Limitations of Azure in GIS Scalability: A performance and migration study
Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
In this study, the cloud platform Windows Azure has been targeted for test implementations of Geographical Information System (GIS) software in the form of map servers and tile caches. The map servers included were GeoServer, MapNik, MapServer and SharpMap, which together with the tile caches, GeoWebCache, MapCache and TileCache, were installed on Windows Azures three different virtual machine roles (Web, Worker and VM). Furthermore, different techniques for scalingapplications and internal role communication are presented, followed by four sets of performance tests. The performance tests attempt to highlight the differences in request times, how the different role sizes handle the load from the incoming requests, how the different role sizes handle many concurrent TCP-connections and how well the incoming requests are load balanced in between the worker roles. The test implementations showed that all map servers and tile caches were successfully installed in Azure, which leads to the conclusion that Windows Azure is suitable for hosting GIS software with similar installation requirements to the previously mentioned software. Four different approaches (Direct mapping, Public Internal Endpoints, Queue and Worker Role Request Broker) are presented showing how Azure allows different methods in order to scale the internal role communication as well as the external client requests. The performance tests provided somewhat inconclusive test results due to hardware limitations in the test setup. This made it difficult to draw concluding parallels between the final results and the expected values. Minor tendencies in performance gain can be seen when scaling the VM size as well as the number of VMs.
Place, publisher, year, edition, pages
2012. , 76 p.
Windows Azure, GIS, Scalability, Migration
IdentifiersURN: urn:nbn:se:miun:diva-17009OAI: oai:DiVA.org:miun-17009DiVA: diva2:552371
Civilingenjör i datateknik TDTEA 300 hp
Kjellqvist, Martin, Lecturer
Zhang, Tingting, Professor