Data centers are widely used for big data analytics, which often involve data-parallel jobs,
including query and web service. Meanwhile, cluster frameworks are rapidly developed for …

The world is witnessing an unprecedented increase in camera deployment. The USA and
UK, for instance, have one camera for every 8 people. Video analytics from these cameras …

Detecting activities from video taken with a single camera is an active research area for ML-
based machine vision. In this paper, we examine the next research frontier: near real-time …

Elasticity—scaling out or in depending upon resource demand or availability—allows a
system to improve its efficiency or performance. This leads to potentially significant cost …

Fully autonomous aerial systems (FAAS) fly complex missions guided wholly by software. If
users choose software, compute hardware and aircraft well, FAAS can complete missions …

We present a new video storage system (VSS) designed to decouple high-level video
operations from the low-level details required to store and efficiently retrieve video data. VSS …

The advent of high-accuracy and resource-intensive deep neural networks (DNNs) has
fulled the development of live video analytics, where camera videos need to be streamed …

Elf is a runtime for an energy-constrained camera to continuously summarize video scenes
as approximate object counts. Elf's novelty centers on planning the camera's count actions …

Major cities worldwide have millions of cameras deployed for surveillance, business
intelligence, traffic control, crime prevention, etc. Real-time analytics on video data demands …

Machine learning models are becoming the primary work-horses for many applications.
Services deploy models through prediction serving systems that take in queries and return …