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SpaceWire Meets Big Data - Realtime Data Mining

Bahls, Thomas and Bihler, Markus and Tarassenko, Sergey (2018) SpaceWire Meets Big Data - Realtime Data Mining. In: Proceedings Proceedings of the 8 th International SpaceWire Conference California, 2018, pp. 139-142. Univeristy of Dundee. International SpaceWire Conference 2018, 14-18 May 2018, Long Beach CA, USA.

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Official URL: http://2018.spacewire-conference.org/downloads/2018SpWProceedings.pdf


Abstract —The whole is more than the sum of its parts. This saying particularly fits in the context of big data and data mining. A single data set is only valid and relevant at exactly one point in time. Dependencies between the individual elements of the data set as well as the behaviour over time can only be investigated if large amounts of data are available. A good example is traffic monitoring based on GPS data, WiFi, and/or cellular triangulation of modern mobile phones (see [1], [2]). Here, the data sets are collected from multiple sources to estimate a precise traffic situation. Data completeness is vital to achieving sufficient reflection of the actual state of a system, since information can be lost through downsampling. This is a difficult requirement to fulfill especially for highly dynamic systems like robots. Data recording over the same communication infrastructure from multiple sources must meet strict real time requirements of the control application. Main control loops at joint level of ≥ 3 kHz and up to 100 kHz at motor control are quite common (e.g. [3]). Due to this, a simple duplication of the cyclic data sets at CPU-level for simultaneously controlling and recording is not possible without decimation of the recording sample rate. Therefore recording has to be performed at a different point of the communication infrastructure. This approach provides a duplication of the data at SpaceWire packet level by using seperate SpaceWire regions for control and recording without violating the real time requirements of the control application.

Item URL in elib:https://elib.dlr.de/120404/
Document Type:Conference or Workshop Item (Poster)
Title:SpaceWire Meets Big Data - Realtime Data Mining
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Bahls, ThomasUNSPECIFIEDhttps://orcid.org/0000-0002-9935-2676UNSPECIFIED
Date:14 May 2018
Journal or Publication Title:Proceedings Proceedings of the 8 th International SpaceWire Conference California, 2018
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In ISI Web of Science:No
Page Range:pp. 139-142
Publisher:Univeristy of Dundee
Keywords:BigData, DataMining
Event Title:International SpaceWire Conference 2018
Event Location:Long Beach CA, USA
Event Type:international Conference
Event Dates:14-18 May 2018
Organizer:Univerity of Dundee, ESA, JPL, Microsemi
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space System Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Space System Technology
DLR - Research theme (Project):R - Medical Assistance Systems [SY]
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics (since 2013) > Mechatronic Systems
Deposited By: Bahls, Thomas
Deposited On:28 Nov 2018 11:08
Last Modified:28 Nov 2018 11:08

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