On the public citation graph
Animation Rendering on Multimedia Fog Computing Platforms
0 signed · 38 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known work and none has been retracted — and get a dated CiteStamped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/10.1007/s10586-010-0145-4openalex-snapshot
A multi-strategy collaborative prediction model for the runtime of online tasks in computing cluster/grid
inferredcites →https://doi.org/10.1007/s12083-007-0006-yopenalex-snapshot
A survey on peer-to-peer video streaming systems
inferredcites →https://doi.org/10.1016/j.neunet.2014.09.003openalex-snapshot
Deep learning in neural networks: An overview
inferredcites →https://doi.org/10.1109/ccgrid.2009.69openalex-snapshot
Modeling Job Lifespan Delays in Volunteer Computing Projects
inferredcites →https://doi.org/10.1109/ccgrid.2015.60openalex-snapshot
Statistical Characterization of Business-Critical Workloads Hosted in Cloud Datacenters
inferredcites →https://doi.org/10.1109/grid.2004.14openalex-snapshot
BOINC: A System for Public-Resource Computing and Storage
inferredcites →https://doi.org/10.1109/icpads.2010.34openalex-snapshot
Towards a P2P Cloud: Reliable Resource Reservations in Unreliable P2P Systems
inferredcites →https://doi.org/10.1109/itime.2009.5236386openalex-snapshot
A Cloud Computing Platform Based on P2P
inferredcites →https://doi.org/10.1109/mprv.2009.82openalex-snapshot
The Case for VM-Based Cloudlets in Mobile Computing
inferredcites →https://doi.org/10.1109/wcncw.2013.6533324openalex-snapshot
Context-aware decision engine for mobile cloud offloading
inferredcites →https://doi.org/10.1111/j.1467-985x.2010.00646_6.xopenalex-snapshot
The Elements of Statistical Learning: Data Mining, Inference, and Prediction
inferredcites →https://doi.org/10.1145/1551609.1551632openalex-snapshot
Trace-based evaluation of job runtime and queue wait time predictions in grids
inferredcites →https://doi.org/10.1145/2245276.2245357openalex-snapshot
Design and implementation of a P2P Cloud system
inferredcites →https://doi.org/10.1145/2342509.2342513openalex-snapshot
Fog computing and its role in the internet of things
inferredcites →https://doi.org/10.1198/jasa.2003.s269openalex-snapshot
Learning With Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/s12083-019-00729-zopenalex-snapshot
Multimedia intelligent fog computing scheme based on robust perception for complex networks
inferred← citeshttps://doi.org/10.1007/s42514-022-00109-9openalex-snapshot
Status, challenges and trends of data-intensive supercomputing
inferred← citeshttps://doi.org/10.1016/j.sysarc.2019.02.009openalex-snapshot
All one needs to know about fog computing and related edge computing paradigms: A complete survey
inferred← citeshttps://doi.org/10.1109/access.2019.2947542openalex-snapshot
A Review of Fog Computing and Machine Learning: Concepts, Applications, Challenges, and Open Issues
inferred← citeshttps://doi.org/10.1109/apnoms.2017.8094194openalex-snapshot
Distributed analytics in fog computing platforms using tensorflow and kubernetes
inferred← citeshttps://doi.org/10.1109/cloudcom.2017.45openalex-snapshot
Supporting Internet-of-Things Analytics in a Fog Computing Platform
inferred← citeshttps://doi.org/10.1109/cloudcom.2017.53openalex-snapshot
From Cloud Computing to Fog Computing: Unleash the Power of Edge and End Devices
inferred← citeshttps://doi.org/10.1109/comst.2023.3338015openalex-snapshot
AI-Empowered Fog/Edge Resource Management for IoT Applications: A Comprehensive Review, Research Challenges, and Future Perspectives
inferred← citeshttps://doi.org/10.1109/icc.2018.8423003openalex-snapshot
Fogbed: A Rapid-Prototyping Emulation Environment for Fog Computing
inferred← citeshttps://doi.org/10.1109/icds47004.2019.8942304openalex-snapshot
A Review On Relationship Between Iot– Cloud Computing – Fog Computing (Applications And Challenges)
inferred← citeshttps://doi.org/10.1109/ipccc47392.2019.8958741openalex-snapshot
piFogBed: A Fog Computing Testbed Based on Raspberry Pi
inferred← citeshttps://doi.org/10.1109/isc246665.2019.9071674openalex-snapshot
From cloud computing to fog computing: two technologies to serve iot–a review-
inferred← citeshttps://doi.org/10.1109/iscc.2018.8538484openalex-snapshot
Scalable Fogbed for Fog Computing Emulation
inferred← citeshttps://doi.org/10.1145/3326066openalex-snapshot
Resource Management in Fog/Edge Computing
inferred← citeshttps://doi.org/10.1145/3748522.3779848openalex-snapshot
A Volunteer Computing Framework for IoT Devices using Intermittent Computing
inferred← citeshttps://doi.org/10.4108/eai.23-12-2020.167788openalex-snapshot
A Survey of Architecture, Framework and Algorithms for Resource Management in Edge Computing
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.