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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.
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Data Flow: From Space to Earth. Applications and interoperability congress
PERFORMANCE OF STANDARDIZEDWEB MAP SERVERS
FOR REMOTE SENSING IMAGERYFOR REMOTE SENSING IMAGERYJoan Masó, Paula Díaz, Xavier Pons.
Data Flow: From Space to Earth. Applications and interoperability congressMarch 2011
CREAF & Universitat Autònoma de Barcelona
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
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 technologiesimprovements
Integration in bigger System
Data Flow: From Space to Earth. Applications and interoperability congress March 2011
Communication satellitesg gg y
of Systems, like GEOSS
2. MATERIALS AND METHODOLOGYClientsServers 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
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
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
Traditional WMS server‐client interaction
WMSServer
requestGetMap
URLServer
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
3 . EV A LU A T IO N O F W M S CO N CU RR EN T R EQ U EST S 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 concurrentclientsclients.
The time response for the requests are exposed in h
Data Flow: From Space to Earth. Applications and interoperability congress March 2011
graphs.
3. EVALUATION OF WMS CONCURRENT REQUESTS TO A SINGLE SERVER
Evaluation of the time request for Pixel Size (multiple clients - MiraMon Server)
789
10
con
5 Clients4 Clients3 Clients2 Clients
Evaluation of the time request for Pixel Size (multiple clients - MapServer)
6789
10
econ
5 Clients4 Clients3 Clients2 Clients
0123456
0.001 0.010 0.100 1.000 10.000
PixelSize(secondsofarc)
Tim
e (s
ec
0123456
0.001 0.010 0.100 1.000 10.000
PixelSize(secondsofarc)
Tim
e (s
e
Pixel Size (seconds of arc) Pixel Size (seconds of arc)
Evaluation of the time request for Pixel Size (multiple clients -GeoServer)
910
5 Clients4 Clients3Clients
012345678
Tim
e (s
econ
3 Clients2 Clients
Data Flow: From Space to Earth. Applications and interoperability congress March 2011
00.001 0.010 0.100 1.000 10.000
Pixel Size (seconds of arc)
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 server6 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
4. EVALUATION OF A CLUSTER OF SERVERSEvaluation of the response time for Pixel Size (Clients to MiraMon Single Server)
1000
120.0
140.0
160.0
180.0
lisec
o
17 clients
14 Clients
11 Clients
8 Clients
4Cli t
0.0
20.0
40.0
60.0
80.0
100.0
Tim
e (m
ill 4 Clients
1 Client
Evaluation of the response time for Pixel Size (Clients to MiraMon Server Cluster)
160.0
180.017 clients
14 Clients
11Clients
0.0000 2.0000 4.0000 6.0000 8.0000 10.0000 12.0000 14.0000 16.0000
Pixel Size (seconds of arc)
40.0
60.0
80.0
100.0
120.0
140.0
Tim
e (m
illis
eco
11 Clients
8 Clients
4 Clients
1 Client
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
Pixel Size (seconds of arc)
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 viewportThey can recycle some tiles when the user moves the view laterallyAlso can take advantage of the cache mechanismsIf 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
5. TILING THE REQUEST AND THE RESPONSETime response for unlimited concurrent 256x256 Time response for complete window request Time response for sequential 256x256 tiledTime response for up to 4 concurrent 256x256
tiled requests on a pure WMS server
2.5
3 MMServer
GeoServer
MapServer
p p qon 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
Tim
e (s
econ
ds)
1
1.5
2
Tim
e (s
econ
ds)
1
1.5
2
Tim
e (s
econ
ds)
1
2
2
Tim
e (s
econ
ds)
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 2011Concurrent Tiled WMS
Full window WMS Sequential tiled WMSSemi-concurrent Tiled WMS
6. CONCLUSIONSThe speed tests described are a practical demonstration of the suitability of certain serversand 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.
Thank you!
Joan Masó Paula Díaz Xavier Pons
Paula diaz@creaf uab es
Data Flow: From Space to Earth. Applications and interoperability congressMarch 2011
Paula.diaz@creaf.uab.es
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