This paper provides a review of the consensus problem as one of the most challenging
issues in the distributed control of the multi-agent systems (MASs). In this survey, firstly, the …

Distributed computing has become a common approach for large-scale computation tasks
due to benefits such as high reliability, scalability, computation speed, and cost …

We present a system for training deep neural networks for object detection using synthetic
images. To handle the variability in real-world data, the system relies upon the technique of …

Large cloud service providers have invested in increasingly larger datacenters to house the
computing infrastructure required to support their services. Accordingly, researchers and …

How can we optimally trade extra computing power to reduce the communication load in
distributed computing? We answer this question by characterizing a fundamental tradeoff …

The initial design of Apache Hadoop [1] was tightly focused on running massive,
MapReduce jobs to process a web crawl. For increasingly diverse companies, Hadoop has …

We present SWAN, a system that boosts the utilization of inter-datacenter networks by
centrally controlling when and how much traffic each service sends and frequently re …

Tasks in modern data parallel clusters have highly diverse resource requirements, along
CPU, memory, disk and network. Any of these resources may become bottlenecks and …

Reconstructing the detailed geometric structure of a face from a given image is a key to
many computer vision and graphics applications, such as motion capture and reenactment …

Low latency analytics on geographically distributed datasets (across datacenters, edge
clusters) is an upcoming and increasingly important challenge. The dominant approach of …