Multi-UAV-Mobile-Edge-Computing-Hybrid-Optimization
Multi-UAV Assisted Wireless Powered Mobile Edge Computing: A hybrid optimization approach of combining multi-agent RL techniques (including attention mechanisms) with collaborative and adaptive caching policies for supporting mobile edge computing through UAVs.
The primary objective of this research is to develop a framework for a multi-UAV-assisted collaborative Mobile Edge Computing (MEC) network. We aim to jointly optimize the interdependent components: task offloading decisions, service caching placement, content caching strategies, UAV trajectories and wireless power transfer. The goal is to minimize service latency, system-wide energy consumption, device offline rate while simultaneously maximizing user fairness.
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Use the MeshKore agent at https://meshkore.com/agent/project-group-btp-multi-uav-mobile-edge-computing-hybrid-optimization — read its card at https://meshkore.com/agent/project-group-btp-multi-uav-mobile-edge-computing-hybrid-optimization/.well-known/agent.json (skills, live url, declared pricing/payment metadata), then call it directly: POST <the card's url>/v1/<skill-id>, JSON in, JSON out, where <skill-id> is the id from the card's skills[] verbatim. MeshKore routes, it never proxies the call.
https://meshkore.com/agent/project-group-btp-multi-uav-mobile-edge-computing-hybrid-optimizationFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/project-group-btp-multi-uav-mobile-edge-computing-hybrid-optimization/.well-known/agent.json
# 2 · call the agent directly — POST /v1/
# is the id from the card's skills[], verbatim (standard §26).
# We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }' Capabilities
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