DRL-based Low-Latency Content Delivery for 6G Massive Vehicular IoT
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2021.3064874
Abstract: Vehicle-to-everything communication is an indispensable component of 6G networks that could help to facilitate future transportation systems. However, massive vehicles and unstable vehicle-to-vehicle (V2V) links may become bottlenecks for the low-latency delivery of contents, such… read more here.
Keywords: vehicle; massive vehicular; low latency; drl based ... See more keywords
DRL-Based Secure Video Offloading in MEC-Enabled IoT Networks
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2022.3161680
Abstract: Wireless offloading in mobile-edge-computing (MEC)-enabled Internet of Things (IoT) networks inevitably suffers the risk of eavesdropping. Physical-layer security (PLS) approaches can be applied to prevent eavesdropping. However, the existing PLS techniques are not well targeted… read more here.
Keywords: drl based; iot networks; security; video offloading ... See more keywords
DRL-Based RIS Phase Shift Design for OFDM Communication Systems
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Wireless Communications Letters"
DOI: 10.1109/lwc.2023.3242449
Abstract: This letter investigates a downlink orthogonal frequency division multiplexing (OFDM) transmission system aided by a reconfigurable intelligent surface (RIS). To reduce the system overhead and cost, we consider a 1-bit resolution and column-wise controllable RIS,… read more here.
Keywords: ris phase; phase shift; drl based; based ris ... See more keywords
DRL-Based Long-Term Resource Planning for Task Offloading Policies in Multiserver Edge Computing Networks
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Network and Service Management"
DOI: 10.1109/tnsm.2022.3191748
Abstract: Multi-access edge computing (MEC) has been regarded as one of the essential technologies for mobile networks, by providing computing resources and services close to users, thereby, avoiding extra energy consumption and fitting the low-latency ultra-reliable… read more here.
Keywords: long term; drl based; resource; task offloading ... See more keywords
Adaptive DRL-Based Virtual Machine Consolidation in Energy-Efficient Cloud Data Center
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DOI: 10.1109/tpds.2022.3147851
Abstract: The dramatic increasing of data and demands for computing capabilities may result in excessive use of resources in cloud data centers, which not only causes the raising of energy consumption, but also leads to the… read more here.
Keywords: drl based; energy; consolidation; cloud data ... See more keywords
Robustness Analysis and Enhancement of Deep Reinforcement Learning-Based Schedulers
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DOI: 10.1109/tpds.2022.3218649
Abstract: Dependency-aware jobs, such as the big data analytic workflows, are commonly executed on the cloud. They are compiled to directed acyclic graphs, with tasks linked in regarding the dependency. The cloud scheduler, which maintains a… read more here.
Keywords: drl based; based schedulers; reinforcement learning; deep reinforcement ... See more keywords
Multi-Agent DRL-based Hungarian Algorithm (MADRLHA) for Task Offloading in Multi-Access Edge Computing Internet of Vehicles (IoVs)
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Wireless Communications"
DOI: 10.1109/twc.2022.3160099
Abstract: This paper investigates the computation offloading problem in a high mobility internet of vehicles (IoVs) environment, aiming to guarantee latency, energy consumption, and payment cost requirements. Both moving and parked vehicles are utilized as fog… read more here.
Keywords: vehicles iovs; drl based; access edge; agent ... See more keywords