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Database Systems and Information Management GroupNewest work on the NebulaStream System by Database Systems Researchers of TU Berlin and DFKI will be Presented at VLIoT 2020

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Newest work on the NebulaStream System by Database Systems Researchers of TU Berlin and DFKI will be Presented at VLIoT 2020

The Paper “NebulaStream: Complex Analytics Beyond the Cloud” by Steffen Zeuch, Eleni Tzirita Zacharatou, Shuhao Zhang, Xenofon Chatziliadis, Ankit Chaudhary, Bonaventura DelMonte, Philipp M. Grulich, Dimitrios Giouroukis, Ariane Ziehn, Volker Markl was accepted for presentation at the 2020 International Workshop on Very Large Internet of Things (VLIoT 2020). VLIoT 2020 will take place in conjunction with the VLDB 2020 conference on September 4, 2020.
In this paper, the NebulaStream (NES) project team shows why there is a need for a new End-to-End data processing systems for the Internet of Things (IoT). NES deals with the heterogeneity and distribution of computers and data, supports various data and programming models that go beyond relational algebra and addresses potentially unreliable communication. The NebulaStream platform enables new IoT applications in various application areas.

Abstract:

The arising Internet of Things (IoT) will require significant changes to current stream processing engines (SPEs) to enable large-scale IoT applications. In this paper, we present challenges and opportunities for an IoT data management system to enable complex analytics beyond the cloud. As one of the most important upcoming IoT applications, we focus on the vision of a smart city. The goal of this paper is to bridge the gap between the requirements of upcoming IoT applications and the supported features of an IoT data management system. To this end, we outline how state-of-the-art SPEs have to change to exploit the new capabilities of the IoT and showcase how we tackle IoT challenges in our own system, NebulaStream. This paper lays the foundation for a new type of systems that leverages the IoT to enable large-scale applications over millions of IoT devices in highly dynamic and geo-distributed environments.

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