Masó J., Díaz, P., Pons, X. (2011). Performance of standardized web map servers for remote sensing Imagery, en: Proceedings of Data Flow: From Space to Earth. Applications and interoperability Conference, March 2011, Venice. Corila -Consorzio per la Gestione del Centro di Coordinamento delle Attività di Ricerca Inerenti il Sistema Lagunare di Venezia, pp.64-64. ISBN:9788889405154.

1. Data Flow: From Space to Earth. Applications and interoperability congress
PERFORMANCE OF STANDARDIZED
WEB MAP SERVERS
FOR REMOTE SENSING IMAGERYFOR REMOTE SENSING IMAGERY
Joan Masó, Paula Díaz, Xavier Pons.
Data Flow: From Space to Earth. Applications and interoperability congress
March 2011
CREAF & Universitat Autònoma de Barcelona

2. Index
1. INTRODUCTION
MATERIALS AND METHODOLOGY2. MATERIALS AND METHODOLOGY
3. EVALUATION OF WMS CONCURRENT REQUESTS
TO A SINGLE SERVER
4. EVALUATION OF A CLUSTER OF SERVERS4. EVALUATION OF A CLUSTER OF SERVERS
5. TILING THE REQUEST AND THE RESPONSE
Data Flow: From Space to Earth. Applications and interoperability congress March 2011
6. CONCLUSIONS

3. 1. INTRODUCTION
Amount of data (satellite)
Web portals and
clearinghouses
Standards available
Implementation of
standardized protocols
Space technologies
Hazard modeling and analysis
Remote sensing imagery Space technologies
improvements
Integration in bigger System
Data Flow: From Space to Earth. Applications and interoperability congress March 2011
Communication satellites
g gg y
of Systems, like GEOSS

4. 2. MATERIALS AND METHODOLOGY
ClientsServers ClientsStandardsData
Web Map Service
(WMS) ( S)
Web Map Service
Cache (WMS‐C)
Tile Map Service
(TMS)
This communication evaluates the efficiency and possibilities of several
maps servers
GEO‐PICTURES is an EU FP7 SPACE project with the aim of integrating
lli i i h i i d d i l f
Data Flow: From Space to Earth. Applications and interoperability congress March 2011
satellite imagery with in‐situ sensors and geo‐tagged images as a tool for
decision making in emergency crisis situations

5. 2. MATERIALS AND METHODOLOGY
22 satellite images of GeoEye‐1 (Orthorectified
GeoTIFF; provided by Google)
(http://www google com/relief/haitiearthquake/geoeye html)(http://www.google.com/relief/haitiearthquake/geoeye.html)
Covering Port‐au‐Prince
and surroundings
16‐01‐2010, 3 days
after the Earthquake
Each image has
196 373 kb 4.21 Gb
Data Flow: From Space to Earth. Applications and interoperability congress March 2011
40 994x57 392 pixels
pdiaz4

6. Diapositiva 5
pdiaz4 Al Web de descàrrega posa:
By downloading these files, you agree to use the imagery solely for non-commercial use related to emergency relief, and to provide a
proper and distinct photo credit to “GeoEye Satellite Image.”
Això significa que hem de posar el logo de GeoEye a la presentació?
pdiaz; 13/10/2010

7. Traditional WMS server‐client interaction
WMS
Server
request
GetMap
URL
Server
responseresponse
All studied protocols request maps by creating an URL with specific syntax
URL requests were randomly generated
Data Flow: From Space to Earth. Applications and interoperability congress March 2011
The time response is stored in an archive and analyzed

8. 3 . EV A LU A TIO N O F W M S C O N C U R R EN T R EQ U ESTS TO A
SINGLE SERVER
More than one hundred different requests were
done (without optimizing speed configurations).( p g p g )
The influence of the pixel size and the image size in
the time response were evaluatedthe time response were evaluated
The requests were made from up to 6 concurrent
clientsclients.
The time response for the requests are exposed in
h
Data Flow: From Space to Earth. Applications and interoperability congress March 2011
graphs.

9. 3. EVALUATION OF WMS CONCURRENT REQUESTS TO A
SINGLE SERVER
EvaluationofthetimerequestforPixelSize(multipleclients-
MiraMonServer)
7
8
9
10
con
5Clients
4Clients
3Clients
2Clients
EvaluationofthetimerequestforPixelSize(multipleclients-
MapServer)
6
7
8
9
10
econ
5Clients
4Clients
3Clients
2Clients
0
1
2
3
4
5
6
0.001 0.010 0.100 1.000 10.000
PixelSize(secondsofarc)
Time(sec
0
1
2
3
4
5
6
0.001 0.010 0.100 1.000 10.000
PixelSize(secondsofarc)
Time(se
PixelSize(secondsofarc) PixelSize(secondsofarc)
EvaluationofthetimerequestforPixelSize(multipleclients-
GeoServer)
9
10
5Clients
4Clients
3Clients
0
1
2
3
4
5
6
7
8
Time(secon
3Clients
2Clients
Data Flow: From Space to Earth. Applications and interoperability congress March 2011
0
0.001 0.010 0.100 1.000 10.000
PixelSize(secondsofarc)

10. 4. EVALUATION OF A CLUSTER OF SERVERS
To overcome the performance degradation in
concurrent requests a possible solution is to set up aconcurrent requests a possible solution is to set up a
cluster of servers
h l f i l i lThe cluster of servers act as a virtual single server
6 computers are able to respond at same time to different
clients as if they were like a faster single serverclients as if they were like a faster single server
We carried out some tests comparing a WMS single
Data Flow: From Space to Earth. Applications and interoperability congress March 2011
server and a WMS in a computer cluster server

11. 4. EVALUATION OF A CLUSTER OF SERVERS
EvaluationoftheresponsetimeforPixelSize(ClientstoMiraMonSingleServer)
1000
120.0
140.0
160.0
180.0
liseco
17clients
14Clients
11Clients
8Clients
4Cli t
0.0
20.0
40.0
60.0
80.0
100.0
Time(mill
4Clients
1Client
EvaluationoftheresponsetimeforPixelSize(ClientstoMiraMonServerCluster)
160.0
180.0
17clients
14Clients
11Clients
0.0000 2.0000 4.0000 6.0000 8.0000 10.0000 12.0000 14.0000 16.0000
PixelSize(secondsofarc)
40.0
60.0
80.0
100.0
120.0
140.0
Time(milliseco
11Clients
8Clients
4Clients
1Client
Data Flow: From Space to Earth. Applications and interoperability congress March 2011
0.0
20.0
0.0000 2.0000 4.0000 6.0000 8.0000 10.0000 12.0000 14.0000 16.0000
PixelSize(secondsofarc)

12. 5. TILING THE REQUEST AND THE RESPONSE
Some WMS clients are able to tile the space in a regular matrix of small
pieces.
They need several tiles to cover the whole viewportThey need several tiles to cover the whole viewport
They can recycle some tiles when the user moves the view laterally
Also can take advantage of the cache mechanisms
If the caching mechanism cannot help the response time can increase even
if each tile is smaller that the whole view
Tiled clients (tiles of 256x256 pixels) were simulated in three ( p )
configurations.
Speed metrics in the 3 different services were done for the three servers
mentioned
Data Flow: From Space to Earth. Applications and interoperability congress March 2011
mentioned

13. 5. TILING THE REQUEST AND THE RESPONSE
Time response for unlimited concurrent 256x256Time response for complete window request Time response for sequential 256x256 tiled
Time response for up to 4 concurrent 256x256
tiled requests on a pure WMS server
2.5
3
MMServer
GeoServer
MapServer
p p q
on a WMS server
2.5
3 MMServer
GeoServer
MapServer
Time response for sequential 256x256 tiled
requests on a pure WMS server
2.5
3 MMServer
GeoServer
MapServer
tiled requests on a pure WMS server
3
3 MMServer
GeoServer
MapServer
1
1.5
2
Time(seconds)
1
1.5
2
Time(seconds)
1
1.5
2
Time(seconds)
1
2
2
Time(seconds)
0
0.5
0.001 0.010 0.100 1.000 10.000
Pixel Size (seconds of arc)
0
0.5
0.001 0.010 0.100 1.000 10.000
Pixel Size (seconds of arc)
0
0.5
0.001 0.010 0.100 1.000 10.000
Pixel Size (seconds of arc)
0
1
0.001 0.010 0.100 1.000 10.000
Pixel Size (seconds of arc)
Data Flow: From Space to Earth. Applications and interoperability congress March 2011
Concurrent Tiled WMS
Full window WMS Sequential tiled WMS
Semi-concurrent Tiled WMS

14. 6. CONCLUSIONS
The speed tests described are a practical demonstration of the suitability of certain servers
and service configurations in certain domains where reliability of services is imperative
All the analyzed servers have slower performances when the number of simultaneous
clients is increasedclients is increased
To solve this situation a cluster server can be used
Results show that WMS servers perform worst if clients using tile strategies are used over
servers that are not optimized for this situationservers that are not optimized for this situation
Future work will analyze tile cache strategies (TMS and WMTS) and implementations to overcome
concurrent situations that can severely degrade map server performance.
MapServer and GeoServer with common data configuration do not require any data
i b h i f i h h i h i i d ipreparation process but their performance is worst than other services that require indexing
methods like MiraMon Map Server
MapServer (based on C++ code) performs better than GeoServer (based on Java code) under
single client requests but GeoServer is surprisingly faster under concurrent simultaneous
Data Flow: From Space to Earth. Applications and interoperability congress March 2011
single client requests, but GeoServer is surprisingly faster under concurrent simultaneous
requests.

15. Thank you!
Joan Masó Paula Díaz Xavier Pons
Paula diaz@creaf uab es
Data Flow: From Space to Earth. Applications and interoperability congress
March 2011
Paula.diaz@creaf.uab.es