Binbin Xiang, Xu Li, Min Zhang, Lifei Lu, Fa Li, Binru Zhao, Zhipeng Gui
{"title":"An extensible simulation framework for diagnosing the execution of the distributed geospatial web services","authors":"Binbin Xiang, Xu Li, Min Zhang, Lifei Lu, Fa Li, Binru Zhao, Zhipeng Gui","doi":"10.1109/GEOINFORMATICS.2015.7378672","DOIUrl":null,"url":null,"abstract":"Distributed geospatial web services have been widely utilized in scientific researches, public web applications and emergency responses. However, due to the high cost and limitation of reality for these potential applications, it is necessary to diagnose the execution of the distributed geospatial web services before applying them in real-world. In this article, we introduce an extensible framework that provides the users with the capacity to simulate the execution of distributed geospatial web services. Specifically, it can simulate the task arrival, computing resource usage, execution status, as well as execution results of geospatial web services. It also provides the statistics and evaluation function of the results of execution. The proposed simulation framework can be divided into three modules, i.e., a web Graphic User Interface (GUI), a simulator, and a database. The GUI is in charge of the interaction functions for specifying simulation parameters and visualizing the execution status dynamically. The simulator module provides a flexible mechanism to integrate a variety of simulation features by using a simulator coordinator. The database is for storing the real-time status and historical simulation data. The experiment demonstrates that the proposed framework can 1) facilitate the evaluation of the performance and reliability of the web service in advance, 2) help users find the critical path and the bottleneck of the processing workflow, and 3) provide useful information for further improvement in the performance and for dealing with the unexpected events.","PeriodicalId":371399,"journal":{"name":"2015 23rd International Conference on Geoinformatics","volume":"47 4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 23rd International Conference on Geoinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GEOINFORMATICS.2015.7378672","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Distributed geospatial web services have been widely utilized in scientific researches, public web applications and emergency responses. However, due to the high cost and limitation of reality for these potential applications, it is necessary to diagnose the execution of the distributed geospatial web services before applying them in real-world. In this article, we introduce an extensible framework that provides the users with the capacity to simulate the execution of distributed geospatial web services. Specifically, it can simulate the task arrival, computing resource usage, execution status, as well as execution results of geospatial web services. It also provides the statistics and evaluation function of the results of execution. The proposed simulation framework can be divided into three modules, i.e., a web Graphic User Interface (GUI), a simulator, and a database. The GUI is in charge of the interaction functions for specifying simulation parameters and visualizing the execution status dynamically. The simulator module provides a flexible mechanism to integrate a variety of simulation features by using a simulator coordinator. The database is for storing the real-time status and historical simulation data. The experiment demonstrates that the proposed framework can 1) facilitate the evaluation of the performance and reliability of the web service in advance, 2) help users find the critical path and the bottleneck of the processing workflow, and 3) provide useful information for further improvement in the performance and for dealing with the unexpected events.