… Inspired by the above, a mobile edge-assisted video camera network in this paper is … .1 for
video analytics. For convenience, we use the edge node to represent the mobile edge node in …

… Our paper aims to efficiently assign dependent tasks to multiple collaborative edge nodes
with appropriate video configuration, to achieve low latency while maintain accuracy. Firstly, …

… the prior edge-cloud systems. We present Runespoor, an edge-cloud video analytics system
to … Kaminsky, and SR Dulloor, “Scaling video analytics on constrained edge nodes,” in 2nd …

… Considering the limited number of edge nodes in the real-word edge video analytics
system (see Table 4), we only conducted the performance comparison under 1 to 5 …

… analytics bring an overwhelming burden for vehicular networks. Moreover, owing to the unstable
network connection, the video … a video analytics framework, where the multiaccess edge …

… We present CEVAS, a video analytics system that integrates the edge and cloud resources
to have the best of both worlds and leverages serverless computing to tackle the challenges …

… on our IoT camera edge cloud testbed, … video analytic cloud services. The rest of the paper
is organized as follows: In Section 2, we explain a motivating video analytics scenario in edge …

… Our objective is to design a real-time edgecloud video analytics system that saves as
much bandwidth as possible while still achieving high inference accuracy and low latency. To …

… As a result, edge nodes in the AGVs networks are empowered to store popular … For
future work, we will investigate edge video analytics of vehicular networks in more generated …

… In order to solve P3, EdgeURB assigns a ‘Helper’ process to each user device (randomly
or from the nearest edge node). The helpers apply the Best Response Strategy algorithm in …