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Data Flow: From Space to Earth. Applications and interoperability congress
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Data Flow: From Space to Earth. Applications and interoperability congress PERFORMANCE OF STANDARDIZED WEB MAP SERVERS FOR REMOTE SENSING IMAGERY Joan Masó, Paula Díaz, Xavier Pons. CREAF & Universitat Autònoma de Barcelona. Index. INTRODUCTION MATERIALS AND METHODOLOGY

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Index

Data Flow: From Space to Earth. Applications and interoperability congressPERFORMANCE OF STANDARDIZED WEB MAP SERVERS FOR REMOTE SENSING IMAGERYJoan Masó, Paula Díaz, Xavier Pons.CREAF & Universitat Autònoma de Barcelona


Index

Index

  • INTRODUCTION

  • MATERIALS AND METHODOLOGY

  • EVALUATION OF WMS CONCURRENT REQUESTS TO A SINGLE SERVER

  • EVALUATION OF A CLUSTER OF SERVERS

  • TILING THE REQUEST AND THE RESPONSE

  • CONCLUSIONS


1 introduction

1. INTRODUCTION

  • Web portals and clearinghouses

  • Implementation of standardized protocols

  • Hazard modeling and analysis

  • Remote sensing imagery improvements

  • Integration in bigger System of Systems, like GEOSS

  • Amount of data (satellite)

  • Standards available

  • Space technologies

  • Communication satellites


2 materials and methodology

2. MATERIALS AND METHODOLOGY

Clients

Data

Servers

Standards

Web Map Service (WMS)

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 satellite imagery with in-situ sensors and geo-tagged images as a tool for decision making in emergency crisis situations


2 materials and methodology1

2. MATERIALS AND METHODOLOGY

  • 22 satellite images of GeoEye-1 (Orthorectified GeoTIFF; provided by Google)

    • (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

  • 40 994x57 392 pixels


Traditional wms server client interaction

request

GetMap

URL

WMS

Server

response

Traditional WMS server-client interaction

  • All studied protocols request maps by creating an URL with specific syntax

  • URL requests were randomly generated

  • The time response is stored in an archive and analyzed


3 evaluation of wms concurrent requests to a single server

3. EVALUATION OF WMS CONCURRENT REQUESTS TO A SINGLE SERVER

  • More than one hundred different requests were done (without optimizing speed configurations).

  • The influence of the pixel size and the image size in the time response were evaluated

  • The requests were made from up to 6 concurrentclients.

  • The time response for the requests are exposed in graphs.


3 evaluation of wms concurrent requests to a single server1

3. EVALUATION OF WMS CONCURRENT REQUESTS TO A SINGLE SERVER


4 evaluation of a cluster of servers

4. EVALUATION OF A CLUSTER OF SERVERS

  • To overcome the performance degradation in concurrent requests a possible solution is to set up a cluster of servers

  • The 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 server

  • We carried out some tests comparing a WMS single server and a WMS in a computer cluster server


4 evaluation of a cluster of servers1

4. EVALUATION OF A CLUSTER OF SERVERS


5 tiling the request and the response

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 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 configurations.

  • Speed metrics in the 3 different services were done for the three servers mentioned


5 tiling the request and the response1

Full window WMS

Sequential tiled WMS

Concurrent Tiled WMS

Semi-concurrent Tiled WMS

5. TILING THE REQUEST AND THE RESPONSE


6 conclusions

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 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 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 preparation 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 requests.


Thank you

Thank you!

Joan Masó Paula DíazXavier Pons

Paula.diaz@creaf.uab.es


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