On the public citation graph

Energy and latency reductions at the fog gateway using a machine learning classifier

https://doi.org/10.1016/j.suscom.2021.100582
0 signed · 51 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.
Claim with ORCID
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 See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

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

inferredcites →https://doi.org/10.1002/cpe.3314openalex-snapshot
OpenStack Neat: a framework for dynamic and energy‐efficient consolidation of virtual machines in OpenStack clouds
inferredcites →https://doi.org/10.1002/spe.2509openalex-snapshot
iFogSim: A toolkit for modeling and simulation of resource management techniques in the Internet of Things, Edge and Fog computing environments
inferredcites →https://doi.org/10.1016/j.suscom.2011.06.005openalex-snapshot
An overview and classification of thermal-aware scheduling techniques for multi-core processing systems
inferredcites →https://doi.org/10.1016/j.suscom.2017.10.003openalex-snapshot
MLscale: A machine learning based application-agnostic autoscaler
inferredcites →https://doi.org/10.1016/j.suscom.2018.08.005openalex-snapshot
WEEC: Web Energy Efficient Computing
inferredcites →https://doi.org/10.1016/j.suscom.2019.100355openalex-snapshot
A novel four-tier architecture for delay aware scheduling and load balancing in fog environment
inferredcites →https://doi.org/10.1016/j.suscom.2020.100412openalex-snapshot
PowerCoord: Power capping coordination for multi-CPU/GPU servers using reinforcement learning
inferredcites →https://doi.org/10.1109/aicas.2019.8771621openalex-snapshot
Edge and Fog Computing Enabled AI for IoT-An Overview
inferredcites →https://doi.org/10.1109/aicas45491.2019openalex-snapshot
2019 IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS)
inferredcites →https://doi.org/10.1109/bdcloud.2014.105openalex-snapshot
A Generic and Extensible Framework for Monitoring Energy Consumption of OpenStack Clouds
inferredcites →https://doi.org/10.1109/cloud.2009.72openalex-snapshot
EnaCloud: An Energy-Saving Application Live Placement Approach for Cloud Computing Environments
inferredcites →https://doi.org/10.1109/healthcom.2017.8210762openalex-snapshot
User behavior driven MAC scheduling for body sensor networks
inferredcites →https://doi.org/10.1109/healthcom40869.2017openalex-snapshot
2017 IEEE 19th International Conference on e-Health Networking, Applications and Services (Healthcom)
inferredcites →https://doi.org/10.1109/icecds.2017.8389935openalex-snapshot
Internet of Things (IOT): An overview and its applications
inferredcites →https://doi.org/10.1109/icecds42120.2017openalex-snapshot
2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS)
inferredcites →https://doi.org/10.1109/icsesp.2018.8376731openalex-snapshot
Low latency and energy efficient sensor selection for IoT services
inferredcites →https://doi.org/10.1109/icsesp43389.2018openalex-snapshot
2018 Technologies for Smart-City Energy Security and Power (ICSESP)
inferredcites →https://doi.org/10.1109/ipdps.2007.370510openalex-snapshot
Autonomic Power & Performance Management for Large-Scale Data Centers
inferredcites →https://doi.org/10.1109/iscc.2012.6249339openalex-snapshot
Honeyguide: A VM migration-aware network topology for saving energy consumption in data center networks
inferredcites →https://doi.org/10.1109/itc31499.2013openalex-snapshot
Proceedings of the 2013 25th International Teletraffic Congress (ITC)
inferredcites →https://doi.org/10.1109/mc.2007.443openalex-snapshot
The Case for Energy-Proportional Computing
inferredcites →https://doi.org/10.1109/sustainit.2015.7101358openalex-snapshot
Adding energy efficiency to Openstack
inferredcites →https://doi.org/10.1109/tcomm.2017.2699660openalex-snapshot
Offloading in Mobile Edge Computing: Task Allocation and Computational Frequency Scaling
inferredcites →https://doi.org/10.1109/tpds.2015.2421352openalex-snapshot
An Evolutionary Technique for Performance-Energy-Temperature Optimized Scheduling of Parallel Tasks on Multi-Core Processors
inferredcites →https://doi.org/10.1145/2367736.2367743openalex-snapshot
Energy- and performance-aware scheduling of tasks on parallel and distributed systems
inferredcites →https://doi.org/10.1201/b16631openalex-snapshot
Handbook of Energy-Aware and Green Computing - Two Volume Set
inferredcites →https://doi.org/10.2172/1372902openalex-snapshot
United States Data Center Energy Usage Report
inferredcites →https://doi.org/10.23919/itc.2017.8065706openalex-snapshot
Energy-Aware Consolidation Scheme for Data Center Cloud Applications
inferredcites →https://doi.org/10.3390/en10101470openalex-snapshot
Trends in Data Centre Energy Consumption under the European Code of Conduct for Data Centre Energy Efficiency
inferredcites →https://doi.org/10.5555/1855711.1855728openalex-snapshot
ElasticTree: saving energy in data center networks

What points at this work

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

inferred← citeshttps://doi.org/10.2139/ssrn.4662182openalex-extracted
Machine Learning-based Classification Approach for Improving Renewable Energy Management in IoT-based Smart Grids
inferred← citeshttps://doi.org/10.1002/9781119817741.ch10openalex-snapshot
Sustainable Energy Storage Devices and Device Design for Sensors and Actuators Applications THIS CHAPTER IS WITHDRAWN
inferred← citeshttps://doi.org/10.1007/978-3-031-08038-8_2openalex-snapshot
Optimization of Green Mobile Cloud Computing
inferred← citeshttps://doi.org/10.1007/s00607-022-01073-6openalex-snapshot
An overview of data reduction solutions at the edge of IoT systems: a systematic mapping of the literature
inferred← citeshttps://doi.org/10.1007/s11042-023-16399-2openalex-snapshot
Machine learning-based solutions for resource management in fog computing
inferred← citeshttps://doi.org/10.1016/j.cosrev.2023.100568openalex-snapshot
Deep learning models for cloud, edge, fog, and IoT computing paradigms: Survey, recent advances, and future directions
inferred← citeshttps://doi.org/10.1016/j.jnca.2023.103648openalex-snapshot
AI augmented Edge and Fog computing: Trends and challenges
inferred← citeshttps://doi.org/10.1016/j.jpdc.2023.02.006openalex-snapshot
Improving cloud/edge sustainability through artificial intelligence: A systematic review
inferred← citeshttps://doi.org/10.1016/j.mlwa.2022.100363openalex-snapshot
Renewable energy management in smart grids by using big data analytics and machine learning
inferred← citeshttps://doi.org/10.1016/j.suscom.2023.100898openalex-snapshot
Energy management of smart homes over fog-based IoT architecture
inferred← citeshttps://doi.org/10.1063/5.0109736openalex-snapshot
An interface machine for cloud technology and multicore processing of intelligent development communication network
inferred← citeshttps://doi.org/10.1109/access.2024.3376670openalex-snapshot
A Novel Offloading Mechanism Leveraging Fuzzy Logic and Deep Reinforcement Learning to Improve IoT Application Performance in a Three-Layer Architecture Within the Fog-Cloud Environment
inferred← citeshttps://doi.org/10.1109/icpads60453.2023.00349openalex-snapshot
Latency, Energy and Carbon Aware Collaborative Resource Allocation with Consolidation and QoS Degradation Strategies in Edge Computing
inferred← citeshttps://doi.org/10.1109/tim.2025.3557124openalex-snapshot
AIoT: Artificial Intelligence and the Internet of Things for Monitoring and Prognosis of Systems and Structures
inferred← citeshttps://doi.org/10.1115/1.4054690openalex-snapshot
Machine Health Management System Using Moving Average Feature With Bidirectional Long-Short Term Memory
inferred← citeshttps://doi.org/10.3233/jhs-230002openalex-snapshot
Decision tree-based prediction approach for improving stable energy management in smart grids
inferred← citeshttps://doi.org/10.3390/pr10020204openalex-snapshot
An Artificial Neural Network Model to Predict Efficiency and Emissions of a Gasoline Engine
inferred← citeshttps://doi.org/10.3390/s22010196openalex-snapshot
Recent Advances in Evolving Computing Paradigms: Cloud, Edge, and Fog Technologies
inferred← citeshttps://doi.org/10.3390/s23208435openalex-snapshot
An Energy-Efficient Routing Protocol with Reinforcement Learning in Software-Defined Wireless Sensor Networks
inferred← citeshttps://doi.org/10.3390/s25030687openalex-snapshot
Machine Learning-Based Resource Management in Fog Computing: A Systematic Literature Review
inferred← citeshttps://doi.org/10.4271/2022-01-0380openalex-snapshot
Modeling Performance and Emissions of a Spark Ignition Engine with Machine Learning Approaches
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.