Placement of microservices-based iot applications in fog computing: A taxonomy and future directions
The Fog computing paradigm utilises distributed, heterogeneous and resource-constrained
devices at the edge of the network for efficient deployment of latency-critical and bandwidth …
devices at the edge of the network for efficient deployment of latency-critical and bandwidth …
A Sparse Sensor Placement Strategy Based on Information Entropy and Data Reconstruction for Ocean Monitoring
Sparse sensor placement strategies are applied to reconstruct a region's full-state data
conditioned to a limited number of sensors; particularly, crucial to ocean monitoring systems …
conditioned to a limited number of sensors; particularly, crucial to ocean monitoring systems …
A distributed microservice-aware paradigm for 6g: Challenges, principles, and research opportunities
Owing to the increasing popularity of online social media, Web 3.0, and Metaverse, mobile
users can access intelligent and self-sustained services more conveniently than before …
users can access intelligent and self-sustained services more conveniently than before …
Graph Reinforcement Learning-based Dependency-Aware Microservice Deployment in Edge Computing
Microservice architecture is a design philosophy that achieves decoupling by decomposing
a monolithic application into multiple lightweight microservices. Meanwhile, edge computing …
a monolithic application into multiple lightweight microservices. Meanwhile, edge computing …
Model-driven dependability assessment of microservice chains in mec-enabled iot
M ulti-access e dge c omputing (MEC)-enabled I nternet of T hings (IoT) is considered as a
promising paradigm to deliver computation-intensive and delay-sensitive services to users …
promising paradigm to deliver computation-intensive and delay-sensitive services to users …
The security and privacy challenges toward cybersecurity of 6G networks: A comprehensive review
The integration of 6G networks with emerging key technologies such as blockchain, artificial
intelligence, and digital twins continues to improve. However, it carries many issues with …
intelligence, and digital twins continues to improve. However, it carries many issues with …
Joint Optimization of Coverage and Reliability for Application Placement in Mobile Edge Computing
Mobile edge computing (MEC) provides a new distributed computing paradigm that
overcomes the inability of cloud computing to offer low end-to-end latency. In a MEC …
overcomes the inability of cloud computing to offer low end-to-end latency. In a MEC …
GeoScale: Microservice Autoscaling With Cost Budget in Geo-Distributed Edge Clouds
K Cheng, S Zhang, M Liu, Y Gu, L Wei… - … on Parallel and …, 2024 - ieeexplore.ieee.org
Deploying microservice instances in geo-distributed edge clouds which are located at the
network edge and in proximity to end-users can provide on-site processing, thereby …
network edge and in proximity to end-users can provide on-site processing, thereby …
AFL-HCS: asynchronous federated learning based on heterogeneous edge client selection
B Tang, Y Xiao, L Zhang, B Cao, M Tang, Q Yang - Cluster Computing, 2024 - Springer
Federated learning (FL) constitutes a potent machine learning paradigm extensively applied
in edge computing for training models on vast datasets. However, the challenges of data …
in edge computing for training models on vast datasets. However, the challenges of data …
Cost‐optimized Internet of Things application deployment in edge computing environment
B Tang, X Zhang, Q Yang, X Qi… - International Journal …, 2023 - Wiley Online Library
With the increasing popularity of cloud native and DevOps, container technology has
become widely used in combination with microservices. However, deploying container …
become widely used in combination with microservices. However, deploying container …