5 papers
Matching-with-Contracts for the AI-RAN Market: AIGC-as-a-Service for Teleoperation
Zijun Zhan, Yaxian Dong, Daniel Mawunyo Doe +3
Artificial intelligence radio access networks (AI-RANs) are a promising architecture for bolstering the prosperity of the edge AI ecosystem. A well-designed incentive mechanism can…
CASTER: Breaking the Cost-Performance Barrier in Multi-Agent Orchestration via Context-Aware Strategy for Task Efficient Routing
Shanyv Liu, Xuyang Yuan, Tao Chen +5
Graph-based Multi-Agent Systems (MAS) enable complex cyclic workflows but suffer from inefficient static model allocation, where deploying strong models uniformly wastes computatio…
Learning to Incentivize: LLM-Empowered Contract for AIGC Offloading in Teleoperation
Zijun Zhan, Yaxian Dong, Daniel Mawunyo Doe +4
With the rapid growth in demand for AI-generated content (AIGC), edge AIGC service providers (ASPs) have become indispensable. However, designing incentive mechanisms that motivate…
A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms
Zijun Zhan, Yaxian Dong, Daniel Mawunyo Doe +4
Vertical Federated Learning (VFL)-based Traffic State Estimation (TSE) offers a promising approach for integrating vertically distributed traffic data from municipal authorities (M…
Distributionally Robust Contract Theory for Edge AIGC Services in Teleoperation
Zijun Zhan, Yaxian Dong, Daniel Mawunyo Doe +5
Advanced AI-Generated Content (AIGC) technologies have injected new impetus into teleoperation, further enhancing its security and efficiency. Edge AIGC networks have been introduc…