边云协同计算中成本感知的物联网数据处理方法

doi:10.11896/jsjkx.211000101

计算机科学 ›› 2022, Vol. 49 ›› Issue (11A): 211000101-7.doi: 10.11896/jsjkx.211000101

边云协同计算中成本感知的物联网数据处理方法

王晨华¹, 侯守璐¹, 刘秀磊^1,2

1 北京信息科技大学数据与科学情报分析研究所北京 100101
2 北京材料基因工程高精尖创新中心(北京信息科技大学) 北京 100101

出版日期:2022-11-10 发布日期:2022-11-21
通讯作者: 刘秀磊(xiuleiliu@hotmail.com)
作者简介:(w1760014@163.com)
基金资助:
促进高校分类发展-重点研究培育项目(2121YJPY225,2121YJPY226);科研机构创新能力建设-数据科学与情报分析研究所;促进高校内涵发展-面向边缘计算的创新科研平台建设项目(2020KYNH105)

Cost-aware IoT Data Processing in Edge-Cloud Collaborative Computing

WANG Chen-hua¹, HOU Shou-lu¹, LIU Xiu-lei^1,2

1 Institute of Data and Scientific Information Analysis,Beijing Information Science and Technology University,Beijing 100101,China
2 Beijing Material Genetic Engineering High-precision Innovation Center,Beijing Information Science and Technology University,Beijing 100101,China

Online:2022-11-10 Published:2022-11-21
About author:WANG Chen-hua,born in 1994,postgraduate.Her main research interests include Internet of things and edge computing.
LIU Xiu-lei,born in 1981,Ph.D,is a member of China Computer Federation.His main research interests include ontology matching,semantic sensor,knowledge graph,semantic Web and semantic search.
Supported by:
Promoting the Classified Development of Colleges and Universities-Key Research and Cultivation Project(2121YJPY225,2121YJPY226),Construction of Innovation Capability of Scientific Research Institutions-Institute of Data Science and Information Analysis and Promoting the Connotation Development of Colleges and Universities-Construction of an Innovative Scientific Research Platform for Edge Computing(2020KYNH105).

摘要/Abstract

摘要： 随着物联网终端设备联网产生大量计算密集型的任务,文中提出了一种针对边云协同计算中成本优化的大数据处理方法。首先,所提算法考虑网络传输带宽约束及计算资源约束,联合优化带宽资源、计算资源分配以及动态卸载策略。其次,应用MapReduce框架,建立边云协同计算模型,通过Lyapunov优化理论将目标公式拆分成4个子问题,分别进行优化求解。大量对比实验结果表明,通过合理利用边缘和云的力量,在保证系统稳定性的前提下,所提算法可以有效地提高云计算的数据处理效率,降低服务供应商的数据处理开销,同时,该算法可降低任务成本总开销及提高性价比(队列长度与运营成本的比值),在物联网数据处理过程中,应用边云协同计算方法对降低成本开销并提高性价比具有重要意义。

关键词: 物联网, 边云协同, 任务卸载, 运营成本, Lyapunov优化理论

Abstract: With the networking of Internet of Things(IoT) terminal devices,a large number of computation-intensive tasks appear.This paper proposes a cost-optimized big data processing method in the edge-cloud collaborative computing environment.Firstly,the proposed algorithm considers the constraints of network transmission bandwidth and computer resources,jointly optimizes bandwidth resources,and calculates resource distribution and dynamic offloading strategies.Secondly,based on the MapReduce framework,it establishes an edge-cloud collaborative computing model.According to Lyapunov optimization theory,it splits the target formula into four subproblems which can be solved separately.Comparative experiments results indicate that using the power of the edge rationally,the data processing efficiency of cloud computing can be improved and the expense of service provi-ders can be reduced.At the same time,the algorithm can improve the cost performance(the ratio of queue length to operating cost).In processing IoT data,is of great significance to reduce operating costs by utilizing edge-cloud collaborative computing methods.

Key words: Internet of things, Edge-cloud collaboration, Task offloading, Operating cost, Lyapunov optimization theory

中图分类号:

TP312

王晨华, 侯守璐, 刘秀磊. 边云协同计算中成本感知的物联网数据处理方法[J]. 计算机科学, 2022, 49(11A): 211000101-7. https://doi.org/10.11896/jsjkx.211000101

WANG Chen-hua, HOU Shou-lu, LIU Xiu-lei. Cost-aware IoT Data Processing in Edge-Cloud Collaborative Computing[J]. Computer Science, 2022, 49(11A): 211000101-7. https://doi.org/10.11896/jsjkx.211000101

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边云协同计算中成本感知的物联网数据处理方法

Cost-aware IoT Data Processing in Edge-Cloud Collaborative Computing

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