Presentation by Alain Tamayo during the Sensor Web Ontology and Semantics paper session of the Sensor Web Enablement workshop (held during the 2011 Cybera Summit).

1. Analysing
Performance
of
XML
Data
Binding
Solutions
for
SOS
Applications
Alain
Tamayo,
Carlos
Granell,
Joaquín
Huerta
Geospatial
Technologies
Research
Group,
Universitat
Jaume
I,
Spain
SWE
2011,
Oct
6-­‐7,
Banff,
Alberta,
Canada

2. 1
.
Motivation
SOS-­‐based
applications
are
commonplace
in
server,
web
and
desktop
environments.
It’s
just
a
matter
of
time
they
become
commonplace
in
mobile
devices
Analysing
Performance
of
XML
Data
Binding
Solutions
for
SOS
Applications
2

3. 2
.
Motivation
SOS
protocols
are
based
in
large
schemas
that
describes
the
structure
of
exchanged
messages
in
XML
format
(+700
types,
+80
schema
files)
• Low-­‐Level
APIs:
• Tree
APIs:
DOM
• Streaming
APIs:
SAX,
StaX,
…
• XML
Data
Binding:
XMLBeans,
JAXB,
XBinder,
…
Using
low-­‐level
APIs
in
the
presence
of
large
schemas
is
time-­‐consuming
and
error-­‐prone.
Using
XML
data
binding
is
advised,
but
frequently
generated
code
needs
more
computational
resources.
Analysing
Performance
of
XML
Data
Binding
Solutions
for
SOS
Applications
3

4. 3
.
Objectives
• To
analyse
to
what
extent
the
use
of
XML
data
binding
solutions
is
a
problem
in
SOS
applications
running
in
different
platforms
(Windows
7
and
Android):
• Execution
speed
(without
including
storage
or
network
transfer
times).
• Memory
consumption
• Size
of
generated
code
Analysing
Performance
of
XML
Data
Binding
Solutions
for
SOS
Applications
4

5. 4
.
Experimental
Setup
• 4
datasets
of
real
SOS
data:
• CAPS
(capabilities
files)
• SD
(Sensor
description
files)
• OBS
(Observation
files)
• MEA
(Measurement
files)
• 4
XML
data
binding
tools:
• XMLBeans
(PC)
• JAXB
(PC)
• XBinder
(PC
and
Mobile)
• DBMG
(PC
and
Mobile)
• 2
Hardware
platforms:
• HTC
Desire
Android
Phone
(1
GHz
CPU,
576
RAM)
• Windows
7
PC
(Intel
Quad
Core
i7
2.8
GHz
CPU,
8GB
RAM)
Analysing
Performance
of
XML
Data
Binding
Solutions
for
SOS
Applications
5

6. 5
–
Execution
Speed
(CAPS
Dataset)
Mobile
Scenario
PC
Scenario
The
execution
times
for
the
mobile
phone
were
about
60
times
slower
than
for
the
personal
computer.
XML
processing
code
does
not
seem
to
be
a
bottleneck
for
PCs.
High
processing
times
for
mobiles
raises
the
question
if
the
current
SOS
protocol
is
appropriate
for
being
implemented
in
these
devices.
XML
is
a
verbose
format.
Analysing
Performance
of
XML
Data
Binding
Solutions
for
SOS
Applications
6

7. 6
–
Execution
Speed
(SD
Dataset)
• SD
dataset:
• SensorML
files
used
to
be
small
(<20KB).
As
a
consequence,
the
execution
times
were
not
high.
• OBS
and
MEA
datasets:
• Observation
files
contains
about
7
times
more
observation
values
than
measurement
files
of
the
same
size.
As
a
consequence,
we
recommend
to
use
the
former
in
mobile
device
SOS
clients.
• Observation
files
represent
observation
values
inside
a
xsd:anyType
element
that
is
not
mapped
successfully
by
some
XML
data
binding
tools.
Additionally,
as
the
“block”
of
observation
values
is
represented
as
a
String
the
application
code
must
parse
this
information
again.
Analysing
Performance
of
XML
Data
Binding
Solutions
for
SOS
Applications
7

8. 7
–
Execution
Speed
(Parsers
–
CAPS
Dataset)
PC
Scenario
Small
files
(<100KB)
Large
files
(>100KB)
Analysing
Performance
of
XML
Data
Binding
Solutions
for
SOS
Applications
8

9. 8
–
Execution
Speed
(Parsers
–
CAPS
Dataset)
Mobile
Scenario
Writing
XML
processing
code
using
a
manual
approach
do
not
necessarily
produce
a
code
that
is
much
faster
than
code
generated
by
some
tools.
Analysing
Performance
of
XML
Data
Binding
Solutions
for
SOS
Applications
9

10. 9
–
Memory
Consumption
(CAPS
dataset)
Small
files
(<100KB)
Large
files
(>100KB)
JAXB
and
XMLBeans
show
higher
memory
consumption,
but
it
does
not
seem
to
represent
a
problem
for
a
desktop
or
server
application.
Analysing
Performance
of
XML
Data
Binding
Solutions
for
SOS
Applications
10

11. 10
–
Size
of
Generated
Code
Code
generated
based
on
large
schemas
usually
has
a
large
size.
Customised
code
fits
better
the
limitations
of
mobile
devices.
Customised
code
does
not
necessarily
has
to
be
written
manually.
Analysing
Performance
of
XML
Data
Binding
Solutions
for
SOS
Applications
11

12. 11
-­‐
Conclusions
We
have
presented
a
study
to
measure
the
influence
of
XML
processing
code
in
the
performance
of
desktop
and
mobile
SOS
applications.
The
results
have
shown
that
XML
processing
does
not
seem
to
be
a
bottleneck
in
PC
applications.
On
the
other
hand,
the
opposite
happens
in
mobile
devices
where
the
time
needed
to
process
large
XML
files
is
very
high
due
to
their
associated
resource
constraints.
Analysing
Performance
of
XML
Data
Binding
Solutions
for
SOS
Applications
12

13. ¿?
Thank
you
for
your
attention