Vertical Workflows: Service Orchestration across Cloud & Edge Resources

O. Rana, M. Shaikh, Muhammad K. Ali, A. Anjum, L. Bittencourt
{"title":"Vertical Workflows: Service Orchestration across Cloud & Edge Resources","authors":"O. Rana, M. Shaikh, Muhammad K. Ali, A. Anjum, L. Bittencourt","doi":"10.1109/FiCloud.2018.00058","DOIUrl":null,"url":null,"abstract":"Currently devices used for data capture often differ from those that are used to subsequently carry out analysis on such data. Many Internet of Things (IoT) applications today involve data capture from sensors that are close to the phenomenon being measured, with such data subsequently being transmitted to Cloud data centers for analysis and storage. Increasing availability of storage and processing devices closer to the data capture device, perhaps over a one-hop network connection or even directly connected to the IoT device itself, requires more efficient allocation of processing across such edge devices and data centers. We refer to these as \"vertical workflows\" – i.e. workflows which are enacted across resources that can vary in: (i) type and behaviour; (ii) processing and storage capacity; (iii) latency and security profiles. Understanding how a workflow pipeline can be enacted across these resource types is outlined, motivated through two scenarios. The overall objective considered is the completion of the workflow within some deadline constraint, but with flexibility on where data processing is carried out.","PeriodicalId":174838,"journal":{"name":"2018 IEEE 6th International Conference on Future Internet of Things and Cloud (FiCloud)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 6th International Conference on Future Internet of Things and Cloud (FiCloud)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FiCloud.2018.00058","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10

Abstract

Currently devices used for data capture often differ from those that are used to subsequently carry out analysis on such data. Many Internet of Things (IoT) applications today involve data capture from sensors that are close to the phenomenon being measured, with such data subsequently being transmitted to Cloud data centers for analysis and storage. Increasing availability of storage and processing devices closer to the data capture device, perhaps over a one-hop network connection or even directly connected to the IoT device itself, requires more efficient allocation of processing across such edge devices and data centers. We refer to these as "vertical workflows" – i.e. workflows which are enacted across resources that can vary in: (i) type and behaviour; (ii) processing and storage capacity; (iii) latency and security profiles. Understanding how a workflow pipeline can be enacted across these resource types is outlined, motivated through two scenarios. The overall objective considered is the completion of the workflow within some deadline constraint, but with flexibility on where data processing is carried out.
垂直工作流:跨云和边缘资源的服务编排
目前用于数据捕获的设备通常与随后用于对这些数据进行分析的设备不同。如今,许多物联网(IoT)应用都涉及从靠近被测量现象的传感器捕获数据,随后将这些数据传输到云数据中心进行分析和存储。增加靠近数据采集设备的存储和处理设备的可用性,可能是通过一跳网络连接,甚至直接连接到物联网设备本身,这需要在这些边缘设备和数据中心之间更有效地分配处理。我们将这些称为“垂直工作流”,即跨资源制定的工作流,可以在以下方面有所不同:(i)类型和行为;(二)处理和储存能力;(iii)延迟和安全概况。通过两个场景,概述了如何跨这些资源类型制定工作流管道。考虑的总体目标是在一定的期限限制内完成工作流,但在执行数据处理的位置上具有灵活性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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