Résumé Le domaine du traitement de flux de données (ou stream processing (SP)) a
émergé comme une réponse au besoin de développer et de déployer des applications pour …

Stream processing answers the need for quickly developing and deploying applications for
real-time processing of continually created data. While its ability to handle a high volume of …

While todays' stream processing applications are typically deployed in the cloud, newly
arising use cases in the context of Internet of Things (IoT) often require low-latency analytics …

Abstract Stream Processing (SP), ie, the processing of data in motion, as soon as it becomes
available, is a hot topic in cloud computing. Various SP stacks exist today, with applications …

In volatile data streams as encountered in the Internet of Things (IoT), the data volume to be
processed changes permanently. Hence, to ensure timely data processing, there is a need …

Fog computing is rapidly changing the distributed computing landscape by extending the
Cloud computing paradigm to include wide-spread resources located at the network edges …

Le déploiement de systèmes de traitement de données en flux (DSP) dans des
infrastructures informatiques géo-distribuées peut combler le fossé entre le Cloud et les …

Data stream processing (DSP) is an interesting computation paradigm in geo-distributed
infrastructures such as Fog computing because it allows one to decentralize the processing …

Abstract The “New Landscapes of the Data Stream Processing in the era of Fog Computing”
special issue aims to present new research works on topics related to recent advances in …

The digital transformation is leading to a constantly increasing volume of data. With the
growth of big data, there is a rising demand for analyzing and making use of those large …