Video cameras are pervasively deployed for security and smart city scenarios, with millions
of them in large cities worldwide. Achieving the potential of these cameras requires …

Distributed stream processing systems need to support stateful processing, recover quickly
from failures to resume such processing, and reprocess an entire data stream quickly. We …

Large volumes of videos are continuously recorded from cameras deployed for traffic control
and surveillance with the goal of answering “after the fact” queries: identify video frames with …

Programmable data plane hardware creates new opportunities for infusing intelligence into
the network. This raises a fundamental question: what kinds of computation should be …

Stateful serverless analytics can be enabled using a remote memory system for inter-task
communication, and for storing and exchanging intermediate data. However, existing …

Large scale streaming systems aim to provide high throughput and low latency. They are
often used to run mission-critical applications, and must be available 24x7. Thus such …

An increasingly important system requirement for distributed stream processing applications
is to provide strong correctness guarantees under unexpected failures and out-of-order data …

Stream processing has been an active research field for more than 20 years, but it is now
witnessing its prime time due to recent successful efforts by the research community and …

Many Internet of Things (IoT) applications would benefit if streams of data could be analyzed
rapidly at the Edge, near the data source. However, existing Stream Processing Engines …

Stream analytics on real-time events has an insatiable demand for throughput and latency.
Its performance on a single machine is central to meeting this demand, even in a distributed …