simulations.
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Joint Optimization of DNN Model Caching and Request Routing in Mobile Edge Computing
The paper introduces CoCaR for joint submodel caching and request routing with dynamic DNNs in MEC, reporting 46% higher average inference precision in simulations and at least 32.3% QoE gain for its online variant.