When machine learning meets network management and orchestration in Edge-based networking paradigms
A Shahraki, T Ohlenforst, F Kreyß - Journal of Network and Computer …, 2023 - Elsevier
Caused by the rising of new network types, eg, Internet of Things (IoT), within the last
decade and related challenges like Big Data and data processing delay, new paradigms …
decade and related challenges like Big Data and data processing delay, new paradigms …
Fair and scalable orchestration of network and compute resources for virtual edge services
The combination of service virtualization and edge computing allows for low latency
services, while keeping data storage and processing local. However, given the limited …
services, while keeping data storage and processing local. However, given the limited …
Enabling In-Network Caching in Traditional IP Networks: Selective Router Upgrades and Cooperative Cache Strategies
Enabling in-network caching in a traditional IP network by progressively adding cache-
enabled nodes into the network can provide a variety of advantages, such as efficient …
enabled nodes into the network can provide a variety of advantages, such as efficient …
A game theoretical balancing approach for offloaded tasks in edge datacenters
Edge computing is the next-generation computing paradigm that brings the processing
capability closer to the location where it is needed. 5G and beyond 5G aim to achieve …
capability closer to the location where it is needed. 5G and beyond 5G aim to achieve …
Caching User-Generated Content in Distributed Autonomous Networks via Contextual Bandit
The escalating proliferation of user generated contents such as videos and images are
dominating the network traffic. The optimal strategy for mitigating backbone congestion and …
dominating the network traffic. The optimal strategy for mitigating backbone congestion and …
EdgeVision: Towards Collaborative Video Analytics on Distributed Edges for Performance Maximization
Deep Neural Network (DNN)-based video analytics significantly improves recognition
accuracy in computer vision applications. Deploying DNN models at edge nodes, closer to …
accuracy in computer vision applications. Deploying DNN models at edge nodes, closer to …
Collaborative video analytics on distributed edges with multiagent deep reinforcement learning
G Gao, Y Dong, R Wang - arXiv e-prints, 2022 - ui.adsabs.harvard.edu
Abstract Deep Neural Network (DNN) based video analytics empowers many computer
vision-based applications to achieve high recognition accuracy. To reduce inference delay …
vision-based applications to achieve high recognition accuracy. To reduce inference delay …
Reine: Reinspection Necessity-Based Video Collaborative Edge Caching in Smart Factory
In intelligent factories, multiple industrial cameras capture continuous videos and upload
them to edge nodes for automatic preinspection. For reliability, video chunks with low …
them to edge nodes for automatic preinspection. For reliability, video chunks with low …
Fair DNN Model Selection in Edge AI via A Cooperative Game Approach
Edge intelligence is an emerging paradigm that leverages edge computing to pave the last-
mile delivery of artificial intelligence (AI). To adapt to the resource restriction, model …
mile delivery of artificial intelligence (AI). To adapt to the resource restriction, model …
A Survey on Privacy-Preserving Caching at Network Edge: Classification, Solutions, and Challenges
Caching content at the network edge is a popular and effective technique widely deployed to
alleviate the burden of network backhaul, shorten service delay and improve service quality …
alleviate the burden of network backhaul, shorten service delay and improve service quality …