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Priority-Aware Resource Management for Adaptive Service Function Chaining in Real-Time Intelligent IoT Services

https://doi.org/10.3390/electronics11192976

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1 of the 30 references listed on this page is in the Retraction Watch database as retracted (export 2026-11-11): 10.1155/2022/4289216 (notice 2023-12-29).

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1109/colcomcon.2014.6860404openalex-snapshot

Using Mininet for emulation and prototyping Software-Defined Networks

inferredcites →https://doi.org/10.1109/comst.2015.2477041openalex-snapshot

Network Function Virtualization: State-of-the-Art and Research Challenges

inferredcites →https://doi.org/10.1109/comst.2018.2866942openalex-snapshot

A Survey of Machine Learning Techniques Applied to Software Defined Networking (SDN): Research Issues and Challenges

inferredcites →https://doi.org/10.1109/comst.2021.3073036openalex-snapshot

Deep Reinforcement Learning for Internet of Things: A Comprehensive Survey

inferredcites →https://doi.org/10.1109/hpsr48589.2020.9098994openalex-snapshot

Deep Reinforcement Learning for NFV-based Service Function Chaining in Multi-Service Networks : Invited Paper

inferredcites →https://doi.org/10.1109/jas.2016.7508798openalex-snapshot

Traffic signal timing via deep reinforcement learning

inferredcites →https://doi.org/10.1109/jsac.2019.2959181openalex-snapshot

Optimal VNF Placement via Deep Reinforcement Learning in SDN/NFV-Enabled Networks

inferredcites →https://doi.org/10.1109/jstars.2021.3120724openalex-snapshot

Adaptive Resource Optimized Edge Federated Learning in Real-Time Image Sensing Classifications

inferredcites →https://doi.org/10.1109/mnet.011.2000373openalex-snapshot

The Need for Advanced Intelligence in NFV Management and Orchestration

inferredcites →https://doi.org/10.1109/netsoft.2016.7502433openalex-snapshot

Optimal network resource utilization in service function chaining

inferredcites →https://doi.org/10.1109/tccn.2018.2809722openalex-snapshot

Deep Reinforcement Learning for Dynamic Multichannel Access in Wireless Networks

inferredcites →https://doi.org/10.1109/tccn.2020.2988486openalex-snapshot

End-to-End Performance-Based Autonomous VNF Placement With Adopted Reinforcement Learning

inferredcites →https://doi.org/10.1145/2829988.2790030openalex-snapshot

A Mininet-based Virtual Testbed for Distributed SDN Development

inferredcites →https://doi.org/10.1145/3022670.2976746openalex-snapshot

TensorFlow: learning functions at scale

inferredcites →https://doi.org/10.1155/2022/4289216openalex-snapshot

Intelligent Offloading Decision and Resource Allocations Schemes Based on RNN/DQN for Reliability Assurance in Software-Defined Massive Machine-Type Communications

inferredcites →https://doi.org/10.3390/app10144735openalex-snapshot

Deep Learning at the Mobile Edge: Opportunities for 5G Networks

inferredcites →https://doi.org/10.3390/electronics10060700openalex-snapshot

Network Intelligent Control and Traffic Optimization Based on SDN and Artificial Intelligence

inferredcites →https://doi.org/10.3390/electronics11091457openalex-snapshot

A Survey of NFV Network Acceleration from ETSI Perspective

inferredcites →https://doi.org/10.3390/electronics9091363openalex-snapshot

A Survey of Multi-Task Deep Reinforcement Learning

inferredcites →https://doi.org/10.3390/electronics9091392openalex-snapshot

Overview of Architectural Alternatives for the Integration of ETSI MEC Environments from Different Administrative Domains

inferredcites →https://doi.org/10.3390/fi11030055openalex-snapshot

Simulating Fog and Edge Computing Scenarios: An Overview and Research Challenges

inferredcites →https://doi.org/10.3390/fi14020059openalex-snapshot

Network Function Virtualization and Service Function Chaining Frameworks: A Comprehensive Review of Requirements, Objectives, Implementations, and Open Research Challenges

inferredcites →https://doi.org/10.3390/s18093071openalex-snapshot

DM-MQTT: An Efficient MQTT Based on SDN Multicast for Massive IoT Communications

inferredcites →https://doi.org/10.3390/su12145706openalex-snapshot

Deep Reinforcement Learning for the Management of Software-Defined Networks and Network Function Virtualization in an Edge-IoT Architecture

inferredcites →https://doi.org/10.3837/tiis.2018.02.027openalex-snapshot

An Efficient Software Defined Data Transmission Scheme based on Mobile Edge Computing for the Massive IoT Environment

inferredcites →https://doi.org/10.3837/tiis.2021.09.002openalex-snapshot

Adaptive Success Rate-based Sensor Relocation for IoT Applications

inferredcites →https://doi.org/10.3837/tiis.2021.09.003openalex-snapshot

Multicast Tree Generation using Meta Reinforcement Learning in SDN-based Smart Network Platforms

inferredcites →https://doi.org/10.3837/tiis.2021.12.006openalex-snapshot

An Efficient Service Function Chains Orchestration Algorithm for Mobile Edge Computing

inferredcites →https://doi.org/10.3837/tiis.2022.05.016openalex-snapshot

Routing optimization algorithm for logistics virtual monitoring based on VNF dynamic deployment

inferredcites →https://doi.org/10.3837/tiis.2022.07.008openalex-snapshot

Integrating Resilient Tier N+1 Networks with Distributed Non-Recursive Cloud Model for Cyber-Physical Applications

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/s11235-025-01387-8openalex-snapshot

Performance monitoring and self-adaptation in smart environments: a systematic literature review

inferred← citeshttps://doi.org/10.1016/j.comnet.2023.110001openalex-snapshot

Dynamic slicing reconfiguration for virtualized 5G networks using ML forecasting of computing capacity

inferred← citeshttps://doi.org/10.1016/j.eswa.2026.131705openalex-snapshot

Oraculum: A model for self-adaptive system optimization in smart environments

inferred← citeshttps://doi.org/10.1049/ell2.70320openalex-snapshot

AI‐Based Virtual Network Function Embedding for Internet of Things Using Parallel Deep Reinforcement Learning

inferred← citeshttps://doi.org/10.1063/5.0254293openalex-snapshot

Exploring the landscape of software defined networking: A comprehensive survey of applications, challenges, and future directions

inferred← citeshttps://doi.org/10.1109/access.2024.3444313openalex-snapshot

A Comprehensive Survey on Resource Management in 6G Network Based on Internet of Things

inferred← citeshttps://doi.org/10.1109/inspect67393.2025.11350518openalex-snapshot

Adaptive Priority Data Transmission in Swarm Robots using CAN Protocol

inferred← citeshttps://doi.org/10.1109/isncc66965.2025.11250434openalex-snapshot

A Self-Adaptive Architecture for Predictive and Reinforcement-Based Optimization in Smart Environments

inferred← citeshttps://doi.org/10.1109/tccn.2025.3540256openalex-snapshot

GAI-Based Resource and QoE Aware Service Placement in Next-Generation Multi-Domain IoT Networks

inferred← citeshttps://doi.org/10.1109/tce.2024.3426483openalex-snapshot

GCN-Based Multi-Agent Deep Reinforcement Learning for Dynamic Service Function Chain Deployment in IoT

inferred← citeshttps://doi.org/10.1155/2024/3384837openalex-snapshot

SFC‐Based IoT Provisioning on a Hybrid Cloud‐Fog Computing with a Minimized Latency

inferred← citeshttps://doi.org/10.32604/cmc.2025.062716openalex-snapshot

Priority-Aware Resource Allocation for VNF Deployment in Service Function Chains Based on Graph Reinforcement Learning

inferred← citeshttps://doi.org/10.33640/2405-609x.3326openalex-snapshot

Smart Service Function Chain System for Dynamic Traffic Steering using Reinforcement Learning (CHRL)

inferred← citeshttps://doi.org/10.3390/electronics11203371openalex-snapshot

Graph Neural Networks for Intelligent Modelling in Network Management and Orchestration: A Survey on Communications

inferred← citeshttps://doi.org/10.3390/electronics12061307openalex-snapshot

An Improved Adaptive Service Function Chain Mapping Method Based on Deep Reinforcement Learning

inferred← citeshttps://doi.org/10.3390/electronics12122753openalex-snapshot

Virtual Network Function Migration Considering Load Balance and SFC Delay in 6G Mobile Edge Computing Networks

inferred← citeshttps://doi.org/10.5753/ctd.2026.19468openalex-snapshot

Oraculum: A Model for Self-Adaptive System Optimization in Smart Environments

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