On the public citation graph
Resource Management in Mobile Edge Computing: A Comprehensive Survey
0 signed · 224 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-030-01237-3_47openalex-snapshot
MVSNet: Depth Inference for Unstructured Multi-view Stereo
inferredcites →https://doi.org/10.1007/978-3-319-46448-0_2openalex-snapshot
SSD: Single Shot MultiBox Detector
inferredcites →https://doi.org/10.1007/s11036-020-01624-1openalex-snapshot
Vehicular Edge Computing and Networking: A Survey
inferredcites →https://doi.org/10.1016/j.comnet.2017.03.015openalex-snapshot
Incentive mechanism for computation offloading using edge computing: A Stackelberg game approach
inferredcites →https://doi.org/10.1016/j.future.2019.01.059openalex-snapshot
Task migration for mobile edge computing using deep reinforcement learning
inferredcites →https://doi.org/10.1016/j.sysarc.2019.02.009openalex-snapshot
All one needs to know about fog computing and related edge computing paradigms: A complete survey
inferredcites →https://doi.org/10.1109/access.2016.2597169openalex-snapshot
Energy-Efficient Offloading for Mobile Edge Computing in 5G Heterogeneous Networks
inferredcites →https://doi.org/10.1109/access.2018.2819690openalex-snapshot
Joint Computation Offloading and Resource Allocation Optimization in Heterogeneous Networks With Mobile Edge Computing
inferredcites →https://doi.org/10.1109/access.2018.2828102openalex-snapshot
A Survey on Service Migration in Mobile Edge Computing
inferredcites →https://doi.org/10.1109/access.2018.2872781openalex-snapshot
5G Wireless Network Slicing for eMBB, URLLC, and mMTC: A Communication-Theoretic View
inferredcites →https://doi.org/10.1109/access.2018.2879334openalex-snapshot
Joint Offloading and Computing Design in Wireless Powered Mobile-Edge Computing Systems With Full-Duplex Relaying
inferredcites →https://doi.org/10.1109/access.2018.2882452openalex-snapshot
A Density-Based Offloading Strategy for IoT Devices in Edge Computing Systems
inferredcites →https://doi.org/10.1109/access.2018.2882800openalex-snapshot
Decentralized Computation Offloading and Resource Allocation for Mobile-Edge Computing: A Matching Game Approach
inferredcites →https://doi.org/10.1109/access.2019.2909319openalex-snapshot
Energy-Efficient Cooperation in Mobile Edge Computing-Enabled Cognitive Radio Networks
inferredcites →https://doi.org/10.1109/access.2019.2919736openalex-snapshot
Federated Learning-Based Computation Offloading Optimization in Edge Computing-Supported Internet of Things
inferredcites →https://doi.org/10.1109/access.2019.2938534openalex-snapshot
Edge Computing in 5G: A Review
inferredcites →https://doi.org/10.1109/access.2020.3004571openalex-snapshot
Lightweight Online Profiling-Based Configuration Adaptation for Video Analytics System in Edge Computing
inferredcites →https://doi.org/10.1109/ccgrid51090.2021.00059openalex-snapshot
EFFECT: Energy-efficient Fog Computing Framework for Real-time Video Processing
inferredcites →https://doi.org/10.1109/cloudcom.2016.0061openalex-snapshot
SEGUE: Quality of Service Aware Edge Cloud Service Migration
inferredcites →https://doi.org/10.1109/comst.2017.2682318openalex-snapshot
Mobile Edge Computing: A Survey on Architecture and Computation Offloading
inferredcites →https://doi.org/10.1109/comst.2017.2745201openalex-snapshot
A Survey on Mobile Edge Computing: The Communication Perspective
inferredcites →https://doi.org/10.1109/comst.2018.2849509openalex-snapshot
Survey on Multi-Access Edge Computing for Internet of Things Realization
inferredcites →https://doi.org/10.1109/comst.2020.2970550openalex-snapshot
Convergence of Edge Computing and Deep Learning: A Comprehensive Survey
inferredcites →https://doi.org/10.1109/cvpr.2016.91openalex-snapshot
You Only Look Once: Unified, Real-Time Object Detection
inferredcites →https://doi.org/10.1109/cvpr.2017.691openalex-snapshot
Multi-view 3D Object Detection Network for Autonomous Driving
inferredcites →https://doi.org/10.1109/drcn48652.2020.1570610618openalex-snapshot
Formal Modeling and Analysis of Multi-Rogue Backoff Manipulation Attacks in Unlicensed Networks
inferredcites →https://doi.org/10.1109/glocom.2016.7841937openalex-snapshot
Joint Subcarrier and CPU Time Allocation for Mobile Edge Computing
inferredcites →https://doi.org/10.1109/glocom.2018.8647611openalex-snapshot
Deep Reinforcement Learning for User Association and Resource Allocation in Heterogeneous Networks
inferredcites →https://doi.org/10.1109/glocomw.2017.8269049openalex-snapshot
Decentralized Computation Offloading in Mobile Edge Computing Empowered Small-Cell Networks
inferredcites →https://doi.org/10.1109/icc.2014.6883509openalex-snapshot
A Markov Decision Process-based service migration procedure for follow me cloud
inferredcites →https://doi.org/10.1109/icc.2016.7511131openalex-snapshot
PRIMAL: PRofIt Maximization Avatar pLacement for mobile edge computing
inferredcites →https://doi.org/10.1109/icc.2018.8422517openalex-snapshot
Optimal Pricing-Based Edge Computing Resource Management in Mobile Blockchain
inferredcites →https://doi.org/10.1109/icc.2018.8422877openalex-snapshot
Energy-Efficient Joint Offloading and Wireless Resource Allocation Strategy in Multi-MEC Server Systems
inferredcites →https://doi.org/10.1109/icc.2019.8761385openalex-snapshot
Resource Allocation for Edge Computing in IoT Networks via Reinforcement Learning
inferredcites →https://doi.org/10.1109/icc40277.2020.9148698openalex-snapshot
Energy Efficient Resource Allocation and Computation Offloading in Millimeter-Wave based Fog Radio Access Networks
inferredcites →https://doi.org/10.1109/icc40277.2020.9149012openalex-snapshot
Energy Efficient Task Offloading for Compute-intensive Mobile Edge Applications
inferredcites →https://doi.org/10.1109/icc40277.2020.9149185openalex-snapshot
Mobility-Aware Deep Reinforcement Learning with Glimpse Mobility Prediction in Edge Computing
inferredcites →https://doi.org/10.1109/icdcs.2017.226openalex-snapshot
Distributed Deep Neural Networks Over the Cloud, the Edge and End Devices
inferredcites →https://doi.org/10.1109/icdcs47774.2020.00028openalex-snapshot
EdgeSlice: Slicing Wireless Edge Computing Network with Decentralized Deep Reinforcement Learning
inferredcites →https://doi.org/10.1109/icpr.2016.7900006openalex-snapshot
BranchyNet: Fast inference via early exiting from deep neural networks
inferredcites →https://doi.org/10.1109/icsess.2010.5552416openalex-snapshot
Live virtual machine migration based on improved pre-copy approach
inferredcites →https://doi.org/10.1109/ifipnetworking.2015.7145316openalex-snapshot
Dynamic service migration in mobile edge-clouds
inferredcites →https://doi.org/10.1109/infocom.2018.8485905openalex-snapshot
DeepDecision: A Mobile Deep Learning Framework for Edge Video Analytics
inferredcites →https://doi.org/10.1109/infocom.2018.8486241openalex-snapshot
An Edge Network Orchestrator for Mobile Augmented Reality
inferredcites →https://doi.org/10.1109/infocom.2019.8737464openalex-snapshot
Federated Learning over Wireless Networks: Optimization Model Design and Analysis
inferredcites →https://doi.org/10.1109/infocom.2019.8737478openalex-snapshot
Hetero-Edge: Orchestration of Real-time Vision Applications on Heterogeneous Edge Clouds
inferredcites →https://doi.org/10.1109/infocom41043.2020.9155524openalex-snapshot
Joint Configuration Adaptation and Bandwidth Allocation for Edge-based Real-time Video Analytics
inferredcites →https://doi.org/10.1109/ipdps47924.2020.00033openalex-snapshot
Experience-Driven Computational Resource Allocation of Federated Learning by Deep Reinforcement Learning
inferredcites →https://doi.org/10.1109/jcn.2019.000046openalex-snapshot
Joint resource allocation and computation offloading in mobile edge computing for SDN based wireless networks
inferredcites →https://doi.org/10.1109/jiot.2018.2838022openalex-snapshot
Hierarchical Fog-Cloud Computing for IoT Systems: A Computation Offloading Game
inferredcites →https://doi.org/10.1109/jiot.2018.2876279openalex-snapshot
Optimized Computation Offloading Performance in Virtual Edge Computing Systems Via Deep Reinforcement Learning
inferredcites →https://doi.org/10.1109/jiot.2019.2903191openalex-snapshot
Deep Learning Empowered Task Offloading for Mobile Edge Computing in Urban Informatics
inferredcites →https://doi.org/10.1109/jiot.2020.3026589openalex-snapshot
When Deep Reinforcement Learning Meets Federated Learning: Intelligent Multitimescale Resource Management for Multiaccess Edge Computing in 5G Ultradense Network
inferredcites →https://doi.org/10.1109/jiot.2020.3030926openalex-snapshot
Multihop Offloading of Multiple DAG Tasks in Collaborative Edge Computing
inferredcites →https://doi.org/10.1109/jiot.2021.3072611openalex-snapshot
Federated Learning Meets Blockchain in Edge Computing: Opportunities and Challenges
inferredcites →https://doi.org/10.1109/jproc.2019.2918951openalex-snapshot
Edge Intelligence: Paving the Last Mile of Artificial Intelligence With Edge Computing
inferredcites →https://doi.org/10.1109/jsac.2018.2864426openalex-snapshot
Computation Rate Maximization in UAV-Enabled Wireless-Powered Mobile-Edge Computing Systems
inferredcites →https://doi.org/10.1109/jsac.2019.2904348openalex-snapshot
Adaptive Federated Learning in Resource Constrained Edge Computing Systems
inferredcites →https://doi.org/10.1109/jsac.2019.2933893openalex-snapshot
Multi-Tenant Cross-Slice Resource Orchestration: A Deep Reinforcement Learning Approach
inferredcites →https://doi.org/10.1109/lcnsymposium50271.2020.9363256openalex-snapshot
Deep Reinforcement Learning Based Energy-efficient Task Offloading for Secondary Mobile Edge Systems
inferredcites →https://doi.org/10.1109/lcomm.2019.2960777openalex-snapshot
Risk-Sensitive Task Fetching and Offloading for Vehicular Edge Computing
inferredcites →https://doi.org/10.1109/mcom.001.2000112openalex-snapshot
DBNS: A Distributed Blockchain-Enabled Network Slicing Framework for 5G Networks
inferredcites →https://doi.org/10.1109/mnet.2019.1800254openalex-snapshot
Intelligent Edge Computing for IoT-Based Energy Management in Smart Cities
inferredcites →https://doi.org/10.1109/mnet.2019.1800286openalex-snapshot
In-Edge AI: Intelligentizing Mobile Edge Computing, Caching and Communication by Federated Learning
inferredcites →https://doi.org/10.1109/mobilecloud55333.2022.00010openalex-snapshot
End-to-End Latency Optimization of Multi-view 3D Reconstruction for Disaster Response
inferredcites →https://doi.org/10.1109/mvt.2017.2668838openalex-snapshot
Mobile-Edge Computing for Vehicular Networks: A Promising Network Paradigm with Predictive Off-Loading
inferredcites →https://doi.org/10.1109/nca.2019.8935043openalex-snapshot
Migration-driven Resilient Disaster Response Edge-Cloud Deployments
inferredcites →https://doi.org/10.1109/pimrc.2017.8292207openalex-snapshot
Joint subcarrier and power allocation for OFDMA based mobile edge computing system
inferredcites →https://doi.org/10.1109/sec.2018.00016openalex-snapshot
VideoEdge: Processing Camera Streams using Hierarchical Clusters
inferredcites →https://doi.org/10.1109/sec.2018.00019openalex-snapshot
Bandwidth-Efficient Live Video Analytics for Drones Via Edge Computing
inferredcites →https://doi.org/10.1109/tcad.2018.2858384openalex-snapshot
DeepThings: Distributed Adaptive Deep Learning Inference on Resource-Constrained IoT Edge Clusters
inferredcites →https://doi.org/10.1109/tccn.2017.2725277openalex-snapshot
Online Learning for Offloading and Autoscaling in Energy Harvesting Mobile Edge Computing
inferredcites →https://doi.org/10.1109/tcomm.2017.2787700openalex-snapshot
Computation Offloading and Resource Allocation in Mixed Fog/Cloud Computing Systems With Min-Max Fairness Guarantee
inferredcites →https://doi.org/10.1109/tcomm.2019.2898573openalex-snapshot
Dynamic Task Offloading and Resource Allocation for Ultra-Reliable Low-Latency Edge Computing
inferredcites →https://doi.org/10.1109/tgcn.2018.2878348openalex-snapshot
Energy-Optimal Scheduling of Mobile Cloud Computing Based on a Modified Lyapunov Optimization Method
inferredcites →https://doi.org/10.1109/tii.2021.3064351openalex-snapshot
Deep Reinforcement Learning Assisted Federated Learning Algorithm for Data Management of IIoT
inferredcites →https://doi.org/10.1109/tits.2021.3099597openalex-snapshot
Vehicle Selection and Resource Optimization for Federated Learning in Vehicular Edge Computing
inferredcites →https://doi.org/10.1109/tmc.2019.2920819openalex-snapshot
Optimal Mobile Computation Offloading with Hard Deadline Constraints
inferredcites →https://doi.org/10.1109/tmc.2019.2928811openalex-snapshot
Deep Reinforcement Learning for Online Computation Offloading in Wireless Powered Mobile-Edge Computing Networks
inferredcites →https://doi.org/10.1109/tnet.2015.2487344openalex-snapshot
Efficient Multi-User Computation Offloading for Mobile-Edge Cloud Computing
inferredcites →https://doi.org/10.1109/tnet.2019.2924471openalex-snapshot
RL-NSB: Reinforcement Learning-Based 5G Network Slice Broker
inferredcites →https://doi.org/10.1109/tnet.2022.3156178openalex-snapshot
Joint Wireless and Edge Computing Resource Management With Dynamic Network Slice Selection
inferredcites →https://doi.org/10.1109/tnse.2020.2978856openalex-snapshot
Deep Reinforcement Learning Based Resource Management for Multi-Access Edge Computing in Vehicular Networks
inferredcites →https://doi.org/10.1109/tsc.2019.2947914openalex-snapshot
Cloud/Edge Computing Service Management in Blockchain Networks: Multi-leader Multi-follower Game-based ADMM for Pricing
inferredcites →https://doi.org/10.1109/tvt.2019.2917890openalex-snapshot
Computation Offloading and Resource Allocation For Cloud Assisted Mobile Edge Computing in Vehicular Networks
inferredcites →https://doi.org/10.1109/tvt.2019.2935450openalex-snapshot
Deep Reinforcement Learning for Offloading and Resource Allocation in Vehicle Edge Computing and Networks
inferredcites →https://doi.org/10.1109/tvt.2020.2992607openalex-snapshot
Dynamic Network Slicing and Resource Allocation in Mobile Edge Computing Systems
inferredcites →https://doi.org/10.1109/twc.2014.2331051openalex-snapshot
Collaborative Task Execution in Mobile Cloud Computing Under a Stochastic Wireless Channel
inferredcites →https://doi.org/10.1109/twc.2016.2633522openalex-snapshot
Energy-Efficient Resource Allocation for Mobile-Edge Computation Offloading
inferredcites →https://doi.org/10.1109/twc.2017.2717986openalex-snapshot
Stochastic Joint Radio and Computational Resource Management for Multi-User Mobile-Edge Computing Systems
inferredcites →https://doi.org/10.1109/twc.2017.2785305openalex-snapshot
Joint Offloading and Computing Optimization in Wireless Powered Mobile-Edge Computing Systems
inferredcites →https://doi.org/10.1109/twc.2018.2845360openalex-snapshot
Latency Optimization for Resource Allocation in Mobile-Edge Computation Offloading
inferredcites →https://doi.org/10.1109/twc.2018.2885266openalex-snapshot
Distributed Resource Allocation in Blockchain-Based Video Streaming Systems With Mobile Edge Computing
inferredcites →https://doi.org/10.1109/twc.2018.2890653openalex-snapshot
Stochastic Control of Computation Offloading to a Helper With a Dynamically Loaded CPU
inferredcites →https://doi.org/10.1109/twc.2019.2946140openalex-snapshot
Edge AI: On-Demand Accelerating Deep Neural Network Inference via Edge Computing
inferredcites →https://doi.org/10.1109/twc.2020.3025446openalex-snapshot
Joint Device Scheduling and Resource Allocation for Latency Constrained Wireless Federated Learning
inferredcites →https://doi.org/10.1109/twc.2020.3037554openalex-snapshot
Energy Efficient Federated Learning Over Wireless Communication Networks
inferredcites →https://doi.org/10.1109/vtcfall.2018.8690663openalex-snapshot
URLLC Services in 5G Low Latency Enhancements for LTE
inferredcites →https://doi.org/10.1109/vtcfall.2018.8690980openalex-snapshot
Performance Optimization in Mobile-Edge Computing via Deep Reinforcement Learning
inferredcites →https://doi.org/10.1109/wf-iot48130.2020.9221089openalex-snapshot
Resource Allocation in Mobility-Aware Federated Learning Networks: A Deep Reinforcement Learning Approach
inferredcites →https://doi.org/10.1145/1618525.1618528openalex-snapshot
Post-copy live migration of virtual machines
inferredcites →https://doi.org/10.1145/2342509.2342513openalex-snapshot
Fog computing and its role in the internet of things
inferredcites →https://doi.org/10.1145/3132211.3134448openalex-snapshot
An energy-efficient offloading framework with predictable temporal correctness
inferredcites →https://doi.org/10.1145/3239565openalex-snapshot
A Dynamic Service Migration Mechanism in Edge Cognitive Computing
inferredcites →https://doi.org/10.1145/3300061.3300116openalex-snapshot
Edge Assisted Real-time Object Detection for Mobile Augmented Reality
inferredcites →https://doi.org/10.1145/3318216.3363328openalex-snapshot
Adaptive task offloading over wireless in mobile edge computing
inferredcites →https://doi.org/10.1145/3326066openalex-snapshot
Resource Management in Fog/Edge Computing
inferredcites →https://doi.org/10.1145/3545008.3545085openalex-snapshot
FedDRL: Deep Reinforcement Learning-based Adaptive Aggregation for Non-IID Data in Federated Learning
inferredcites →https://doi.org/10.1155/2019/3159762openalex-snapshot
A Survey on Vehicular Edge Computing: Architecture, Applications, Technical Issues, and Future Directions
inferredcites →https://doi.org/10.1364/ofc.2019.m3g.3openalex-snapshot
COSMOS: Optical Architecture and Prototyping
inferredcites →https://doi.org/10.1609/aaai.v30i1.10295openalex-snapshot
Deep Reinforcement Learning with Double Q-Learning
inferredcites →https://doi.org/10.23919/date.2017.7927211openalex-snapshot
MoDNN: Local distributed mobile computing system for Deep Neural Network
inferredcites →https://doi.org/10.23919/wiopt.2018.8362865openalex-snapshot
Joint computation and communication cooperation for mobile edge computing
inferredcites →https://doi.org/10.26636/jtit.2016.3.749openalex-snapshot
Stackelberg Security Games: Models, Applications and Computational Aspects
inferredcites →https://doi.org/10.3390/s20030610openalex-snapshot
Mobility-Aware Service Caching in Mobile Edge Computing for Internet of Things
inferredcites →https://doi.org/10.3390/s22020450openalex-snapshot
Federated Learning in Edge Computing: A Systematic Survey
inferredcites →https://doi.org/10.48550/arxiv.1703.02529openalex-snapshot
NoScope: Optimizing Neural Network Queries over Video at Scale
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/cpe.70448openalex-snapshot
A Chaotic Model‐Based Dynamic Resource Allocation and Adaptive Task Offloading With Lightweight Encryption in Multi‐Access Edge Computing
inferred← citeshttps://doi.org/10.1007/978-3-032-09917-4_6openalex-snapshot
An Improved Anomaly Detection Based on Ensemble Learning and Deep Q-Network for Mobile Edge Computing Monitoring
inferred← citeshttps://doi.org/10.1007/978-981-96-0096-0_18openalex-snapshot
Distributed Optimisation of Mobile Robots in a Mobile Edge Computing Environment
inferred← citeshttps://doi.org/10.1007/978-981-96-0805-8_2openalex-snapshot
POSEIDON: Efficient Function Placement at the Edge Using Deep Reinforcement Learning
inferred← citeshttps://doi.org/10.1007/978-981-97-2644-8_3openalex-snapshot
Resource Allocation and Placement in Multi-access Edge Computing
inferred← citeshttps://doi.org/10.1007/s00607-025-01471-6openalex-snapshot
An efficient task offloading and auto-scaling approach for IoT applications in edge computing environment
inferred← citeshttps://doi.org/10.1007/s00607-025-01526-8openalex-snapshot
A systematic literature review of machine learning-based resource allocation techniques in cloud computing
inferred← citeshttps://doi.org/10.1007/s10115-025-02507-1openalex-snapshot
Dynamic resource orchestration in edge computing environments using multi-agent reinforcement learning
inferred← citeshttps://doi.org/10.1007/s10462-025-11340-5openalex-snapshot
Multi-agent reinforcement learning for resources allocation optimization: a survey
inferred← citeshttps://doi.org/10.1007/s10586-025-05560-1openalex-snapshot
Computation offloading based on incomplete information in edge computing networks
inferred← citeshttps://doi.org/10.1007/s10586-025-05607-3openalex-snapshot
Deadline-Aware and Priority-Driven scheduling for IoT tasks in Fog-Cloud systems using reinforcement learning
inferred← citeshttps://doi.org/10.1007/s10586-026-06358-5openalex-snapshot
QoS-aware service provisioning in federated edge computing: a comprehensive review of mobility management, context-awareness and reliability
inferred← citeshttps://doi.org/10.1007/s10922-025-09992-3openalex-snapshot
Priority-Aware Resource Reallocation in Edge Computing Using Reinforcement Learning
inferred← citeshttps://doi.org/10.1007/s11042-024-18123-0openalex-snapshot
Resource allocation problem and artificial intelligence: the state-of-the-art review (2009–2023) and open research challenges
inferred← citeshttps://doi.org/10.1007/s11761-026-00489-8openalex-snapshot
Double auction based task migration for load balancing among multiple edge servers
inferred← citeshttps://doi.org/10.1007/s42486-024-00159-8openalex-snapshot
Distributed multi-agent deep reinforcement learning for trajectory planning in UAVs-assisted edge offloading
inferred← citeshttps://doi.org/10.1016/j.adhoc.2025.103971openalex-snapshot
Deep reinforcement learning for optimizing computation latency in wireless-powered Multi-Access Edge Computing systems: A partial offloading approach
inferred← citeshttps://doi.org/10.1016/j.aei.2026.104635openalex-snapshot
LDS-former: A lightweight dual-stream transformer for real-time acoustic emission monitoring of crack evolution in offshore steel structures
inferred← citeshttps://doi.org/10.1016/j.comcom.2024.05.021openalex-snapshot
IoT video analytics for surveillance-based systems in smart cities
inferred← citeshttps://doi.org/10.1016/j.comcom.2025.108254openalex-snapshot
Optimizing mobility prediction in 5G for enhanced C-V2X applications: A multidisciplinary research survey
inferred← citeshttps://doi.org/10.1016/j.comnet.2024.110633openalex-snapshot
Task execution latency minimization for energy-sensitive IoTs in wireless powered mobile edge computing: A DRL-based method
inferred← citeshttps://doi.org/10.1016/j.comnet.2025.111111openalex-snapshot
Game theory-based vehicle selection and channel scheduling for federated learning in vehicular edge networks
inferred← citeshttps://doi.org/10.1016/j.comnet.2025.111458openalex-snapshot
A stochastic learning algorithm for multi-agent game in mobile network: A Cross-Silo federated learning perspective
inferred← citeshttps://doi.org/10.1016/j.cor.2026.107454openalex-snapshot
Collaborative multi-agent DRL for energy-efficient task offloading and resource allocation in WBAN-MEC systems
inferred← citeshttps://doi.org/10.1016/j.cosrev.2025.100887openalex-snapshot
Revisiting workflow scheduling with the power of edge computing: Taxonomy, review, and open challenges
inferred← citeshttps://doi.org/10.1016/j.eswa.2025.127214openalex-snapshot
Reinforcement learning-based solution for resource management in fog computing: A comprehensive survey
inferred← citeshttps://doi.org/10.1016/j.future.2024.04.047openalex-snapshot
Elastic Federated Learning with Kubernetes Vertical Pod Autoscaler for edge computing
inferred← citeshttps://doi.org/10.1016/j.iot.2024.101119openalex-snapshot
Advancing 6G-IoT networks: Willow catkin packet transmission scheduling with AI and bayesian game-theoretic approach-based resource allocation.
inferred← citeshttps://doi.org/10.1016/j.iot.2024.101342openalex-snapshot
Comprehensive survey on reinforcement learning-based task offloading techniques in aerial edge computing
inferred← citeshttps://doi.org/10.1016/j.iot.2024.101385openalex-snapshot
Load-balanced offloading of multiple task types for mobile edge computing in IoT
inferred← citeshttps://doi.org/10.1016/j.paerosci.2026.101183openalex-snapshot
Bridging game theory and multi-agent systems: Development status and future prospects
inferred← citeshttps://doi.org/10.1016/j.peva.2026.102554openalex-snapshot
Performance comparison of LSTM-based handover prediction models for 6G MEC services
inferred← citeshttps://doi.org/10.1016/j.phycom.2025.102632openalex-snapshot
A review of channel estimation research methods for massive MIMO systems
inferred← citeshttps://doi.org/10.1109/access.2025.3552479openalex-snapshot
Non-Redundant Feature Extraction in Mobile Edge Computing
inferred← citeshttps://doi.org/10.1109/access.2025.3573929openalex-snapshot
Deep Reinforcement Learning With Dueling DQN for Partial Computation Offloading and Resource Allocation in Mobile Edge Computing
inferred← citeshttps://doi.org/10.1109/access.2025.3576716openalex-snapshot
A Review of Resource Allocation for Maximizing Performance of IoT Systems
inferred← citeshttps://doi.org/10.1109/aibdf67964.2025.11440917openalex-snapshot
Dynamic Resource Scheduling for UAV-Assisted Vehicular Edge Computing: A Multi-Agent RL Approach
inferred← citeshttps://doi.org/10.1109/ccgrid68966.2026.00067openalex-snapshot
Deep Reinforcement Learning-Driven Edge Offloading for Latency-Constrained XR Pipelines
inferred← citeshttps://doi.org/10.1109/commnet63022.2024.10793255openalex-snapshot
Multi-Service And Multi-Tier Edge-Cloud Continuum Planning
inferred← citeshttps://doi.org/10.1109/dsis67228.2025.11390598openalex-snapshot
A Lightweight Task Allocation Method Based on Dynamic Spatiotemporal Clustering for Mobile Crowdsensing
inferred← citeshttps://doi.org/10.1109/dyspan64764.2025.11115950openalex-snapshot
A Proof of Concept Resource Management Scheme for Augmented Reality Applications in 5G Systems
inferred← citeshttps://doi.org/10.1109/eurocon64445.2025.11073213openalex-snapshot
Performance-Driven System Design for Multi-Access Edge Computing
inferred← citeshttps://doi.org/10.1109/fuzz69877.2026.11626457openalex-snapshot
Fuzzy Admission Control Using Non-Intrusive QoS Inference for Resource-Constrained Environments
inferred← citeshttps://doi.org/10.1109/gast67799.2026.11523246openalex-snapshot
Decentralized Edge embedded intelligence for Cooperative Drone Swarms using STM32 microcontroller and Zephyr RTOS
inferred← citeshttps://doi.org/10.1109/icc52391.2025.11161007openalex-snapshot
Dynamic Service Caching, Computing, and Communication Resource Optimization for Low-Latency Edge-Cloud Networks
inferred← citeshttps://doi.org/10.1109/icfec69006.2026.00020openalex-snapshot
Attention-Based Decomposition Framework for Joint Task Offloading and Resource Allocation in Multi-Task Multi-Server MEC
inferred← citeshttps://doi.org/10.1109/iciics67880.2026.11483456openalex-snapshot
Intelligent and Cost Aware Resource Scheduling Strategies in Cloud Computing
inferred← citeshttps://doi.org/10.1109/icosaas68663.2026.11648619openalex-snapshot
Chaos Engineering and Observability Integration for Resilient Cloud Infrastructure
inferred← citeshttps://doi.org/10.1109/ijcnn64981.2025.11228743openalex-snapshot
Optimization of Task Offloading Strategy based on Lyapunov and Deep Reinforcement Learning in Multi MEC Systems
inferred← citeshttps://doi.org/10.1109/infocomwkshps65812.2025.11152972openalex-snapshot
Joint Optimization of Executor Deployment and Task Offloading for Mobile Edge Computing: A Pointer Network Approach
inferred← citeshttps://doi.org/10.1109/ipdpsw63119.2024.00116openalex-snapshot
FrameFeedback: A Closed-Loop Control System for Dynamic Offloading Real-Time Edge Inference
inferred← citeshttps://doi.org/10.1109/ispa67752.2025.00045openalex-snapshot
Generative AI-Enhanced Energy-Efficient Multi-UAV Collaborative Mobile Edge Computing
inferred← citeshttps://doi.org/10.1109/jiot.2025.3557431openalex-snapshot
Precision-Adaptive Task Offloading and Resource Allocation for Efficient Positioning and Sensing in Near-Field IoV Systems
inferred← citeshttps://doi.org/10.1109/jiot.2025.3583204openalex-snapshot
Joint Optimization of AAV Deployment and Task Scheduling in Multi-AAV-Enabled Mobile Edge Computing Systems
inferred← citeshttps://doi.org/10.1109/jiot.2026.3685815openalex-snapshot
Mobility-Aware Joint Task Offloading and Resource Allocation in SDN-Enabled MEC Networks via Hierarchical Deep Reinforcement Learning
inferred← citeshttps://doi.org/10.1109/lcn65610.2025.11146344openalex-snapshot
AdVAR-DNN: Adversarial Misclassification Attack on Collaborative DNN Inference
inferred← citeshttps://doi.org/10.1109/mass66014.2025.00071openalex-snapshot
Reliable Multi-view 3D Reconstruction for ‘Just-in-time’ Edge Environments
inferred← citeshttps://doi.org/10.1109/miot.2025.3616853openalex-snapshot
Harnessing Artificial Intelligence for Efficient Resource Management in Mobile Edge Computing: Insights from Real-World Data
inferred← citeshttps://doi.org/10.1109/nfv-sdn66355.2025.11349573openalex-snapshot
An X-by-Construction Framework Targeting 6G Edge-Networked Applications
inferred← citeshttps://doi.org/10.1109/nnice68970.2026.11466221openalex-snapshot
A Deep Reinforcement Learning-Based Dynamic Queue Management Approach for Network Traffic Scheduling
inferred← citeshttps://doi.org/10.1109/noms57970.2025.11073623openalex-snapshot
Infer-EDGE: Dynamic DNN Inference Optimization in Just-in-Time Edge-AI Implementations
inferred← citeshttps://doi.org/10.1109/noms69089.2026.11668171openalex-snapshot
Orchestrating Composite Applications at the Edge
inferred← citeshttps://doi.org/10.1109/noms69089.2026.11668205openalex-snapshot
DRIFTER: A Diffusion-RL Inference Framework for AI Service Fault-Tolerant Migration in 6G Dynamic Edge Networks
inferred← citeshttps://doi.org/10.1109/prdc63035.2024.00046openalex-snapshot
RL-Based Approach to Enhance Reliability and Efficiency in Autoscaling for Heterogeneous Edge Serverless Computing Environments
inferred← citeshttps://doi.org/10.1109/sec62691.2024.00072openalex-snapshot
Poster: Reliable 3D Reconstruction for Ad-Hoc Edge Implementations
inferred← citeshttps://doi.org/10.1109/smartiot70864.2026.00021openalex-snapshot
GPMS: Prediction-Driven GNN-Based Multi-Agent Scheduling for Multi-Cluster Edge Computing
inferred← citeshttps://doi.org/10.1109/smc58881.2025.11343326openalex-snapshot
Dynamic Service Placement and Computation Resource Allocation for Cloud-Edge Computing: A Reinforcement Learning Approach
inferred← citeshttps://doi.org/10.1109/sti64222.2024.10951061openalex-snapshot
Resource Sharing in Federated Edge Network Using Fractional Knapsack Based Genetic Algorithm
inferred← citeshttps://doi.org/10.1109/swc62898.2024.00370openalex-snapshot
deepV:PPO-driven Task Latency Minimization in Volunteer-supported Edge Computing
inferred← citeshttps://doi.org/10.1109/swc65939.2025.00100openalex-snapshot
Optimizing Multi-Task Offloading in LEO Satellite Networks with Q-Transformer and Lagrangian
inferred← citeshttps://doi.org/10.1109/tits.2025.3546048openalex-snapshot
Bidding-Enabled Resource Pricing for Computation Offloading in 6G Vehicle-to-Edge Networks
inferred← citeshttps://doi.org/10.1109/tmc.2025.3587713openalex-snapshot
Mixed-Timescale Service Caching, Computing, and Communication Optimization for Low-Latency High-Reliability Edge-Cloud Networks
inferred← citeshttps://doi.org/10.1109/tmc.2025.3605382openalex-snapshot
Rising From Pieces: Effective Inference at the Edge via Robust Split ML
inferred← citeshttps://doi.org/10.1109/tmc.2026.3664992openalex-snapshot
P-UCB: A Preference-Based Upper Confidence Bound Strategy for Efficient Edge Server Placement
inferred← citeshttps://doi.org/10.1109/tmc.2026.3680521openalex-snapshot
HSplitLoRA: A Heterogeneous Split Parameter-Efficient Fine-Tuning Framework for Large Language Models
inferred← citeshttps://doi.org/10.1109/tnsm.2025.3592979openalex-snapshot
Deep Reinforcement Learning-Based Contract Incentive and Computation Offloading for Mobile Edge Computing-Enabled Blockchain
inferred← citeshttps://doi.org/10.1109/tqe.2024.3398410openalex-snapshot
Variational Quantum Algorithms for the Allocation of Resources in a Cloud/Edge Architecture
inferred← citeshttps://doi.org/10.1109/tsc.2025.3620092openalex-snapshot
ERAP Optimization via Enhanced Constraints and Boundary Detection in GMRA
inferred← citeshttps://doi.org/10.1109/tvt.2024.3485017openalex-snapshot
Adaptive Task Offloading for Mobile Edge Computing With Forecast Information
inferred← citeshttps://doi.org/10.1109/twc.2025.3606543openalex-snapshot
Two-Timescale Joint 3C Optimizations for RIS-Assisted MIMO-OFDM Wireless Networks
inferred← citeshttps://doi.org/10.1109/wf-iot64238.2025.11270645openalex-snapshot
Generative AI-Driven Robust Service Fault-Tolerant Migration Under Dynamic Edge Networks
inferred← citeshttps://doi.org/10.1109/wincom65874.2025.11313367openalex-snapshot
Semantics Driven Multi Agent Artificial Intelligence Framework for Adaptive Resource Management in SixG Mobile Edge Networks
inferred← citeshttps://doi.org/10.1145/3680256.3721329openalex-snapshot
Introducing Resource Awareness Levels in Edge Computing Resource Management
inferred← citeshttps://doi.org/10.1145/3719664openalex-snapshot
A Review on Edge Large Language Models: Design, Execution, and Applications
inferred← citeshttps://doi.org/10.1145/3762181openalex-snapshot
Resource Management for Mission-Critical Applications in Edge Computing: Systematic Review on Recent Research and Open Issues
inferred← citeshttps://doi.org/10.1145/3772281openalex-snapshot
c2mec: Cooperative Multi-split and Multi-hop Edge Computing Based on Deep Reinforcement Learning
inferred← citeshttps://doi.org/10.1145/3793811.3793823openalex-snapshot
An Empirical Evaluation of Kubernetes Resilience in Cloud–Edge Deployments Using Failure Injection Techniques
inferred← citeshttps://doi.org/10.1186/s13638-024-02401-4openalex-snapshot
Computational offloading into UAV swarm networks: a systematic literature review
inferred← citeshttps://doi.org/10.15302/j-sscae-2024.01.016openalex-snapshot
Vehicle-Infrastructure Cooperative Sensing: Progress and Prospect
inferred← citeshttps://doi.org/10.1561/1300000074openalex-snapshot
Resilience in Edge Computing: Challenges and Concepts
inferred← citeshttps://doi.org/10.21203/rs.3.rs-9450046/v1openalex-snapshot
Hierarchical Hybrid Optimization Algorithm for Task Unloading: Joint Solution of Discrete Decision and Convex Optimization
inferred← citeshttps://doi.org/10.2139/ssrn.6463849openalex-snapshot
Research on Construction of an Energy Efficiency Evaluation System for Edge Computing in Library Smart Service
inferred← citeshttps://doi.org/10.2139/ssrn.6949561openalex-snapshot
Uncertainty-aware multi-objective modelling and optimization framework for coupled production scheduling and computation offloading in cloud–edge–terminal intelligent workshops
inferred← citeshttps://doi.org/10.23919/cje.2024.00.346openalex-snapshot
Offloading Budget-Constrained Tasks to Edge via Reinforced Embedding
inferred← citeshttps://doi.org/10.2478/ijanmc-2025-0009openalex-snapshot
Edge Computing in IoT Networks: Enhancing Efficiency, Reducing Latency, and Improving Scalability.
inferred← citeshttps://doi.org/10.26634/jcc.11.2.21661openalex-snapshot
Leveraging mobile cloud computing for real-time data processing: Novel approach
inferred← citeshttps://doi.org/10.26906/sunz.2025.4.088openalex-snapshot
АДАПТИВНИЙ МЕТОД ДИНАМІЧНОГО КЕРУВАННЯ РЕСУРСАМИ ГРАНИЧНОГО ШАРУ ІНДУСТРІАЛЬНОГО ІНТЕРНЕТУ РЕЧЕЙ
inferred← citeshttps://doi.org/10.26906/sunz.2026.1.082openalex-snapshot
СИНТЕЗ МЕРЕЖІ ЗВ’ЯЗКУ КЛАСТЕРА ТУМАННОГО ШАРУ ВИСОКОЩІЛЬНОГО ПРОМИСЛОВОГО ІНТЕРНЕТУ РЕЧЕЙ
inferred← citeshttps://doi.org/10.3390/s25216759openalex-snapshot
Task Offloading Algorithm for Multiple Unmanned Aerial Vehicles Based on Temporal Graph
inferred← citeshttps://doi.org/10.3390/signals7050092openalex-snapshot
Discrete Atomic Compression of JPEG Images: A Comparative Study with a Progressive DCT-Based Coder and Evaluation Across a Diverse Set of Established and State-of-the-Art CNN Classifiers
inferred← citeshttps://doi.org/10.36548/rrrj.2025.1.009openalex-snapshot
Distributed Resource Management in Operating Systems: A Case Study on HDFS and YARN
inferred← citeshttps://doi.org/10.51583/ijltemas.2026.150500164openalex-snapshot
Predictive Maintenance of Industrial Equipment Using Machine Learning and IOT Data Analytics: A Context-Aware, Edge-Cloud Framework with Operator-in-the-Loop Adaptation
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.