Since the real-time video analytics with high accuracy requirement is resource-consuming,
the profiles regarding such resource-accuracy trade-off are needed before the analytics for …

Edge computing is a computational paradigm that brings resources closer to the network
edge, such as base stations or gateways, in order to provide quick and efficient computing …

With the advancements in Machine Learning (ML) and edge computing, increasing efforts
have been devoted to edge video analytics. However, most of the existing works fail to …

摘要实时视频流分析在智能监控, 智慧城市, 自动驾驶等场景中具有重要价值. 然而计算负载高,
带宽需求大, 延迟要求严等特点使得实时视频流分析难以通过传统的云计算范式进行部署 …

After the advent of the Internet of Things and 5G networks, edge computing became the
center of attraction. The tasks demanding high computation are generally offloaded to the …

In the era of the IoT revolution, applications are becoming ever more sophisticated and
accompanied by diverse functional and non-functional requirements, including those related …

Multi-Access Edge Computing (MEC) is increasingly growing in prominence as the de facto
enabler for ultra-low latency access to services. MEC averts the high network latencies often …

The recent trend to deploy programmable packet processors in cloud environaxsxsments
enhances the packet processing capability without losing the flexibility to adapt the functions …

Edge computing is a growing paradigm where compute resources are provisioned between
data sources and the cloud to decrease compute latency from data transfer, lower costs …

For the edge cloud-based large-scale distributed systems in wide areas, it is important to
quickly adjust the deployed resource in multiple edge clouds to maximize the resource …