{"title":"基于时间可重构架构的能源感知服务编排","authors":"Emna Hosni, Zaki Brahmi","doi":"10.1109/WETICE.2016.23","DOIUrl":null,"url":null,"abstract":"Cloud computing is by far the most cost-effective technology for hosting Internet-scale services and applications. It becomes a valuable contributor and cost-saver for companies with the introduction of orchestration platforms as a Service (OaaS) to perform the services that support a variety of business processes such as BPEL. In this paper we will investigate three issues i) exploiting the minimum of resources to execute a maximum number of processes, ii) preventing possible overload to the server, and iii) minimizing the dynamic energy consumption which becomes one of the main challenges for large-scale computing, such as in cloud data center. As a solution for these challenges we propose a temporal partitioning based on dynamic reconfiguration approach. Our work aims to reduce the dynamic energy consumption. The proposed approach is based on two main steps: 1) Estimate the energy consumption of BPEL processes 2) Temporal and dynamic partitioning of BPEL process based on reconfigurable architecture in order to minimize overall energy consumption on each BPEL process at run time.","PeriodicalId":319817,"journal":{"name":"2016 IEEE 25th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Energy-Aware Service Orchestration Based on Temporal Reconfigurable Architecture\",\"authors\":\"Emna Hosni, Zaki Brahmi\",\"doi\":\"10.1109/WETICE.2016.23\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cloud computing is by far the most cost-effective technology for hosting Internet-scale services and applications. It becomes a valuable contributor and cost-saver for companies with the introduction of orchestration platforms as a Service (OaaS) to perform the services that support a variety of business processes such as BPEL. In this paper we will investigate three issues i) exploiting the minimum of resources to execute a maximum number of processes, ii) preventing possible overload to the server, and iii) minimizing the dynamic energy consumption which becomes one of the main challenges for large-scale computing, such as in cloud data center. As a solution for these challenges we propose a temporal partitioning based on dynamic reconfiguration approach. Our work aims to reduce the dynamic energy consumption. The proposed approach is based on two main steps: 1) Estimate the energy consumption of BPEL processes 2) Temporal and dynamic partitioning of BPEL process based on reconfigurable architecture in order to minimize overall energy consumption on each BPEL process at run time.\",\"PeriodicalId\":319817,\"journal\":{\"name\":\"2016 IEEE 25th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE 25th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WETICE.2016.23\",\"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 25th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WETICE.2016.23","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Energy-Aware Service Orchestration Based on Temporal Reconfigurable Architecture
Cloud computing is by far the most cost-effective technology for hosting Internet-scale services and applications. It becomes a valuable contributor and cost-saver for companies with the introduction of orchestration platforms as a Service (OaaS) to perform the services that support a variety of business processes such as BPEL. In this paper we will investigate three issues i) exploiting the minimum of resources to execute a maximum number of processes, ii) preventing possible overload to the server, and iii) minimizing the dynamic energy consumption which becomes one of the main challenges for large-scale computing, such as in cloud data center. As a solution for these challenges we propose a temporal partitioning based on dynamic reconfiguration approach. Our work aims to reduce the dynamic energy consumption. The proposed approach is based on two main steps: 1) Estimate the energy consumption of BPEL processes 2) Temporal and dynamic partitioning of BPEL process based on reconfigurable architecture in order to minimize overall energy consumption on each BPEL process at run time.