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Managing and Deploying Distributed and Deep Neural Models Through Kafka-ML in the Cloud-to-Things Continuum

https://doi.org/10.1109/access.2021.3110291
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What this work says

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

inferredcites →https://doi.org/10.1007/978-3-319-89803-2_8openalex-snapshot
Large-Scale Learning from Data Streams with Apache SAMOA
inferredcites →https://doi.org/10.1007/s10462-018-09679-zopenalex-snapshot
Machine Learning and Deep Learning frameworks and libraries for large-scale data mining: a survey
inferredcites →https://doi.org/10.1007/s10723-019-09498-8openalex-snapshot
IoTEF: A Federated Edge-Cloud Architecture for Fault-Tolerant IoT Applications
inferredcites →https://doi.org/10.1016/j.future.2019.10.043openalex-snapshot
HealthFog: An ensemble deep learning based Smart Healthcare System for Automatic Diagnosis of Heart Diseases in integrated IoT and fog computing environments
inferredcites →https://doi.org/10.1016/j.future.2021.07.037openalex-snapshot
Kafka-ML: Connecting the data stream with ML/AI frameworks
inferredcites →https://doi.org/10.1016/j.jnca.2016.01.010openalex-snapshot
State-of-the-art, challenges, and open issues in the integration of Internet of things and cloud computing
inferredcites →https://doi.org/10.1016/j.jnca.2017.12.001openalex-snapshot
Distributed data stream processing and edge computing: A survey on resource elasticity and future directions
inferredcites →https://doi.org/10.1016/j.jss.2018.03.032openalex-snapshot
DIANNE: a modular framework for designing, training and deploying deep neural networks on heterogeneous distributed infrastructure
inferredcites →https://doi.org/10.1016/j.jss.2018.09.082openalex-snapshot
The pains and gains of microservices: A Systematic grey literature review
inferredcites →https://doi.org/10.1016/j.measurement.2018.01.022openalex-snapshot
A machine learning model for improving healthcare services on cloud computing environment
inferredcites →https://doi.org/10.1016/j.pmcj.2020.101321openalex-snapshot
Assessing the impact of unbalanced resources and communications in edge computing
inferredcites →https://doi.org/10.1016/j.sysarc.2021.102214openalex-snapshot
An open source framework based on Kafka-ML for Distributed DNN inference over the Cloud-to-Things continuum
inferredcites →https://doi.org/10.1080/23270012.2019.1570365openalex-snapshot
Artificial intelligence: a survey on evolution, models, applications and future trends
inferredcites →https://doi.org/10.1109/access.2017.2694446openalex-snapshot
Disease Prediction by Machine Learning Over Big Data From Healthcare Communities
inferredcites →https://doi.org/10.1109/cts.2013.6567202openalex-snapshot
Big data: A review
inferredcites →https://doi.org/10.1109/icdcs.2017.226openalex-snapshot
Distributed Deep Neural Networks Over the Cloud, the Edge and End Devices
inferredcites →https://doi.org/10.1109/icpr.2016.7900006openalex-snapshot
BranchyNet: Fast inference via early exiting from deep neural networks
inferredcites →https://doi.org/10.1109/infocom.2019.8737614openalex-snapshot
Dynamic Adaptive DNN Surgery for Inference Acceleration on the Edge
inferredcites →https://doi.org/10.1109/infocom41043.2020.9155237openalex-snapshot
Distributed Inference Acceleration with Adaptive DNN Partitioning and Offloading
inferredcites →https://doi.org/10.1109/iscon47742.2019.9036216openalex-snapshot
EdgeLens: Deep Learning based Object Detection in Integrated IoT, Fog and Cloud Computing Environments
inferredcites →https://doi.org/10.1109/isorc.2018.00021openalex-snapshot
An Edge Computing Architecture in the Internet of Things
inferredcites →https://doi.org/10.1109/lwc.2019.2894703openalex-snapshot
AAIoT: Accelerating Artificial Intelligence in IoT Systems
inferredcites →https://doi.org/10.1109/twc.2019.2946140openalex-snapshot
Edge AI: On-Demand Accelerating Deep Neural Network Inference via Edge Computing
inferredcites →https://doi.org/10.1145/1920261.1920263openalex-snapshot
Detecting spammers on social networks
inferredcites →https://doi.org/10.1145/3065386openalex-snapshot
ImageNet classification with deep convolutional neural networks
inferredcites →https://doi.org/10.1145/3359309openalex-snapshot
"You Know What to Do"
inferredcites →https://doi.org/10.1177/1475921718757405openalex-snapshot
Computer vision and deep learning–based data anomaly detection method for structural health monitoring
inferredcites →https://doi.org/10.3390/ecsa-7-08260openalex-snapshot
Real-Time Concrete Crack Detection and Instance Segmentation using Deep Transfer Learning
inferredcites →https://doi.org/10.48550/arxiv.1912.01703openalex-snapshot
PyTorch: An Imperative Style, High-Performance Deep Learning Library
inferredcites →https://doi.org/10.57702/zp44cu3gopenalex-snapshot
Learning Multiple Layers of Features from Tiny Images

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.4681565openalex-extracted
inferred← citeshttps://doi.org/10.1002/cpe.70259openalex-snapshot
A Comprehensive Soft Error Resiliency Analysis of Distributed Deep Neural Networks
inferred← citeshttps://doi.org/10.1002/spe.3318openalex-snapshot
Functions as a service for distributed deep neural network inference over the cloud‐to‐things continuum
inferred← citeshttps://doi.org/10.1007/978-3-031-33808-3_17openalex-snapshot
A Methodology for the Development of Soft Sensors with Kafka-ML
inferred← citeshttps://doi.org/10.1007/978-3-031-90109-6_8openalex-snapshot
Resilience in the Cloud-to-Things Continuum
inferred← citeshttps://doi.org/10.1007/s00521-024-10136-yopenalex-snapshot
Distributed intelligence for IoT-based smart cities: a survey
inferred← citeshttps://doi.org/10.1016/j.future.2024.06.001openalex-snapshot
Online learning and continuous model upgrading with data streams through the Kafka-ML framework
inferred← citeshttps://doi.org/10.1016/j.iot.2023.101036openalex-snapshot
Towards flexible data stream collaboration: Federated Learning in Kafka-ML
inferred← citeshttps://doi.org/10.1016/j.jocs.2024.102522openalex-snapshot
A soft sensor open-source methodology for inexpensive monitoring of water quality: A case study of NO3− concentrations
inferred← citeshttps://doi.org/10.1109/access.2023.3303810openalex-snapshot
A Survey on Networked Data Streaming With Apache Kafka
inferred← citeshttps://doi.org/10.1109/aimv66517.2025.11203535openalex-snapshot
Agentic AI-Driven Real-Time Inventory Management Using Distributed Cloud Architectures and Machine Learning
inferred← citeshttps://doi.org/10.1109/bigdata62323.2024.10826034openalex-snapshot
Federated Learning Meets Blockchain: A Kafka-ML Integration for reliable model training using data streams
inferred← citeshttps://doi.org/10.1109/edgecom66327.2025.00009openalex-snapshot
Astrolabe: Optimising Edge Inference through Multi-Depth Model Orchestration
inferred← citeshttps://doi.org/10.1109/icfeict57213.2022.00101openalex-snapshot
An Integrated Service Bus Based on Microservice
inferred← citeshttps://doi.org/10.1109/icnp61940.2024.10858547openalex-snapshot
Towards Multi-Tier Stream Data Tiering in the Cloud-Edge Continuum
inferred← citeshttps://doi.org/10.1109/tnsm.2023.3260039openalex-snapshot
Unsupervised GAN-Based Intrusion Detection System Using Temporal Convolutional Networks and Self-Attention
inferred← citeshttps://doi.org/10.1109/wincom62286.2024.10654814openalex-snapshot
Distributed Federated and Incremental Learning for Electric Vehicles Model Development in Kafka-ML
inferred← citeshttps://doi.org/10.1186/s42400-022-00133-wopenalex-snapshot
An ensemble deep learning based IDS for IoT using Lambda architecture
inferred← citeshttps://doi.org/10.3390/app13137956openalex-snapshot
Hybrid Services Collaborative Resource Scheduling Strategy towards Artificial Intelligence of Things
inferred← citeshttps://doi.org/10.61978/digitus.v3i4.959openalex-snapshot
Real Time Mobility Intelligence: Evaluating Kafka Based Pipelines in Global Smart Transit Systems
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