Cargando…

Self-* Capabilities of Cloud-Edge Nodes: A Research Review

Most recent edge and fog computing architectures aim at pushing cloud-native traits at the edge of the network, reducing latency, power consumption, and network overhead, allowing operations to be performed close to data sources. To manage these architectures in an autonomous way, systems that mater...

Descripción completa

Detalles Bibliográficos
Autores principales:	S-Julián, Raúl, Lacalle, Ignacio, Vaño, Rafael, Boronat, Fernando, Palau, Carlos E.
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2023
Materias:	Review
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10058210/ https://www.ncbi.nlm.nih.gov/pubmed/36991641 http://dx.doi.org/10.3390/s23062931

Ejemplares similares

Cloud-Native Workload Orchestration at the Edge: A Deployment Review and Future Directions
por: Vaño, Rafael, et al.
Publicado: (2023)

Framework and Methodology for Establishing Port-City Policies Based on Real-Time Composite Indicators and IoT: A Practical Use-Case
por: Lacalle, Ignacio, et al.
Publicado: (2020)

Design and Development of an AIoT Architecture for Introducing a Vessel ETA Cognitive Service in a Legacy Port Management Solution
por: Valero, Clara I., et al.
Publicado: (2021)

Energy Efficient Node Selection in Edge-Fog-Cloud Layered IoT Architecture
por: Fereira, Rolden, et al.
Publicado: (2023)

Orchestrating and automating security for the Internet of Things: delivering advanced security capabilities from Edge to Cloud for IoT
por: Sabella, Anthony, et al.
Publicado: (2018)

Research on evaluation index method of cloud-network convergence capability
por: Ma, Tengteng, et al.
Publicado: (2023)

Research on Lightweight Microservice Composition Technology in Cloud-Edge Device Scenarios
por: Li, Hanqi, et al.
Publicado: (2023)

Infrastructure as Software in Micro Clouds at the Edge
por: Simić, Miloš, et al.
Publicado: (2021)

Beginning Azure IoT Edge computing: extending the cloud to the intelligent edge
por: Jensen, David
Publicado: (2019)

Practical Deep Learning for Cloud, Mobile, and Edge
por: Koul, Anirudh
Publicado: (2019)

Cloud Robotik: Ein Kubernetes-basierter Ansatz zu Cloud-Edge Integration
por: Ricken, Karl-Albrecht, et al.
Publicado: (2020)

Research on the Rapid Diagnostic Method of Rolling Bearing Fault Based on Cloud–Edge Collaboration
por: Tang, Xianghong, et al.
Publicado: (2022)

Research on Four-Dimensional Innovative Intelligent Education Platform Based on Cloud Edge-End Architecture
por: Wang, Buyu, et al.
Publicado: (2023)

When Sensor-Cloud Meets Mobile Edge Computing
por: Wang, Tian, et al.
Publicado: (2019)

A Survey of Security in Cloud, Edge, and Fog Computing
por: Ometov, Aleksandr, et al.
Publicado: (2022)

Capabilities and Advantages of Cloud Computing in the Implementation of Electronic Health Record
por: Ahmadi, Maryam, et al.
Publicado: (2018)

Retracted: Research on Four-Dimensional Innovative Intelligent Education Platform Based on Cloud Edge-End Architecture
por: Intelligence and Neuroscience, Computational
Publicado: (2023)

Seismic Waveform Inversion Capability on Resource-Constrained Edge Devices
por: Manu, Daniel, et al.
Publicado: (2022)

Foundational elements of an IoT solution: the edge, the cloud, and application development
por: Biron, Joe, et al.
Publicado: (2016)

Method to Increase Dependability in a Cloud-Fog-Edge Environment
por: Stan, Ovidiu Petru, et al.
Publicado: (2021)

QoS-Based Service-Time Scheduling in the IoT-Edge Cloud
por: Mutichiro, Briytone, et al.
Publicado: (2021)

Modified firefly algorithm for workflow scheduling in cloud-edge environment
por: Bacanin, Nebojsa, et al.
Publicado: (2022)

Quality of Service Aware Orchestration for Cloud–Edge Continuum Applications
por: Orive, Adrián, et al.
Publicado: (2022)

Pangea: An MLOps Tool for Automatically Generating Infrastructure and Deploying Analytic Pipelines in Edge, Fog and Cloud Layers
por: Miñón, Raúl, et al.
Publicado: (2022)

Research on Cloud-Edge-End Collaborative Computing Offloading Strategy in the Internet of Vehicles Based on the M-TSA Algorithm
por: Xu, Qiliang, et al.
Publicado: (2023)

Gene Expression Profiling in the Injured Spinal Cord of Trachemys scripta elegans: An Amniote with Self-Repair Capabilities
por: Valentin-Kahan, Adrián, et al.
Publicado: (2017)

Capability of airline jets as an observation platform for noctilucent clouds at middle latitudes
por: Suzuki, Hidehiko, et al.
Publicado: (2022)

Enabling the Orchestration of IoT Slices through Edge and Cloud Microservice Platforms
por: Fernandez, Juan-Manuel, et al.
Publicado: (2019)

An Edge-Fog-Cloud Architecture of Streaming Analytics for Internet of Things Applications
por: Cao, Hung, et al.
Publicado: (2019)

Optimal Design of Hierarchical Cloud-Fog&Edge Computing Networks with Caching
por: Fan, Xiaoqian, et al.
Publicado: (2020)

Edge and Cloud Collaborative Entity Recommendation Method towards the IoT Search
por: Wang, Ruyan, et al.
Publicado: (2020)

Osmotic Cloud-Edge Intelligence for IoT-Based Cyber-Physical Systems
por: Loseto, Giuseppe, et al.
Publicado: (2022)

Recent Advances in Evolving Computing Paradigms: Cloud, Edge, and Fog Technologies
por: Angel, Nancy A, et al.
Publicado: (2021)

On the Efficient Delivery and Storage of IoT Data in Edge–Fog–Cloud Environments
por: Barron, Alfredo, et al.
Publicado: (2022)

Optimizing Face Recognition Inference with a Collaborative Edge–Cloud Network
por: Oroceo, Paul P., et al.
Publicado: (2022)

Edge-Cloud Collaborative Defense against Backdoor Attacks in Federated Learning
por: Yang, Jie, et al.
Publicado: (2023)

On the Location of Fog Nodes in Fog-Cloud Infrastructures
por: C. da Silva, Rodrigo A., et al.
Publicado: (2019)

The Use of Internet of Things and Cloud Computing Technology in the Performance Appraisal Management of Innovation Capability of University Scientific Research Team
por: Meng, Siyu, et al.
Publicado: (2022)

Living on the edge: network neuroscience beyond nodes
por: Betzel, Richard F., et al.
Publicado: (2023)

A Novel Automate Python Edge-to-Edge: From Automated Generation on Cloud to User Application Deployment on Edge of Deep Neural Networks for Low Power IoT Systems FPGA-Based Acceleration
por: Belabed, Tarek, et al.
Publicado: (2021)

Cannot write session to /tmp/vufind_sessions/sess_oi9qd2uno4jiqus1v03f6vv7oo