Edge-LLM Inference With Cost-Aware Layer Allocation and Adaptive Scheduling
This paper addresses two key challenges in distributed Large Language Model (LLM) inference at the edge: 1) cost-efficient and fair task allocation, and 2) dynamic scheduling under deadline constraints. We propose two mechanisms: the Fair Cost-Efficient Incentive Mechanism (FCIM) for task and layer...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11095716/ |
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