D. Schäfer, A. Weiss, M. Tariq, V. Andrikopoulos, Santiago Gómez Sáez, Lukas Krawczyk, K. Rothermel
{"title":"一个高可用性工作流执行系统","authors":"D. Schäfer, A. Weiss, M. Tariq, V. Andrikopoulos, Santiago Gómez Sáez, Lukas Krawczyk, K. Rothermel","doi":"10.1109/SCC.2016.24","DOIUrl":null,"url":null,"abstract":"The workflow technology is the de facto standard for managing business processes. Today, workflows are even used for automating interactions and collaborations between business partners, e.g., for enabling just-in-time production. Every workflow that is part of such a collaboration needs to be highly available. Otherwise, the business operations, e.g., the production, might be hindered or even stopped. Since today's business partners are scattered across the globe, the workflows are executed in a highly distributed and heterogeneous environment. Those environments are, however, failure-prone and, thus, providing availability is not trivial. In this work, we improve availability by replicating workflow executions, while ensuring that the outcome is the same as in a non-replicated execution. For making workflow replication easily usable with current workflow technology, we derive the requirements for modeling a workflow replication system. Then, we propose the HAWKS system, which adheres to the previously specified requirements and is compatible with current technology. We implement a proof-of-concept in the open-source workflow execution engine Apache ODE for demonstrating this compatibility. Finally, we extensively evaluate the impact of using HAWKS in terms of performance and availability in the presence of failures.","PeriodicalId":115693,"journal":{"name":"2016 IEEE International Conference on Services Computing (SCC)","volume":"66 3","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"HAWKS: A System for Highly Available Executions of Workflows\",\"authors\":\"D. Schäfer, A. Weiss, M. Tariq, V. Andrikopoulos, Santiago Gómez Sáez, Lukas Krawczyk, K. Rothermel\",\"doi\":\"10.1109/SCC.2016.24\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The workflow technology is the de facto standard for managing business processes. Today, workflows are even used for automating interactions and collaborations between business partners, e.g., for enabling just-in-time production. Every workflow that is part of such a collaboration needs to be highly available. Otherwise, the business operations, e.g., the production, might be hindered or even stopped. Since today's business partners are scattered across the globe, the workflows are executed in a highly distributed and heterogeneous environment. Those environments are, however, failure-prone and, thus, providing availability is not trivial. In this work, we improve availability by replicating workflow executions, while ensuring that the outcome is the same as in a non-replicated execution. For making workflow replication easily usable with current workflow technology, we derive the requirements for modeling a workflow replication system. Then, we propose the HAWKS system, which adheres to the previously specified requirements and is compatible with current technology. We implement a proof-of-concept in the open-source workflow execution engine Apache ODE for demonstrating this compatibility. Finally, we extensively evaluate the impact of using HAWKS in terms of performance and availability in the presence of failures.\",\"PeriodicalId\":115693,\"journal\":{\"name\":\"2016 IEEE International Conference on Services Computing (SCC)\",\"volume\":\"66 3\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE International Conference on Services Computing (SCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SCC.2016.24\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Services Computing (SCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SCC.2016.24","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
HAWKS: A System for Highly Available Executions of Workflows
The workflow technology is the de facto standard for managing business processes. Today, workflows are even used for automating interactions and collaborations between business partners, e.g., for enabling just-in-time production. Every workflow that is part of such a collaboration needs to be highly available. Otherwise, the business operations, e.g., the production, might be hindered or even stopped. Since today's business partners are scattered across the globe, the workflows are executed in a highly distributed and heterogeneous environment. Those environments are, however, failure-prone and, thus, providing availability is not trivial. In this work, we improve availability by replicating workflow executions, while ensuring that the outcome is the same as in a non-replicated execution. For making workflow replication easily usable with current workflow technology, we derive the requirements for modeling a workflow replication system. Then, we propose the HAWKS system, which adheres to the previously specified requirements and is compatible with current technology. We implement a proof-of-concept in the open-source workflow execution engine Apache ODE for demonstrating this compatibility. Finally, we extensively evaluate the impact of using HAWKS in terms of performance and availability in the presence of failures.