Serverless Empowered Video Analytics for Ubiquitous Networked Cameras

Ubiquitous deployment of networked cameras has boosted the prevalence of video analytics. Leveraging machines to automatically analyze captured videos has become the driving force behind a variety of contemporary applications. However, it is known to be resource-hungry with highly dynamic demands, which mismatches the existing monolithic cloud service deployment with coarse-grained resource allocation. Recent advances in serverless computing, which offers ultra-fast and fine-grained autoscaling, would become a game-changer. This article closely examines the potential and challenges of serverless computing in building modern video analytics applications. We accordingly present an integrated framework with geo-distributed resources, and identify the critical design issues toward its implementation. We further discuss a series of promising research directions in this field.