Copyright © 2011 Open Geospatial Consortium
9 Recipients of this document are requested to submit, with their comments, notification of
any relevant patent claims or other intellectual property rights of which they may be aware that might be infringed by any implementation of the standard set forth in this
document, and to provide supporting documentation.
1.2 Document contributor contact points
All questions regarding this document should be directed to the editors:
Name Organization
J. Jansou AtoS
T. Dacla Atmosphere gbmh
We also want to thank the following contributors to this benchmarking campaign, or report writing:
Name Organization
J. Arquey AtoS
M. Aguidi AtoS
R. Jarzmik AtoS
S Vingataramin Atmosphere gbmh
1.3 Revision history
Date Release
Editor Primary clauses
modified Description
2011-06-24 V0R1 J. Jansou
First draft 2011-08-26 V0R2
J. Jansou Second draft
2011-09-30 V1R0 J. Jansou
First release
1.4 Guidelines for the reader
Chapter §2 presents the reference material used to write this report Chapter §3 lists frequently used terms and definitions
Chapter §4 gives conventions used along this document, in 4.1 you will find abbreviated terms
Copyright © 2011 Open Geospatial Consortium
10 Chapter §5 introduces the platform used for the benchmarking, as well as the
various candidates under test with their possible configurations Chapter §6 enumerates the AIXM files used as input data for the benchmark
Chapter §7 treats results obtain and proposes explanation Chapter §8 shows how whose results could be used for actual applications
Chapter §9 opens ways to further work on the AIXM compression topic Chapter §10 finally concludes, summing up achievements and facts from this
study
1.5 Overview results of the study
The following lines resume the work done in the study and browse conclusions for the hurried reader.
3 families of AIXM files were identified and populated with AIXM files AIXM selected files were analyzed to show general aspects of AIXM and
specificities due to each feature available. Measurements were made on compaction performance, CPU consumption and
memory footprint for both setup, encoding and decoding phases for various algorithms deflate alone, FI, FI with deflate, CWXML, deflate with dictionary,
deflate with several levels of compression, EXI without schema knowledge neither deflate, EXI without schema knowledge but with deflate, EXI with
schema knowledge but without deflate, EXI with both schema knowledge and deflate using the exi-ttfms platform, modified for the purpose.
Main conclusions regarding results obtain are: EXI is very efficient to compress small AIXM files without too much coordinates
inside. Exificient with both AIXM schema knowledge and deflate post- compression allow to produce compressed D-NOTAMs around 700 bytes only
13 of the original file size. The dark spot of using exificient for such data is the huge memory footprint necessary ~100MB and the time needed to perform
deflate post compression. This is not much a problem for a 2011 server, but will certainly raise some issue for an EFB.
For compaction of bigger AIXM files 100KB, the difference of performance between EXI and other compression algorithms decrease, and thus as you can
reach a comparable level of compaction with Fast Info Set with a CPU and memory consumption so much lower, we strongly suggest to stick on Fast Info
Set with deflate post-compression.
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11
1.6 Future work
