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Author

Muhammad Rafid

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4 papers indexed here

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#reinforcement learning Open access Oct 2026

Coordinated Offloading Cooperative Multi-Agent Reinforcement Learning for the Edge–Cloud Continuum

The increasing demand for intelligent, low-latency services in edge–cloud continuum systems poses new challenges for dynamic and efficient task offloading. We propose a Multi Agent Reinforcement Learning (MARL) framework for dis tributed task offloading under partial observability, where each device offloads only a por...

Muhammad Rafid, Golshan Famitafreshi, V. Avgerinos et al. · 0 citations
#reinforcement learning Open access Oct 2026

Coordinated Offloading Cooperative Multi-Agent Reinforcement Learning for the Edge–Cloud Continuum

The increasing demand for intelligent, low-latency services in edge–cloud continuum systems poses new challenges for dynamic and efficient task offloading. We propose a Multi Agent Reinforcement Learning (MARL) framework for dis tributed task offloading under partial observability, where each device offloads only a por...

Muhammad Rafid, Golshan Famitafreshi, V. Avgerinos et al. · 0 citations
#edge computing Open access Sep 2026

Personalized Privacy-Aware MARL Offloading in the Edge-Cloud Continuum

Task offloading in End–Edge–Cloud computing enables resource-constrained User Devices (UDs) to execute computation-intensive applications with reduced latency and energy consumption. However, existing task offloading schemes generally overlook the heterogeneous privacy requirements of users, leading to inefficient priv...

Muhammad Rafid, Golshan Famitafreshi, Kostas Ramantas et al. · 0 citations
#edge computing Open access Sep 2026

Personalized Privacy-Aware MARL Offloading in the Edge-Cloud Continuum

Task offloading in End–Edge–Cloud computing enables resource-constrained User Devices (UDs) to execute computation-intensive applications with reduced latency and energy consumption. However, existing task offloading schemes generally overlook the heterogeneous privacy requirements of users, leading to inefficient priv...

Muhammad Rafid, Golshan Famitafreshi, Kostas Ramantas et al. · 0 citations

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