On the public citation graph
Analytics of Performance and Data Quality for Mobile Edge Cloud Applications
0 signed · 26 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known work and none has been retracted — and get a dated CiteStamped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/10.1016/j.jss.2017.10.033openalex-snapshot
Monitoring self-adaptive applications within edge computing frameworks: A state-of-the-art review
inferredcites →https://doi.org/10.1109/cloud.2015.12openalex-snapshot
Femto Clouds: Leveraging Mobile Devices to Provide Cloud Service at the Edge
inferredcites →https://doi.org/10.1109/cloudnet.2016.56openalex-snapshot
Performance Evaluation of Edge Cloud Computing System for Big Data Applications
inferredcites →https://doi.org/10.1109/comst.2017.2682318openalex-snapshot
Mobile Edge Computing: A Survey on Architecture and Computation Offloading
inferredcites →https://doi.org/10.1109/ficloud.2015.35openalex-snapshot
Containers and Clusters for Edge Cloud Architectures -- A Technology Review
inferredcites →https://doi.org/10.1109/mcc.2015.23openalex-snapshot
Principles for Engineering IoT Cloud Systems
inferredcites →https://doi.org/10.1109/mcom.2015.7120041openalex-snapshot
On the computation offloading at ad hoc cloudlet: architecture and service modes
inferredcites →https://doi.org/10.1109/tc.2016.2620469openalex-snapshot
Hybrid Method for Minimizing Service Delay in Edge Cloud Computing Through VM Migration and Transmission Power Control
inferredcites →https://doi.org/10.1109/tnet.2015.2487344openalex-snapshot
Efficient Multi-User Computation Offloading for Mobile-Edge Cloud Computing
inferredcites →https://doi.org/10.1109/ucc.2014.15openalex-snapshot
Stream Bench: Towards Benchmarking Modern Distributed Stream Computing Frameworks
inferredcites →https://doi.org/10.1111/j.1467-9671.2009.01152.xopenalex-snapshot
Accuracy of iPhone Locations: A Comparison of Assisted GPS, WiFi and Cellular Positioning
inferredcites →https://doi.org/10.1145/1807128.1807152openalex-snapshot
Benchmarking cloud serving systems with YCSB
inferredcites →https://doi.org/10.1145/3152360.3152361openalex-snapshot
Towards a middleware for mobile edge-cloud applications
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-030-99200-2_13openalex-snapshot
Distributed Deep Reinforcement Learning Based Mode Selection and Resource Allocation for VR Transmission in Edge Networks
inferred← citeshttps://doi.org/10.1007/s00607-018-0683-9openalex-snapshot
A distributed, proactive intelligent scheme for securing quality in large scale data processing
inferred← citeshttps://doi.org/10.1016/b978-0-443-21640-4.00003-xopenalex-snapshot
Big Data quality assessment in the IoT era
inferred← citeshttps://doi.org/10.1016/j.cosrev.2025.100844openalex-snapshot
Distributed edge artificial intelligence empowered data trading: Theories, algorithms, and applications
inferred← citeshttps://doi.org/10.1109/access.2019.2896000openalex-snapshot
Matching-Based Task Offloading for Vehicular Edge Computing
inferred← citeshttps://doi.org/10.1109/access.2020.2979970openalex-snapshot
A Simulation-Based Optimization Approach for Reliability-Aware Service Composition in Edge Computing
inferred← citeshttps://doi.org/10.1109/cloudsummit54781.2022.00019openalex-snapshot
Context-Aware Feature Selection using Denoising Auto-Encoder for Fault Detection in Cloud Environments
inferred← citeshttps://doi.org/10.1109/isncc49221.2020.9297191openalex-snapshot
Lightweight cryptographic URLLC for 5G-V2X
inferred← citeshttps://doi.org/10.1109/jiot.2020.2978516openalex-snapshot
Blockchain-Enabled Software-Defined Industrial Internet of Things With Deep Reinforcement Learning
inferred← citeshttps://doi.org/10.1109/twc.2019.2955129openalex-snapshot
Adaptive Video Streaming With Edge Caching and Video Transcoding Over Software-Defined Mobile Networks: A Deep Reinforcement Learning Approach
inferred← citeshttps://doi.org/10.1155/2020/8822990openalex-snapshot
Deploying GIS Services into the Edge: A Study from Performance Evaluation and Optimization Viewpoint
inferred← citeshttps://doi.org/10.23919/cje.2023.00.264openalex-snapshot
Multi-Dimensional QoS Evaluation and Optimization of Mobile Edge Computing for IoT: A Survey
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.