Haywire – A System for Visualizing and Analyzing Streaming IoT Data

In recent years there has been a notable trend towards streaming data systems. The Internet of Things has transformed the Internet into a massive collection of live data streams. These streams range from slowly trickling sensor data from, e.g., residential water or gas meters to very bandwidth-hungry high-definition 360 degree live video streams. In a complex IoT system with thousands of data streams, one of the challenges for system developers and maintainers is the ability to ensure that data in all streams is flowing normally. In this paper we present a system for visualizing streaming data in a quick “at-a-glance” fashion. The Haywire system constructs and dynamically maintains a live 3D graph representation of all streams, and presents the streams in a graphical Web UI with force-directed layout. The user interface includes detailed message statistics and the ability to quickly dive deeper into individual streams if any anomalies are detected in their behavior.

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Publication Details

Published
2024-09-02
DOI
https://doi.org/10.1109/fmec62297.2024.10710184
Citations
1
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
0.27
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article

Haywire – A System for Visualizing and Analyzing Streaming IoT Data

Antero Taivalsaari
1 citations
Traffic Prediction and Management Techniques
0.27
article

Haywire – A System for Visualizing and Analyzing Streaming IoT Data

Antero Taivalsaari
article en
1 citations

Abstract

In recent years there has been a notable trend towards streaming data systems. The Internet of Things has transformed the Internet into a massive collection of live data streams. These streams range from slowly trickling sensor data from, e.g., residential water or gas meters to very bandwidth-hungry high-definition 360 degree live video streams. In a complex IoT system with thousands of data streams, one of the challenges for system developers and maintainers is the ability to ensure that data in all streams is flowing normally. In this paper we present a system for visualizing streaming data in a quick “at-a-glance” fashion. The Haywire system constructs and dynamically maintains a live 3D graph representation of all streams, and presents the streams in a graphical Web UI with force-directed layout. The user interface includes detailed message statistics and the ability to quickly dive deeper into individual streams if any anomalies are detected in their behavior.

Tampere University (FI), Nokia (Finland) (FI)
Openalex Percentile: Top 43%
Traffic Prediction and Management Techniques
0.27
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