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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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

[email protected]


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