Distributed data stream processing and task placement on edge-cloud infrastructure

Abstract

Indubitable growth of smart and connected edge devices with substantial processing power has made ubiquitous computing possible. These edge devices either produce streams of information related to the environment in which they are deployed or the devices can be located in proximity to such information producers. Distributed Data Stream Processing is a programming paradigm that is introduced to process these event streams to acquire relevant insights in order to make informed decisions. While deploying data stream processing frameworks on distributed cloud infrastructure has been the convention, for latency critical real-time applications that rely on data streams produced outside the cloud o..