{"title":"一种在ESB中减少QoS监视开销的方法","authors":"Shima Baghermousavi, H. Rashidi, H. Haghighi","doi":"10.1109/ECDC.2014.6836748","DOIUrl":null,"url":null,"abstract":"Since the Small and Medium Business (SMB) markets is growing, service-oriented architecture will play a crucial role in the SMB IT market. In this market the ability for better integration, increased flexibility, and cost reduction in development by reuse of existing services must be considered. Because of the service oriented architecture's dynamic nature, increment the number of clients and high volume transferred information between service provider and service consumer in business processes, Quality of Service (QoS) monitoring is needed. Services can be monitored at run-time to check whether they comply with their contracts or not. Monitoring can be done in different places such as provider side, client side and third part like Enterprise Service Bus (ESB). In the approach presented in this paper, the monitoring module was placed in ESB. Despite the monitoring place, QoS monitoring module is invoked at every time of service calling. Because of other methods running, overhead is inevitable. Specially monitoring overhead effects on the service quality parameters such as response time. The main objective of our approach is to reduce the QoS monitoring overhead using Time Series Forecasting in Neural Network. At the end, the performance of approach was evaluated through simulation on a case study in Tehran Metro. The experimental results show that this approach had low overhead in monitoring module.","PeriodicalId":432650,"journal":{"name":"8th International Conference on e-Commerce in Developing Countries: With Focus on e-Trust","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"An approach to reduce QoS monitoring overhead in ESB\",\"authors\":\"Shima Baghermousavi, H. Rashidi, H. Haghighi\",\"doi\":\"10.1109/ECDC.2014.6836748\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Since the Small and Medium Business (SMB) markets is growing, service-oriented architecture will play a crucial role in the SMB IT market. In this market the ability for better integration, increased flexibility, and cost reduction in development by reuse of existing services must be considered. Because of the service oriented architecture's dynamic nature, increment the number of clients and high volume transferred information between service provider and service consumer in business processes, Quality of Service (QoS) monitoring is needed. Services can be monitored at run-time to check whether they comply with their contracts or not. Monitoring can be done in different places such as provider side, client side and third part like Enterprise Service Bus (ESB). In the approach presented in this paper, the monitoring module was placed in ESB. Despite the monitoring place, QoS monitoring module is invoked at every time of service calling. Because of other methods running, overhead is inevitable. Specially monitoring overhead effects on the service quality parameters such as response time. The main objective of our approach is to reduce the QoS monitoring overhead using Time Series Forecasting in Neural Network. At the end, the performance of approach was evaluated through simulation on a case study in Tehran Metro. The experimental results show that this approach had low overhead in monitoring module.\",\"PeriodicalId\":432650,\"journal\":{\"name\":\"8th International Conference on e-Commerce in Developing Countries: With Focus on e-Trust\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-04-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"8th International Conference on e-Commerce in Developing Countries: With Focus on e-Trust\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ECDC.2014.6836748\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"8th International Conference on e-Commerce in Developing Countries: With Focus on e-Trust","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECDC.2014.6836748","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
摘要
由于中小型企业(SMB)市场正在增长,面向服务的体系结构将在中小型IT市场中发挥关键作用。在这个市场中,必须考虑通过重用现有服务来实现更好的集成、增加的灵活性和降低开发成本的能力。由于面向服务的体系结构具有动态性,增加了业务流程中服务提供者和服务使用者之间的客户机数量和大量传输信息,因此需要进行服务质量(QoS)监控。可以在运行时监视服务,以检查它们是否遵守它们的契约。监控可以在不同的地方进行,比如提供者端、客户端和企业服务总线(Enterprise Service Bus, ESB)等第三方。在本文提出的方法中,监视模块被放置在ESB中。尽管处于监视位置,但每次调用服务时都会调用QoS监视模块。由于运行其他方法,开销是不可避免的。特别是监视开销对服务质量参数(如响应时间)的影响。该方法的主要目的是利用神经网络中的时间序列预测来减少QoS监控的开销。最后,以德黑兰地铁为例,对该方法的性能进行了仿真分析。实验结果表明,该方法具有较低的监控模块开销。
An approach to reduce QoS monitoring overhead in ESB
Since the Small and Medium Business (SMB) markets is growing, service-oriented architecture will play a crucial role in the SMB IT market. In this market the ability for better integration, increased flexibility, and cost reduction in development by reuse of existing services must be considered. Because of the service oriented architecture's dynamic nature, increment the number of clients and high volume transferred information between service provider and service consumer in business processes, Quality of Service (QoS) monitoring is needed. Services can be monitored at run-time to check whether they comply with their contracts or not. Monitoring can be done in different places such as provider side, client side and third part like Enterprise Service Bus (ESB). In the approach presented in this paper, the monitoring module was placed in ESB. Despite the monitoring place, QoS monitoring module is invoked at every time of service calling. Because of other methods running, overhead is inevitable. Specially monitoring overhead effects on the service quality parameters such as response time. The main objective of our approach is to reduce the QoS monitoring overhead using Time Series Forecasting in Neural Network. At the end, the performance of approach was evaluated through simulation on a case study in Tehran Metro. The experimental results show that this approach had low overhead in monitoring module.