On the public citation graph

A cache‐based approach toward improved scheduling in fog computing

https://doi.org/10.1002/spe.2824
0 signed · 50 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 See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.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/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.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/s10619-015-7173-2openalex-snapshot
Performance analysis of data intensive cloud systems based on data management and replication: a survey
inferredcites →https://doi.org/10.1016/b978-0-12-805395-9.00004-6openalex-snapshot
Fog Computing: principles, architectures, and applications
inferredcites →https://doi.org/10.1016/j.jnca.2017.09.002openalex-snapshot
Survey on fog computing: architecture, key technologies, applications and open issues
inferredcites →https://doi.org/10.1080/17517575.2017.1295321openalex-snapshot
Cost aware cache replacement policy in shared last-level cache for hybrid memory based fog computing
inferredcites →https://doi.org/10.1080/17517575.2017.1304579openalex-snapshot
Fog computing job scheduling optimization based on bees swarm
inferredcites →https://doi.org/10.1109/access.2018.2853148openalex-snapshot
A Survey on the Roles of Communication Technologies in IoT-Based Personalized Healthcare Applications
inferredcites →https://doi.org/10.1109/aina.2015.254openalex-snapshot
Fog Computing Micro Datacenter Based Dynamic Resource Estimation and Pricing Model for IoT
inferredcites →https://doi.org/10.1109/bigdatacongress.2015.87openalex-snapshot
A Community-Based Cloud Computing Caching Service
inferredcites →https://doi.org/10.1109/cc.2016.7445510openalex-snapshot
Fog computing dynamic load balancing mechanism based on graph repartitioning
inferredcites →https://doi.org/10.1109/ee1.2018.8385262openalex-snapshot
Evaluation of low power wide area network technologies for smart urban drainage systems
inferredcites →https://doi.org/10.1109/ficloud.2014.83openalex-snapshot
Fog Computing and Smart Gateway Based Communication for Cloud of Things
inferredcites →https://doi.org/10.1109/icact.2016.7423331openalex-snapshot
A gateway based fog computing architecture for wireless sensors and actuator networks
inferredcites →https://doi.org/10.1109/icact.2016.7423332openalex-snapshot
A gateway based fog computing architecture for wireless sensors and actuator networks
inferredcites →https://doi.org/10.1109/icdcs.2017.83openalex-snapshot
Latency-Driven Cooperative Task Computing in Multi-user Fog-Radio Access Networks
inferredcites →https://doi.org/10.1109/icdcsw.2017.61openalex-snapshot
Router-Based Brokering for Surrogate Discovery in Edge Computing
inferredcites →https://doi.org/10.1109/infcomw.2016.7562149openalex-snapshot
Flowcache: A cache-based approach for improving SDN scalability
inferredcites →https://doi.org/10.1109/infocom.2017.8057196openalex-snapshot
QoE and power efficiency tradeoff for fog computing networks with fog node cooperation
inferredcites →https://doi.org/10.1109/isce.2015.7177778openalex-snapshot
Fog Computing architecture to enable consumer centric Internet of Things services
inferredcites →https://doi.org/10.1109/issnip.2014.6827673openalex-snapshot
Smart gateway based communication for cloud of things
inferredcites →https://doi.org/10.1109/jiot.2019.2957314openalex-snapshot
FESDA: Fog-Enabled Secure Data Aggregation in Smart Grid IoT Network
inferredcites →https://doi.org/10.1109/mcom.2018.1700707openalex-snapshot
Fog Computing Architecture, Evaluation, and Future Research Directions
inferredcites →https://doi.org/10.1109/ntms.2018.8328671openalex-snapshot
A Many-To-One Matching Game Approach to Achieve Low-Latency Exploiting Fogs and Caching
inferredcites →https://doi.org/10.1109/percomw.2016.7457059openalex-snapshot
Analysis of fog model considering computing and communication latency in 5G cellular networks
inferredcites →https://doi.org/10.1109/tcc.2019.2899310openalex-snapshot
A Game-based Thermal-Aware Resource Allocation Strategy for Data Centers
inferredcites →https://doi.org/10.1109/tii.2018.2851241openalex-snapshot
Tasks Scheduling and Resource Allocation in Fog Computing Based on Containers for Smart Manufacturing
inferredcites →https://doi.org/10.1145/2757384.2757397openalex-snapshot
A Survey of Fog Computing
inferredcites →https://doi.org/10.1145/3190645.3190699openalex-snapshot
Prioritized task scheduling in fog computing
inferredcites →https://doi.org/10.48550/arxiv.1502.01815openalex-snapshot
Fog Computing: Focusing on Mobile Users at the Edge
inferredcites →https://doi.org/10.5121/ijcsity.2016.4101openalex-snapshot
Virtual Connection Between Digital and Physical World Based on Sixth Sense Technology

What points at this work

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

inferred← citeshttps://doi.org/10.1002/spe.3006openalex-snapshot
Resource management of IoT edge devices: Challenges, techniques, and solutions
inferred← citeshttps://doi.org/10.1002/spe.3273openalex-snapshot
Energy‐aware resource management in fog computing for IoT applications: A review, taxonomy, and future directions
inferred← citeshttps://doi.org/10.1002/spe.3392openalex-snapshot
Leveraging Fog Computing for Security‐Aware Resource Allocation in Narrowband Internet of Things
inferred← citeshttps://doi.org/10.1007/978-3-031-68952-9_41openalex-snapshot
Secure and Trustworthy Healthcare for the Elderly with Blockchain-Enabled Pervasive Systems
inferred← citeshttps://doi.org/10.1007/978-981-96-5535-9_24openalex-snapshot
Memoization-Based Smart Gateways for Medical IoT
inferred← citeshttps://doi.org/10.1007/s00500-022-07420-1openalex-snapshot
RETRACTED ARTICLE: Prediction of gestational diabetes based on explainable deep learning and fog computing
inferred← citeshttps://doi.org/10.1007/s11227-022-04338-1openalex-snapshot
Classification of resource management approaches in fog/edge paradigm and future research prospects: a systematic review
inferred← citeshttps://doi.org/10.1007/s11227-023-05586-5openalex-snapshot
An efficient resource allocation of IoT requests in hybrid fog–cloud environment
inferred← citeshttps://doi.org/10.1007/s42979-023-02235-9openalex-snapshot
Fog Computing Complete Review: Concepts, Trends, Architectures, Technologies, Simulators, Security Issues, Applications, and Open Research Fields
inferred← citeshttps://doi.org/10.1016/j.asoc.2023.110393openalex-snapshot
An integrated Fuzzy-BWM, Fuzzy-LBWA and V-Fuzzy-CoCoSo-LD model for gateway selection in fog-bolstered Internet of Things
inferred← citeshttps://doi.org/10.1016/j.engappai.2023.105998openalex-snapshot
Optimal fog node selection based on hybrid particle swarm optimization and firefly algorithm in dynamic fog computing services
inferred← citeshttps://doi.org/10.1016/j.rineng.2022.100345openalex-snapshot
An energy efficient and scalable endpoint linked green content caching for Named Data Network based Internet of Things
inferred← citeshttps://doi.org/10.1016/j.swevo.2021.100937openalex-snapshot
Optimization techniques and applications in fog computing: An exhaustive survey
inferred← citeshttps://doi.org/10.1109/iemecon53809.2021.9689109openalex-snapshot
Ai Integration in Data Driven Decision Making for Resource Management in Internet of Things(Iot): A Survey
inferred← citeshttps://doi.org/10.1109/iot69654.2025.11297605openalex-snapshot
Dynamic Task Scheduling and Smart Caching in Fog-Cloud Architectures Using Advantage Actor-Critic Agents
inferred← citeshttps://doi.org/10.1155/int/5268008openalex-snapshot
Joint Planning for Task Scheduling and Task Result Caching in the Fog Using Reinforcement Learning
inferred← citeshttps://doi.org/10.2174/2666255816666220819124133openalex-snapshot
Assessment of Various Scheduling and Load Balancing Algorithms in Integrated Cloud-Fog Environment
inferred← citeshttps://doi.org/10.3233/ais-220613openalex-snapshot
Memoization based priority-aware task management for QoS provisioning in IoT gateways
inferred← citeshttps://doi.org/10.3390/s21072502openalex-snapshot
Health-BlockEdge: Blockchain-Edge Framework for Reliable Low-Latency Digital Healthcare Applications
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.