Joint Optimization of Task Scheduling and Image Placement in Fog Computing Supported Software-Defined Embedded System

Deze Zeng, Lin Gu, Song Guo, Zixue Cheng, Shui Yu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

292 Citations (Scopus)


Traditional standalone embedded system is limited in their functionality, flexibility, and scalability. Fog computing platform, characterized by pushing the cloud services to the network edge, is a promising solution to support and strengthen traditional embedded system. Resource management is always a critical issue to the system performance. In this paper, we consider a fog computing supported software-defined embedded system, where task images lay in the storage server while computations can be conducted on either embedded device or a computation server. It is significant to design an efficient task scheduling and resource management strategy with minimized task completion time for promoting the user experience. To this end, three issues are investigated in this paper: 1) how to balance the workload on a client device and computation servers, i.e., task scheduling, 2) how to place task images on storage servers, i.e., resource management, and 3) how to balance the I/O interrupt requests among the storage servers. They are jointly considered and formulated as a mixed-integer nonlinear programming problem. To deal with its high computation complexity, a computation-efficient solution is proposed based on our formulation and validated by extensive simulation based studies.
Original languageEnglish
Article number7422054
Pages (from-to)3702-3712
Number of pages11
JournalIEEE Transactions on Computers
Issue number12
Publication statusPublished - 1 Dec 2016
Externally publishedYes


  • Fog computing
  • optimization
  • resource management
  • software-defined embedded system
  • task scheduling

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Software
  • Hardware and Architecture
  • Computational Theory and Mathematics

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