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Data Flow: From Space to Earth. Applications and interoperability congress
PERFORMANCE OF STANDARDIZED
WEB MAP SERVERS 
FO...
Index
1. INTRODUCTION
MATERIALS AND METHODOLOGY2. MATERIALS AND METHODOLOGY
3. EVALUATION OF WMS CONCURRENT REQUESTS 
TO A...
1. INTRODUCTION
Amount of data (satellite)
Web portals and 
clearinghouses 
Standards available 
Implementation of 
standa...
2. MATERIALS AND METHODOLOGY
ClientsServers ClientsStandardsData
Web Map Service 
(WMS) ( S)
Web Map Service 
Cache (WMS‐C...
2. MATERIALS AND METHODOLOGY
22 satellite images of GeoEye‐1 (Orthorectified 
GeoTIFF; provided by Google)
(http://www goo...
Diapositiva 5
pdiaz4 Al Web de descàrrega posa:
By downloading these files, you agree to use the imagery solely for non-co...
Traditional WMS server‐client interaction
WMS
Server
request
GetMap
URL
Server
responseresponse
All studied protocols requ...
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 reques...
3. EVALUATION OF WMS CONCURRENT REQUESTS TO A 
SINGLE SERVER
EvaluationofthetimerequestforPixelSize(multipleclients-
MiraM...
4. EVALUATION OF A CLUSTER OF SERVERS
To overcome the performance degradation in 
concurrent requests a possible solution ...
4. EVALUATION OF A CLUSTER OF SERVERS
EvaluationoftheresponsetimeforPixelSize(ClientstoMiraMonSingleServer)
1000
120.0
140...
5. TILING THE REQUEST AND THE RESPONSE
Some WMS clients are able to tile the space in a regular matrix of small 
pieces. 
...
5. TILING THE REQUEST AND THE RESPONSE
Time response for unlimited concurrent 256x256Time response for complete window req...
6. CONCLUSIONS
The speed tests described are a practical demonstration of the suitability of certain servers
and service c...
Thank you!
Joan Masó  Paula Díaz Xavier Pons
Paula diaz@creaf uab es
Data Flow: From Space to Earth. Applications and inte...
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Performance of standardized web map servers for remote sensing Imagery

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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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Transcript of "Performance of standardized web map servers for remote sensing Imagery"

  1. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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
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