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Carbon-Aware, Energy-Efficient, and SLA-Compliant Virtual Machine Placement in Cloud Data Centers Using Deep Q-Networks and Agglomerative Clustering

https://doi.org/10.3390/computers14070280

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1 of the 43 references listed on this page is in the Retraction Watch database as retracted (export 2026-11-11): 10.1007/s12652-020-02283-6 (notice 2022-05-23).

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What this work says

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

inferredcites →https://doi.org/10.1002/dac.3490openalex-snapshot

Toward a hierarchical and architecture‐based virtual machine allocation in cloud data centers

inferredcites →https://doi.org/10.1007/978-3-642-40047-6_33openalex-snapshot

Energy and Carbon-Efficient Placement of Virtual Machines in Distributed Cloud Data Centers

inferredcites →https://doi.org/10.1007/978-981-15-7571-6_10openalex-snapshot

Recent Advances and Application of Metaheuristic Algorithms: A Survey (2014–2020)

inferredcites →https://doi.org/10.1007/s00607-020-00813-wopenalex-snapshot

A multi-objective load balancing algorithm for virtual machine placement in cloud data centers based on machine learning

inferredcites →https://doi.org/10.1007/s00607-024-01311-zopenalex-snapshot

Enhancing virtual machine placement efficiency in cloud data centers: a hybrid approach using multi-objective reinforcement learning and clustering strategies

inferredcites →https://doi.org/10.1007/s10586-019-02954-wopenalex-snapshot

Optimizing virtual machine placement in IaaS data centers: taxonomy, review and open issues

inferredcites →https://doi.org/10.1007/s10586-022-03794-xopenalex-snapshot

Enhanced multi-objective virtual machine replacement in cloud data centers: combinations of fuzzy logic with reinforcement learning and biogeography-based optimization algorithms

inferredcites →https://doi.org/10.1007/s10586-024-04657-3openalex-snapshot

Energy-efficient virtual machine placement in heterogeneous cloud data centers: a clustering-enhanced multi-objective, multi-reward reinforcement learning approach

inferredcites →https://doi.org/10.1007/s11227-016-1797-5openalex-snapshot

Energy efficiency of VM consolidation in IaaS clouds

inferredcites →https://doi.org/10.1007/s11227-024-06510-1openalex-snapshot

A reinforcement learning-based GWO-RNN approach for energy efficiency in data centers by minimizing virtual machine migration

inferredcites →https://doi.org/10.1007/s11227-024-06734-1openalex-snapshot

An intelligent virtual machine allocation optimization model for energy-efficient and reliable cloud environment

inferredcites →https://doi.org/10.1007/s12652-020-02283-6openalex-snapshot

RETRACTED ARTICLE: A novel scheduling approach to improve the energy efficiency in cloud computing data centers

inferredcites →https://doi.org/10.1016/j.compeleceng.2020.106866openalex-snapshot

Multi-resource balance optimization for virtual machine placement in cloud data centers

inferredcites →https://doi.org/10.1016/j.future.2019.12.043openalex-snapshot

Exact algorithms for energy-efficient virtual machine placement in data centers

inferredcites →https://doi.org/10.1016/j.is.2021.101722openalex-snapshot

Applying Reinforcement Learning towards automating energy efficient virtual machine consolidation in cloud data centers

inferredcites →https://doi.org/10.1016/j.procs.2016.02.093openalex-snapshot

A Survey of Virtual Machine Placement Techniques in a Cloud Data Center

inferredcites →https://doi.org/10.1016/j.suscom.2021.100649openalex-snapshot

LECC: Location, energy, carbon and cost-aware VM placement model in geo-distributed DCs

inferredcites →https://doi.org/10.1016/j.suscom.2023.100856openalex-snapshot

An energy-efficient topology-aware virtual machine placement in Cloud Datacenters: A multi-objective discrete JAYA optimization

inferredcites →https://doi.org/10.1016/j.suscom.2024.100989openalex-snapshot

A systematic review of green-aware management techniques for sustainable data center

inferredcites →https://doi.org/10.1016/j.sysarc.2021.102048openalex-snapshot

A global-energy-aware virtual machine placement strategy for cloud data centers

inferredcites →https://doi.org/10.1109/access.2017.2711043openalex-snapshot

Energy-Efficient Algorithms for Dynamic Virtual Machine Consolidation in Cloud Data Centers

inferredcites →https://doi.org/10.1109/access.2017.2718001openalex-snapshot

A Survey and Taxonomy of Energy Efficiency Relevant Surveys in Cloud-Related Environments

inferredcites →https://doi.org/10.1109/access.2025.3562882openalex-snapshot

A Green Cloud-Based Framework for Energy-Efficient Task Scheduling Using Carbon Intensity Data for Heterogeneous Cloud Servers

inferredcites →https://doi.org/10.1109/cloud62652.2024.00062openalex-snapshot

Carbon-Aware and Fault-Tolerant Migration of Deep Learning Workloads in the Geo-Distributed Cloud

inferredcites →https://doi.org/10.1109/icacci.2014.6968597openalex-snapshot

Carbon efficient VM placement and migration technique for green federated cloud datacenters

inferredcites →https://doi.org/10.1109/icears53579.2022.9752341openalex-snapshot

Carbon Footprint Analysis: Need for Green Cloud Computing

inferredcites →https://doi.org/10.1109/ipact.2017.8244950openalex-snapshot

Energy efficient strategy for task allocation and VM placement in cloud environment

inferredcites →https://doi.org/10.1109/jiot.2024.3504260openalex-snapshot

Pioneering Eco-Efficiency in Cloud Computing: The Carbon-Conscious Federated Reinforcement Learning (CCFRL) Approach

inferredcites →https://doi.org/10.1109/jsyst.2020.3002721openalex-snapshot

GRVMP: A Greedy Randomized Algorithm for Virtual Machine Placement in Cloud Data Centers

inferredcites →https://doi.org/10.1109/jsyst.2022.3187971openalex-snapshot

GMPR: A Two-Phase Heuristic Algorithm for Virtual Machine Placement in Large-Scale Cloud Data Centers

inferredcites →https://doi.org/10.1109/pdp.2014.109openalex-snapshot

Energy-Efficient Virtual Machines Consolidation in Cloud Data Centers Using Reinforcement Learning

inferredcites →https://doi.org/10.1109/tcad.2017.2760517openalex-snapshot

Integrating Heuristic and Machine-Learning Methods for Efficient Virtual Machine Allocation in Data Centers

inferredcites →https://doi.org/10.1109/tcc.2015.2511768openalex-snapshot

On the Carbon Footprint Optimization in an InterCloud Environment

inferredcites →https://doi.org/10.1109/tpds.2025.3538525openalex-snapshot

Energy Efficient and Multi-Resource Optimization for Virtual Machine Placement by Improving MOEA/D

inferredcites →https://doi.org/10.1109/tsc.2016.2638900openalex-snapshot

A Hybrid Approach for Optimizing Carbon Footprint in InterCloud Environment

inferredcites →https://doi.org/10.1109/tsusc.2024.3391791openalex-snapshot

CFWS: DRL-Based Framework for Energy Cost and Carbon Footprint Optimization in Cloud Data Centers

inferredcites →https://doi.org/10.1109/tsusc.2025.3526192openalex-snapshot

Adaptive Capacity Provisioning for Carbon-Aware Data Centers: A Digital Twin-Based Approach

inferredcites →https://doi.org/10.1186/s13677-022-00368-5openalex-snapshot

A systematic review on effective energy utilization management strategies in cloud data centers

inferredcites →https://doi.org/10.25147/ijcsr.2017.001.1.225openalex-snapshot

Energy-aware and Carbon Footprint Optimization Model for Virtual Machine Placement in Data Centres –A Systematic Literature Review

inferredcites →https://doi.org/10.3390/electronics11213639openalex-snapshot

Cost-Effective and Energy-Aware Resource Allocation in Cloud Data Centers

inferredcites →https://doi.org/10.3390/electronics14030633openalex-snapshot

Virtual Machine Placement in Edge Computing Based on Multi-Objective Reinforcement Learning

inferredcites →https://doi.org/10.3390/en18112861openalex-snapshot

Energy Management for Distributed Carbon-Neutral Data Centers

inferredcites →https://doi.org/10.5220/0006236500001535openalex-snapshot

A Study of Virtual Machine Placement Optimization in Data Centers

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

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AnyScale Inference for Enterprise Chatbots: Carbon- and Cost-Aware Geo-Shifting Across Heterogeneous Accelerators

inferred← citeshttps://doi.org/10.1007/s00607-026-01732-yopenalex-snapshot

Hierarchical risk-aware RL for DVFS-enabled IoE scheduling

inferred← citeshttps://doi.org/10.1007/s11227-025-08072-2openalex-snapshot

Reduction of energy consumption in cloud data centers with proper placement of virtual machines

inferred← citeshttps://doi.org/10.1016/j.suscom.2026.101398openalex-snapshot

Carbon-aware federated orchestration in edge-cloud systems: A multi-objective optimization framework with dynamic spatio-temporal workload management

inferred← citeshttps://doi.org/10.1109/aic70896.2026.11717153openalex-snapshot

Energy-and SLA-Aware Microservice Autoscaling in Kubernetes Using K2DQN

inferred← citeshttps://doi.org/10.1109/ccge67142.2026.11581781openalex-snapshot

Energy-Aware Load Balancing in Cloud Data Centres: A Carbon-Efficient Approach

inferred← citeshttps://doi.org/10.1109/comcomap68359.2025.11353194openalex-snapshot

An Evolutionary Framework for Virtual Machine Placement in Cloud Computing based on hybrid Tabu Search and Genetic Algorithm

inferred← citeshttps://doi.org/10.1109/icecet65726.2026.11633191openalex-snapshot

Carbon-Aware, Zero-Trust, Energy-Efficient Asynchronous Distributed Learning for Financial Risk and Fraud Models

inferred← citeshttps://doi.org/10.1109/icercs65898.2025.11580884openalex-snapshot

Twin Aware Predictive Carbon-Efficient Scheduling for Workload Intelligence Routing in Multi-Region Computing Ecosystem

inferred← citeshttps://doi.org/10.1109/icesc70182.2026.11687602openalex-snapshot

Uncertainty-Aware Predictive Energy Management for Computer Networks

inferred← citeshttps://doi.org/10.1109/iciccs67901.2026.11502729openalex-snapshot

Carbon-Aware Dynamic Workload Scheduling for Large Language Model Training with Real-Time Energy Optimization

inferred← citeshttps://doi.org/10.1109/iciics67880.2026.11483498openalex-snapshot

EcoMind: A Nature-Inspired AI Framework for Sustainable Cloud Resource Optimization and Carbon Footprint Reduction

inferred← citeshttps://doi.org/10.1109/icnwc68145.2026.11518339openalex-snapshot

AI-Based Carbon-Aware Scheduling for Predicting and Improving Cloud Carbon Footprint

inferred← citeshttps://doi.org/10.1109/icosec67334.2025.11459486openalex-snapshot

SmartComply-RL+: An AI and ML-Driven Framework for Compliant, Cost-Optimal, and Carbon-Conscious Workload Placement Across Multi-Cloud Environments

inferred← citeshttps://doi.org/10.1109/icscss69635.2026.11646091openalex-snapshot

A Carbon-Optimal and Security-Compliant Scheduler for Cloud Workloads using Region-Specific ML Models

inferred← citeshttps://doi.org/10.1109/otcon69332.2026.11629782openalex-snapshot

Eco-Scheduler: A Carbon-Aware Intelligent Workload Distribution Framework for Sustainable Multi-Cloud Environments

inferred← citeshttps://doi.org/10.1109/tsc.2026.3720939openalex-snapshot

EcoVMS: LLM-Driven Reinforcement Learning for End-to-End Energy-Optimized VM Scheduling

inferred← citeshttps://doi.org/10.1186/s42162-026-00651-8openalex-snapshot

Towards carbon-aware AI: a systematic prisma review and taxonomy of green architectures, hardware life-cycle, and energy-efficient algorithms

inferred← citeshttps://doi.org/10.2139/ssrn.5788950openalex-snapshot

C–SLO: Carbon–and SLO–Aware Global Load Balancing for Online Services

inferred← citeshttps://doi.org/10.2139/ssrn.6439498openalex-snapshot

YUGO Framework: An Adaptive VM Consolidation Strategy using Hybrid Workload Prediction and Reinforcement Learning for Green Cloud Computing

inferred← citeshttps://doi.org/10.3390/computers15060339openalex-snapshot

Model for Green AI and Sustainable Computing: Energy-Efficient Architectures and Carbon-Aware Deployment in Industrial Systems

inferred← citeshttps://doi.org/10.3390/s26061780openalex-snapshot

Toward Energy-Efficient and Low-Carbon Intrusion Detection in Edge and Cloud Computing Based on GreenShield Cybersecurity Framework

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