支持硬件重构的多云协作框架

Khaleel W. Mershad, Abdulrahman Kaitoua, H. Artail, M. Saghir, Hazem M. Hajj
{"title":"支持硬件重构的多云协作框架","authors":"Khaleel W. Mershad, Abdulrahman Kaitoua, H. Artail, M. Saghir, Hazem M. Hajj","doi":"10.1109/SERVICES.2013.12","DOIUrl":null,"url":null,"abstract":"Cloud computing is increasingly becoming a desirable and foundational element in international enterprise computing. There are many companies which design, develop, and offer cloud technologies. However, cloud providers are still like lone islands. While current cloud computing models have provided significant benefits of maximizing the use of resources within a cloud, the current solutions still face many challenges including the lack of cross-leverage of available resources across clouds, the need to move data between clouds in some cases, and the lack of a global efficient cooperation between clouds. In [1], we addressed some of these challenges by providing an approach that enables various cloud providers to cooperate in order to execute, together, common requests. In this paper, we illustrate several enhancements to our work in [1] which focus on integrating hardware acceleration with the cloud services. We extend the Hadoop framework by adding provisions for hardware acceleration with Field Programmable Gate Arrays (FPGAs) within the cloud, for multi-cloud interaction, and for global cloud management. Hardware acceleration is used to offload computations when needed or as a service within the clouds. It can provide additional sources of revenues, reduced operating costs, and increased resource utilization. We derive a mathematical model for evaluating the performance of the most important entity in our system under various conditions.","PeriodicalId":169370,"journal":{"name":"2013 IEEE Ninth World Congress on Services","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A Framework for Multi-cloud Cooperation with Hardware Reconfiguration Support\",\"authors\":\"Khaleel W. Mershad, Abdulrahman Kaitoua, H. Artail, M. Saghir, Hazem M. Hajj\",\"doi\":\"10.1109/SERVICES.2013.12\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cloud computing is increasingly becoming a desirable and foundational element in international enterprise computing. There are many companies which design, develop, and offer cloud technologies. However, cloud providers are still like lone islands. While current cloud computing models have provided significant benefits of maximizing the use of resources within a cloud, the current solutions still face many challenges including the lack of cross-leverage of available resources across clouds, the need to move data between clouds in some cases, and the lack of a global efficient cooperation between clouds. In [1], we addressed some of these challenges by providing an approach that enables various cloud providers to cooperate in order to execute, together, common requests. In this paper, we illustrate several enhancements to our work in [1] which focus on integrating hardware acceleration with the cloud services. We extend the Hadoop framework by adding provisions for hardware acceleration with Field Programmable Gate Arrays (FPGAs) within the cloud, for multi-cloud interaction, and for global cloud management. Hardware acceleration is used to offload computations when needed or as a service within the clouds. It can provide additional sources of revenues, reduced operating costs, and increased resource utilization. We derive a mathematical model for evaluating the performance of the most important entity in our system under various conditions.\",\"PeriodicalId\":169370,\"journal\":{\"name\":\"2013 IEEE Ninth World Congress on Services\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-06-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE Ninth World Congress on Services\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SERVICES.2013.12\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE Ninth World Congress on Services","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SERVICES.2013.12","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

摘要

云计算正日益成为国际企业计算中一个理想的基础元素。有许多公司设计、开发和提供云技术。然而,云提供商仍然像孤岛一样。虽然当前的云计算模型为最大限度地利用云中的资源提供了显著的好处,但当前的解决方案仍然面临许多挑战,包括缺乏跨云可用资源的交叉利用,在某些情况下需要在云之间移动数据,以及缺乏云之间的全局高效合作。在[1]中,我们通过提供一种方法来解决其中的一些挑战,该方法使各种云提供商能够合作,以便一起执行共同的请求。在本文中,我们说明了对[1]中工作的几个增强,重点是将硬件加速与云服务集成在一起。我们扩展了Hadoop框架,在云中添加了现场可编程门阵列(fpga)的硬件加速,用于多云交互和全局云管理。硬件加速用于在需要时卸载计算或作为云中的服务。它可以提供额外的收入来源,降低运营成本,提高资源利用率。我们推导了一个数学模型来评估系统中最重要的实体在各种条件下的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Framework for Multi-cloud Cooperation with Hardware Reconfiguration Support
Cloud computing is increasingly becoming a desirable and foundational element in international enterprise computing. There are many companies which design, develop, and offer cloud technologies. However, cloud providers are still like lone islands. While current cloud computing models have provided significant benefits of maximizing the use of resources within a cloud, the current solutions still face many challenges including the lack of cross-leverage of available resources across clouds, the need to move data between clouds in some cases, and the lack of a global efficient cooperation between clouds. In [1], we addressed some of these challenges by providing an approach that enables various cloud providers to cooperate in order to execute, together, common requests. In this paper, we illustrate several enhancements to our work in [1] which focus on integrating hardware acceleration with the cloud services. We extend the Hadoop framework by adding provisions for hardware acceleration with Field Programmable Gate Arrays (FPGAs) within the cloud, for multi-cloud interaction, and for global cloud management. Hardware acceleration is used to offload computations when needed or as a service within the clouds. It can provide additional sources of revenues, reduced operating costs, and increased resource utilization. We derive a mathematical model for evaluating the performance of the most important entity in our system under various conditions.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信