Various research communities have independently arrived at stream processing as a
programming model for efficient and parallel computing. These communities include digital …

Modern networks provide a variety of interrelated services including routing, traffic
monitoring, load balancing, and access control. Unfortunately, the languages used to …

The IBM Streams Processing Language (SPL) is the programming language for IBM
InfoSphere® Streams, a platform for analyzing Big Data in motion. By “Big Data in motion,” …

The maturity of hardware virtualization has motivated Communication Service Providers
(CSPs) to apply thisparadigm to network services. Virtual Network Functions (VNFs) result …

Continuous queries, also known as standing or streaming queries, are a class of queries
that continuously monitor data sources over time, remaining active until explicitly terminated …

Complex event processing uses patterns to detect composite events in streams of simple
events. Typically, the events are logically partitioned by some key. For instance, the key can …

This paper is a survey of recent stream processing languages, which are programming
languages for writing applications that analyze data streams. Data streams, or continuous …

We present Sigma*, a novel technique for learning symbolic models of software behavior.
Sigma* addresses the challenge of synthesizing models of software by using symbolic …

We present the first language design to uniformly express variants of n-way joins over
asynchronous event streams from different domains, eg, stream-relational algebra, event …

Big data is revolutionizing how all sectors of our economy do business, including
telecommunication, transportation, medical, and finance. Big data comes in two flavors: data …