Evaluating Data Marshalling Approaches for Embedded Real-Time Systems on the Example of Autonomous Scaled Cars

dc.contributor.authorBorosean, Victor
dc.contributor.authorEidukas, Saulius
dc.contributor.authorDang, Andy
dc.contributor.departmentGöteborgs universitet/Institutionen för data- och informationsteknikswe
dc.contributor.departmentUniversity of Gothenburg/Department of Computer Science and Engineeringeng
dc.date.accessioned2015-07-20T13:56:26Z
dc.date.available2015-07-20T13:56:26Z
dc.date.issued2015-07-20
dc.description.abstractThis paper conducted a comparison between four di erent data mar- shaling approaches (Netstrings, LCM, Protobuf, and ROS) that were im- plemented in the OpenDaVINCI environment and evaluated from di erent perspectives. In this study we compared the data marshaling approaches on the low-level, focusing on the overhead in terms of control data and en- coding/decoding for data structures that are common to OpenDaVINCI. Further, the data marshaling approaches were compared in terms of de- scriptive expressiveness with the current interface description language ODVD.sv
dc.identifier.urihttp://hdl.handle.net/2077/39983
dc.language.isoengsv
dc.setspec.uppsokTechnology
dc.titleEvaluating Data Marshalling Approaches for Embedded Real-Time Systems on the Example of Autonomous Scaled Carssv
dc.typetext
dc.type.degreeStudent essay
dc.type.uppsokM2

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
gupea_2077_39983_1.pdf
Size:
577.17 KB
Format:
Adobe Portable Document Format
Description:
Bachelor Thesis

License bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
876 B
Format:
Item-specific license agreed upon to submission
Description: