Daniel Ritter, Norman May, Kai Sachs, S. Rinderle-Ma
{"title":"Benchmarking integration pattern implementations","authors":"Daniel Ritter, Norman May, Kai Sachs, S. Rinderle-Ma","doi":"10.1145/2933267.2933269","DOIUrl":null,"url":null,"abstract":"The integration of a growing number of distributed, heterogeneous applications is one of the main challenges of enterprise data management. Through the advent of cloud and mobile application integration, higher volumes of messages have to be processed, compared to common enterprise computing scenarios, while guaranteeing high throughput. However, no previous study has analyzed the impact on message throughput for Enterprise Integration Patterns (EIPs) (e. g., channel creation, routing and transformation). Acknowledging this void, we propose EIPBench, a comprehensive micro-benchmark design for evaluating the message throughput of frequently implemented EIPs and message delivery semantics in productive cloud scenarios. For that, these scenarios are collected and described in a process-driven, TPC-C-like taxonomy, from which the most relevant patterns, message formats, and scale factors are derived as foundation for the benchmark. To prove its applicability, we describe an EIPBench reference implementation and discuss the results of its application to an open source integration system that implements the selected patterns.","PeriodicalId":277061,"journal":{"name":"Proceedings of the 10th ACM International Conference on Distributed and Event-based Systems","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 10th ACM International Conference on Distributed and Event-based Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2933267.2933269","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15
Abstract
The integration of a growing number of distributed, heterogeneous applications is one of the main challenges of enterprise data management. Through the advent of cloud and mobile application integration, higher volumes of messages have to be processed, compared to common enterprise computing scenarios, while guaranteeing high throughput. However, no previous study has analyzed the impact on message throughput for Enterprise Integration Patterns (EIPs) (e. g., channel creation, routing and transformation). Acknowledging this void, we propose EIPBench, a comprehensive micro-benchmark design for evaluating the message throughput of frequently implemented EIPs and message delivery semantics in productive cloud scenarios. For that, these scenarios are collected and described in a process-driven, TPC-C-like taxonomy, from which the most relevant patterns, message formats, and scale factors are derived as foundation for the benchmark. To prove its applicability, we describe an EIPBench reference implementation and discuss the results of its application to an open source integration system that implements the selected patterns.