Abstract
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Tofan Agung Eka Prasetya, Kholoud Alkayid, Farhad Soleimanian Gharehchopogh, Ramin Abbaszadi, Parisa Khoshvaght, Aso Darwesh, Thantrira Porntaveetus, Sadia Din
Abstract
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6G mobile communication technology: requirements, targets, applications, challenges, advantages, and opportunities
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Edge computing in future wireless networks: a comprehensive evaluation and vision for 6G and beyond
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Self-learning adaptive power management scheme for energy-efficient IoT-MEC systems using soft actor-critic algorithm
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Provenance
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10.1016/j.eswa.2024.125762 · 2025
Multi-objective secure task offloading strategy for blockchain-enabled IoV-MEC systems: a double deep Q-network approach
10.1109/access.2023.3348513 · 2024
An energy-efficient data offloading strategy for 5G-enabled vehicular edge computing networks using double deep Q-network
10.1007/s11277-024-10862-5 · 2019
Pervasive AI for IoT applications: a survey on resource-efficient distributed artificial intelligence
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Video caching, analytics, and delivery at the wireless edge: a survey and future directions
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Privacy-aware edge computation offloading with federated learning in healthcare consumer electronics system
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Computation-efficient offloading and power control for MEC in IoT networks by meta-reinforcement learning
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A hybrid PSO and GA algorithm with rescheduling for task offloading in device-edge-cloud collaborative computing
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Dynamic task offloading in edge computing for computer access point selection based on adaptive deep reinforcement learning with meta-heuristic optimization
10.1016/j.asoc.2025.113105 · doi-reference
An energy-focused model for batteryless IoT: vortex wireless power transfer and fog computing in 6G networks
10.1016/j.iot.2025.101657 · doi-reference
Adaptive two-stage task offloading based on meta reinforcement learning for mobile edge computing
10.1007/s11227-025-07274-y · doi-reference
Cooperative caching algorithm for mobile edge networks based on multi-agent meta reinforcement learning
10.1016/j.comnet.2024.110247 · doi-reference
Computation-efficient offloading and power control for MEC in IoT networks by meta-reinforcement learning
10.1109/jiot.2024.3355023 · doi-reference
Privacy-aware edge computation offloading with federated learning in healthcare consumer electronics system
10.1109/tce.2025.3535753 · doi-reference
Acceleration offloading for differential privacy protection based on federated learning in edge intelligent controllers
10.1016/j.future.2024.107526 · doi-reference
FlocOff: data heterogeneity resilient federated learning with communication-efficient edge offloading
10.1109/jsac.2024.3431526 · doi-reference
Computation offloading for edge-assisted federated learning
10.1109/tvt.2021.3098022 · doi-reference
Efficient coordination of federated learning and inference offloading at the edge: a proactive optimization paradigm
10.1109/tmc.2024.3466844 · doi-reference
Real-time offloading for dependent and parallel tasks in cloud-edge environments using deep reinforcement learning
10.1109/tpds.2023.3349177 · doi-reference
Optimizing task offloading and resource allocation in edge-cloud networks: a DRL approach
10.1186/s13677-023-00461-3 · doi-reference
Deep Q-learning-based dynamic network slicing and task offloading in edge network
10.1109/tnsm.2022.3208776 · doi-reference
DeepEdge: a deep reinforcement learning based task orchestrator for edge computing
10.1109/tnse.2022.3217311 · doi-reference
A survey on artificial intelligence and blockchain applications in cybersecurity for smart cities
10.70470/shifra/2025/001 · doi-reference
Efficient hardware acceleration techniques for deep learning on edge devices: a comprehensive performance analysis
10.70470/khwarizmia/2023/010 · doi-reference
Federated learning-assisted task offloading based on feature matching and caching in collaborative device-edge-cloud networks
10.1109/tmc.2024.3403851 · doi-reference
Efficient end-edge-cloud task offloading in 6G networks based on multiagent deep reinforcement learning
10.1109/jiot.2024.3372614 · doi-reference
Hierarchical deep reinforcement learning for joint service caching and computation offloading in mobile edge-cloud computing
10.1109/tsc.2024.3355937 · doi-reference
Task offloading optimization in digital twin assisted MEC-enabled air-ground IIoT 6G networks
10.1109/tvt.2024.3420876 · doi-reference
Coordinated jamming and poisoning attack detection and mitigation in wireless federated learning networks
10.1109/ojcoms.2025.3558672 · doi-reference
Towards the decentralised cloud: survey on approaches and challenges for mobile, ad hoc, and edge computing
10.1145/3243929 · doi-reference
Video caching, analytics, and delivery at the wireless edge: a survey and future directions
10.1109/comst.2020.3035427 · doi-reference
Pervasive AI for IoT applications: a survey on resource-efficient distributed artificial intelligence
10.1109/comst.2022.3200740 · doi-reference
An energy-efficient data offloading strategy for 5G-enabled vehicular edge computing networks using double deep Q-network
10.1007/s11277-024-10862-5 · doi-reference
Multi-objective secure task offloading strategy for blockchain-enabled IoV-MEC systems: a double deep Q-network approach
10.1109/access.2023.3348513 · doi-reference
Quantum-inspired gravitational search algorithm-based low-price binary task offloading for multi-users in unmanned aerial vehicle-assisted edge computing systems
10.1016/j.eswa.2024.125762 · doi-reference
Quantum GA-driven digital twin for task urgency-aware partitioning and offloading in multi UAV-Aided MEC systems
10.1016/j.adhoc.2025.103891 · doi-reference
Combining federated learning and edge computing toward ubiquitous intelligence in 6G network: challenges, recent advances, and future directions
10.1109/comst.2023.3316615 · doi-reference
Self-learning adaptive power management scheme for energy-efficient IoT-MEC systems using soft actor-critic algorithm
10.1016/j.iot.2025.101587 · doi-reference
10.1016/j.adhoc.2024.103656
10.1016/j.adhoc.2024.103656 · doi-reference
An optimizing geo-distributed edge layering with double deep Q-networks for predictive mobility-aware offloading in mobile edge computing
10.1016/j.adhoc.2025.103804 · doi-reference
Edge computing in future wireless networks: a comprehensive evaluation and vision for 6G and beyond
10.1016/j.icte.2024.08.007 · doi-reference