Munin : A Peer-to-Peer Middleware for Ubiquitous Analytics and Visualization Spaces

We present Munin, a software framework for building ubiquitous analytics environments consisting of multiple input and output surfaces, such as tabletop displays, wall-mounted displays, and mobile devices. Munin utilizes a service-based model where each device provides one or more dynamically loaded...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on visualization and computer graphics. - 1998. - 21(2015), 2 vom: 10. Feb., Seite 215-28
1. Verfasser: Badam, Sriram Karthik (VerfasserIn)
Weitere Verfasser: Fisher, Eli, Elmqvist, Niklas
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2015
Zugriff auf das übergeordnete Werk:IEEE transactions on visualization and computer graphics
Schlagworte:Journal Article
Beschreibung
Zusammenfassung:We present Munin, a software framework for building ubiquitous analytics environments consisting of multiple input and output surfaces, such as tabletop displays, wall-mounted displays, and mobile devices. Munin utilizes a service-based model where each device provides one or more dynamically loaded services for input, display, or computation. Using a peer-to-peer model for communication, it leverages IP multicast to replicate the shared state among the peers. Input is handled through a shared event channel that lets input and output devices be fully decoupled. It also provides a data-driven scene graph to delegate rendering to peers, thus creating a robust, fault-tolerant, decentralized system. In this paper, we describe Munin's general design and architecture, provide several examples of how we are using the framework for ubiquitous analytics and visualization, and present a case study on building a Munin assembly for multidimensional visualization. We also present performance results and anecdotal user feedback for the framework that suggests that combining a service-oriented, data-driven model with middleware support for data sharing and event handling eases the design and execution of high performance distributed visualizations
Beschreibung:Date Completed 02.12.2015
Date Revised 11.09.2015
published: Print
Citation Status PubMed-not-MEDLINE
ISSN:1941-0506
DOI:10.1109/TVCG.2014.2337337