Computer Science

Computer Science ›› 2022, Vol. 49 ›› Issue (11A): 211000101-7.doi: 10.11896/jsjkx.211000101

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

WANG Chen-hua1, HOU Shou-lu1, LIU Xiu-lei1,2   

  1. 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).

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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

CLC Number: 

  • TP312
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