On the public citation graph
Toward an autonomic approach for Internet of Things service placement using gray wolf optimization in the fog computing environment
0 signed · 95 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known work and none has been retracted — and get a dated CiteStamped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/10.1002/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/10.1002/spe.2685openalex-snapshot
User allocation‐aware edge cloud placement in mobile edge computing
inferredcites →https://doi.org/10.1002/spe.2699openalex-snapshot
Characterizing application scheduling on edge, fog, and cloud computing resources
inferredcites →https://doi.org/10.1002/spe.2766openalex-snapshot
How to place your apps in the fog: State of the art and open challenges
inferredcites →https://doi.org/10.1002/spe.2804openalex-snapshot
A systematic approach toward security in Fog computing: Assets, vulnerabilities, possible countermeasures
inferredcites →https://doi.org/10.1002/spe.2839openalex-snapshot
A review on the computation offloading approaches in mobile edge computing: A g ame‐theoretic perspective
inferredcites →https://doi.org/10.1002/spe.2896openalex-snapshot
CREW: Cost and Reliability aware Eagle‐Whale optimiser for service placement in Fog
inferredcites →https://doi.org/10.1002/spe.995openalex-snapshot
CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms
inferredcites →https://doi.org/10.1007/978-3-030-02671-4_14openalex-snapshot
Latency-Aware Placement Heuristic in Fog Computing Environment
inferredcites →https://doi.org/10.1007/s10586-020-03096-0openalex-snapshot
An energy-efficient algorithm for virtual machine placement optimization in cloud data centers
inferredcites →https://doi.org/10.1007/s10586-021-03283-7openalex-snapshot
Data replication schemes in cloud computing: a survey
inferredcites →https://doi.org/10.1007/s10723-019-09491-1openalex-snapshot
Resource Management Approaches in Fog Computing: a Comprehensive Review
inferredcites →https://doi.org/10.1007/s10723-020-09530-2openalex-snapshot
A Survey on the Computation Offloading Approaches in Mobile Edge/Cloud Computing Environment: A Stochastic-based Perspective
inferredcites →https://doi.org/10.1007/s11761-017-0219-8openalex-snapshot
Optimized IoT service placement in the fog
inferredcites →https://doi.org/10.1007/s12652-018-0785-4openalex-snapshot
A methodology for deployment of IoT application in fog
inferredcites →https://doi.org/10.1016/j.asoc.2018.12.037openalex-snapshot
An integer encoding grey wolf optimizer for virtual network function placement
inferredcites →https://doi.org/10.1016/j.comnet.2020.107496openalex-snapshot
A survey on the computation offloading approaches in mobile edge computing: A machine learning-based perspective
inferredcites →https://doi.org/10.1016/j.comnet.2021.108116openalex-snapshot
An energy-efficient routing protocol for the Internet of Things networks based on geographical location and link quality
inferredcites →https://doi.org/10.1016/j.future.2018.01.060openalex-snapshot
Towards energy efficient service composition in green energy powered Cyber–Physical Fog Systems
inferredcites →https://doi.org/10.1016/j.future.2018.09.006openalex-snapshot
Energy-aware environments for the development of green applications for cyber–physical systems
inferredcites →https://doi.org/10.1016/j.future.2020.02.047openalex-snapshot
A methodology for the design and deployment of distributed cyber–physical systems for smart environments
inferredcites →https://doi.org/10.1016/j.future.2020.03.064openalex-snapshot
Secure software placement and configuration
inferredcites →https://doi.org/10.1016/j.ins.2019.07.069openalex-snapshot
Privacy-aware service placement for mobile edge computing via federated learning
inferredcites →https://doi.org/10.1016/j.jnca.2021.102974openalex-snapshot
An autonomous computation offloading strategy in Mobile Edge Computing: A deep learning-based hybrid approach
inferredcites →https://doi.org/10.1016/j.knosys.2019.01.018openalex-snapshot
The defect of the Grey Wolf optimization algorithm and its verification method
inferredcites →https://doi.org/10.1016/j.sysarc.2021.101996openalex-snapshot
A priority, power and traffic-aware virtual machine placement of IoT applications in cloud data centers
inferredcites →https://doi.org/10.1049/iet-com.2020.0007openalex-snapshot
Priority, network and energy‐aware placement of IoT‐based application services in fog‐cloud environments
inferredcites →https://doi.org/10.1109/cfec.2019.8733152openalex-snapshot
ORCH: Distributed Orchestration Framework using Mobile Edge Devices
inferredcites →https://doi.org/10.1109/icc40277.2020.9148960openalex-snapshot
Multi-Component V2X Applications Placement in Edge Computing Environment
inferredcites →https://doi.org/10.1109/infocom.2019.8737449openalex-snapshot
Service Placement with Provable Guarantees in Heterogeneous Edge Computing Systems
inferredcites →https://doi.org/10.1109/jiot.2019.2896311openalex-snapshot
FOGPLAN: A Lightweight QoS-Aware Dynamic Fog Service Provisioning Framework
inferredcites →https://doi.org/10.1109/jiot.2019.2959124openalex-snapshot
Trust-Oriented IoT Service Placement for Smart Cities in Edge Computing
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/scc.2019.00017openalex-snapshot
Service Placement in Fog Computing Using Constraint Programming
inferredcites →https://doi.org/10.1109/tcc.2017.2648788openalex-snapshot
STAR: SLA-aware Autonomic Management of Cloud Resources
inferredcites →https://doi.org/10.1109/tencon.2019.8929234openalex-snapshot
GA-PSO: Service Allocation in Fog Computing Environment Using Hybrid Bio-Inspired Algorithm
inferredcites →https://doi.org/10.1109/tmc.2019.2952097openalex-snapshot
Interaction-Oriented Service Entity Placement in Edge Computing
inferredcites →https://doi.org/10.1109/tnsm.2019.2894955openalex-snapshot
Optimized Provisioning of Edge Computing Resources With Heterogeneous Workload in IoT Networks
inferredcites →https://doi.org/10.1109/wowmom.2019.8792989openalex-snapshot
Autonomic Service Placement in Fog Computing
inferredcites →https://doi.org/10.1145/3326285.3329055openalex-snapshot
Dependent task placement and scheduling with function configuration in edge computing
inferredcites →https://doi.org/10.1145/3331052.3332477openalex-snapshot
Distributed Deep Neural Network Deployment for Smart Devices from the Edge to the Cloud
inferredcites →https://doi.org/10.1145/3403955openalex-snapshot
Application Management in Fog Computing Environments
inferredcites →https://doi.org/10.1155/2019/6215454openalex-snapshot
Task Placement on Fog Computing Made Efficient for IoT Application Provision
inferredcites →https://doi.org/10.3390/a12100201openalex-snapshot
GASP: Genetic Algorithms for Service Placement in Fog Computing Systems
inferredcites →https://doi.org/10.3390/app9173550openalex-snapshot
Multi-Objective Service Placement Scheme Based on Fuzzy-AHP System for Distributed Cloud Computing
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.70097openalex-snapshot
Service Placement in Fog Computing Using a Combination of Reinforcement Learning and Improved Gray Wolf Optimization Method
inferred← citeshttps://doi.org/10.1002/ett.4650openalex-snapshot
Reinforcement optimization for decentralized service placement policy in IoT‐centric fog environment
inferred← citeshttps://doi.org/10.1002/ett.4790openalex-snapshot
LPB‐SPP : Solving the internet of things service placement problem using the learner performance‐based behavior algorithm
inferred← citeshttps://doi.org/10.1002/ett.5022openalex-snapshot
Dynamic service function chain placement in mobile computing: An asynchronous advantage actor‐critic based approach
inferred← citeshttps://doi.org/10.1007/s00500-025-10533-yopenalex-snapshot
One-phase multi-view clustering with unified graph and data representation convolution
inferred← citeshttps://doi.org/10.1007/s00607-024-01340-8openalex-snapshot
Hybrid deep learning and evolutionary algorithms for accurate cloud workload prediction
inferred← citeshttps://doi.org/10.1007/s00607-024-01353-3openalex-snapshot
Deep reinforcement learning-based optimal deployment of IoT machine learning jobs in fog computing architecture
inferred← citeshttps://doi.org/10.1007/s00607-024-01371-1openalex-snapshot
An IoT-based bag-of-tasks scheduling framework for deadline-sensitive applications in fog-cloud environment
inferred← citeshttps://doi.org/10.1007/s10462-025-11351-2openalex-snapshot
Swarm intelligence techniques and their applications in fog/edge computing: an in-depth review
inferred← citeshttps://doi.org/10.1007/s10586-024-04665-3openalex-snapshot
A novel approach for energy consumption management in cloud centers based on adaptive fuzzy neural systems
inferred← citeshttps://doi.org/10.1007/s10586-024-04873-xopenalex-snapshot
A cost-aware IoT application deployment approach in fog computing
inferred← citeshttps://doi.org/10.1007/s10586-024-05037-7openalex-snapshot
FEAST: Fog enabled auto-scaling technique for IoT-based cloud application
inferred← citeshttps://doi.org/10.1007/s10723-022-09622-1openalex-snapshot
An Autonomous Evolutionary Approach to Planning the IoT Services Placement in the Cloud-Fog-IoT Ecosystem
inferred← citeshttps://doi.org/10.1007/s10922-024-09883-zopenalex-snapshot
A New Blockchain-Based Auction Method for Resource Allocation in Fog Computing Environment
inferred← citeshttps://doi.org/10.1007/s11063-021-10708-2openalex-snapshot
Solving the Multi-Objective Problem of IoT Service Placement in Fog Computing Using Cuckoo Search Algorithm
inferred← citeshttps://doi.org/10.1007/s11227-023-05264-6openalex-snapshot
TTLA: two-way trust between clients and fog servers using Bayesian learning automata
inferred← citeshttps://doi.org/10.1007/s11227-024-06271-xopenalex-snapshot
A trust management system for fog computing using improved genetic algorithm
inferred← citeshttps://doi.org/10.1007/s11227-024-06278-4openalex-snapshot
A learning-based data and task placement mechanism for IoT applications in fog computing: a context-aware approach
inferred← citeshttps://doi.org/10.1007/s11235-024-01106-9openalex-snapshot
Towards a crop pest control system based on the Internet of Things and fuzzy logic
inferred← citeshttps://doi.org/10.1007/s12652-024-04838-3openalex-snapshot
Speech cryptography algorithms: utilizing frequency and time domain techniques merging
inferred← citeshttps://doi.org/10.1007/s42979-024-03175-8openalex-snapshot
DD-SPP: Dynamic and Distributed Service Placement Policy for Optimal Scheduling in Fog-Edge Computing
inferred← citeshttps://doi.org/10.1007/s42979-024-03524-7openalex-snapshot
Latency Aware Adaptive Ant Colony Algorithm for Service Placement for Healthcare Fog
inferred← citeshttps://doi.org/10.1016/j.adhoc.2022.103020openalex-snapshot
Effective multi-controller management and adaptive service deployment strategy in multi-access edge computing environment
inferred← citeshttps://doi.org/10.1016/j.comnet.2024.110771openalex-snapshot
Two-timescale joint service caching and resource allocation for task offloading with edge–cloud cooperation
inferred← citeshttps://doi.org/10.1016/j.comnet.2024.110791openalex-snapshot
Task offloading strategies for mobile edge computing: A survey
inferred← citeshttps://doi.org/10.1016/j.compbiomed.2024.109282openalex-snapshot
Graph neural network-based subgraph analysis for predicting adverse drug events
inferred← citeshttps://doi.org/10.1016/j.cosrev.2024.100650openalex-snapshot
Auto-scaling mechanisms in serverless computing: A comprehensive review
inferred← citeshttps://doi.org/10.1016/j.eswa.2024.124372openalex-snapshot
Optimizing fog colony layout and service placement through genetic algorithms and hierarchical clustering
inferred← citeshttps://doi.org/10.1016/j.jksuci.2024.102170openalex-snapshot
An electricity price and energy-efficient workflow scheduling in geographically distributed cloud data centers
inferred← citeshttps://doi.org/10.1016/j.jpdc.2022.12.001openalex-snapshot
Optimal placement of applications in the fog environment: A systematic literature review
inferred← citeshttps://doi.org/10.1016/j.pmcj.2023.101800openalex-snapshot
Deadline-aware multi-objective IoT services placement optimization in fog environment using parallel FFD-genetic algorithm
inferred← citeshttps://doi.org/10.1016/j.suscom.2024.101037openalex-snapshot
Optimized dynamic service placement for enhanced scheduling in fog-edge computing environments
inferred← citeshttps://doi.org/10.1038/s41598-024-69134-8openalex-snapshot
Trust value evaluation of cloud service providers using fuzzy inference based analytical process
inferred← citeshttps://doi.org/10.1038/s41598-024-81624-3openalex-snapshot
Assessment of cloud service trusted state based on fuzzy entropy and Markov chain
inferred← citeshttps://doi.org/10.1051/itmconf/20268701019openalex-snapshot
A Review of Reliable and Efficient Task Offloading Strategies on Fog Computing Model for IOT Based Applications
inferred← citeshttps://doi.org/10.1063/5.0210175openalex-snapshot
Survey on evaluation environment selection for fog computing application placement problem
inferred← citeshttps://doi.org/10.1080/08839514.2021.2008149openalex-snapshot
An Evolutionary Multi-objective Optimization Technique to Deploy the IoT Services in Fog-enabled Networks: An Autonomous Approach
inferred← citeshttps://doi.org/10.1080/1206212x.2026.2723233openalex-snapshot
A novel improved optimization algorithm for energy-aware service placement in industrial Fog-IoT systems
inferred← citeshttps://doi.org/10.1108/ijicc-06-2024-0253openalex-snapshot
An automatic IoT application placement using an improved equilibrium optimizer algorithm in fog computing
inferred← citeshttps://doi.org/10.1109/access.2024.3350171openalex-snapshot
Deadline and Energy-Aware Application Module Placement in Fog-Cloud Systems
inferred← citeshttps://doi.org/10.1109/caibda70336.2026.11621172openalex-snapshot
Dynamic Governance Technology for Power Knowledge Warehouse Based on Multi-System Data Collaboration under Microservice Architecture
inferred← citeshttps://doi.org/10.1109/icaiss61471.2025.11041977openalex-snapshot
Server Error Control in Distributed Systems: A Comprehensive Review
inferred← citeshttps://doi.org/10.1109/ikt54664.2021.9685175openalex-snapshot
A Novel Service Deployment Policy in Fog Computing Considering The Degree of Availability and Fog Landscape Utilization Using Multiobjective Evolutionary Algorithms
inferred← citeshttps://doi.org/10.1109/inista68122.2025.11249621openalex-snapshot
Real-Time Fog Infrastructure Configuration for Personalized Recommendation Systems in IoT Environments
inferred← citeshttps://doi.org/10.1186/s40537-024-00939-0openalex-snapshot
Data pipeline approaches in serverless computing: a taxonomy, review, and research trends
inferred← citeshttps://doi.org/10.1371/journal.pone.0315545openalex-snapshot
An enhanced genetic-based multi-objective mathematical model for industrial supply chain network
inferred← citeshttps://doi.org/10.18280/ria.380403openalex-snapshot
Discrete Black Widow Optimization Algorithm for Multi-Objective IoT Application Placement in Fog Computing Environments
inferred← citeshttps://doi.org/10.32604/cmc.2024.048833openalex-snapshot
Hybrid Approach for Cost Efficient Application Placement in Fog-Cloud Computing Environments
inferred← citeshttps://doi.org/10.3389/fcomp.2025.1723498openalex-snapshot
Latency and trust constrained fog node selection using deep reinforcement learning
inferred← citeshttps://doi.org/10.51153/kjcis.v82.260openalex-snapshot
A A Spider Web Optimisation Algorithm for improving Queue Tasks on highly loaded Nodes
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.