Task Scheduling for Streaming Applications in a Cloud-Edge System

  • Fei Yin
  • Xinjia Li
  • Xin LiEmail author
  • Yize Li
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11637)


With the increasing popularity of ubiquitous smart devices, more and more IoT (Internet of Things) data processing applications are deployed. Due to the inherent defects of traditional data transmission networks and the low latency requirement of applications, effective use of bandwidth computing resources to support the efficient deployment of applications has become a very important issue. In this paper, we focus on how to deploy multi-source streaming data processing applications in a cloud-edge collaborative computing network and pay attention to make the overall application data processing delay lower. We abstract the application into a form of streaming data processing, formalize it as a Stream Processing Task Scheduling Problem. We present an efficient algorithm to solve the above problem. Simulation experiments show that our approach can significantly reduce the end-to-end latency of applications compared to commonly used greedy algorithms.


Edge computing End to end delay Internet of Things Stream data processing Task scheduling 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.JiangSu Frontier Electric Technology Co., LTDNanjingChina
  2. 2.CCSTNanjing University of Aeronautics and AstronauticsNanjingChina
  3. 3.State Key Laboratory for Novel Software TechnologyNanjing UniversityNanjingChina

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