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Near real-time optimization of fog service placement for responsive edge computing

Tom Goethals (UGent) , Filip De Turck (UGent) and Bruno Volckaert (UGent)
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Abstract
In recent years, computing workloads have shifted from the cloud to the fog, and IoT devices are becoming powerful enough to run containerized services. While the combination of IoT devices and fog computing has many advantages, such as increased efficiency, reduced network traffic and better end user experience, the scale and volatility of the fog and edge also present new problems for service deployment scheduling.Fog and edge networks contain orders of magnitude more devices than cloud data centers, and they are often less stable and slower. Additionally, frequent changes in network topology and the number of connected devices are the norm in edge networks, rather than the exception as in cloud data centers.This article presents a service scheduling algorithm, labeled "Swirly", for fog and edge networks containing hundreds of thousands of devices, which is capable of incorporating changes in network conditions and connected devices. The theoretical performance is explored, and a model of the behaviour and limits of fog nodes is constructed. An evaluation of Swirly is performed, showing that it is capable of managing service meshes for at least 300.000 devices in near real-time.
Keywords
Fog computing, Fog networks, Edge networks, Service mesh, Service, scheduling, Edge computing

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MLA
Goethals, Tom, et al. “Near Real-Time Optimization of Fog Service Placement for Responsive Edge Computing.” JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS, vol. 9, no. 1, 2020, doi:10.1186/s13677-020-00180-z.
APA
Goethals, T., De Turck, F., & Volckaert, B. (2020). Near real-time optimization of fog service placement for responsive edge computing. JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS, 9(1). https://doi.org/10.1186/s13677-020-00180-z
Chicago author-date
Goethals, Tom, Filip De Turck, and Bruno Volckaert. 2020. “Near Real-Time Optimization of Fog Service Placement for Responsive Edge Computing.” JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS 9 (1). https://doi.org/10.1186/s13677-020-00180-z.
Chicago author-date (all authors)
Goethals, Tom, Filip De Turck, and Bruno Volckaert. 2020. “Near Real-Time Optimization of Fog Service Placement for Responsive Edge Computing.” JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS 9 (1). doi:10.1186/s13677-020-00180-z.
Vancouver
1.
Goethals T, De Turck F, Volckaert B. Near real-time optimization of fog service placement for responsive edge computing. JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS. 2020;9(1).
IEEE
[1]
T. Goethals, F. De Turck, and B. Volckaert, “Near real-time optimization of fog service placement for responsive edge computing,” JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS, vol. 9, no. 1, 2020.
@article{8669806,
  abstract     = {In recent years, computing workloads have shifted from the cloud to the fog, and IoT devices are becoming powerful enough to run containerized services. While the combination of IoT devices and fog computing has many advantages, such as increased efficiency, reduced network traffic and better end user experience, the scale and volatility of the fog and edge also present new problems for service deployment scheduling.Fog and edge networks contain orders of magnitude more devices than cloud data centers, and they are often less stable and slower. Additionally, frequent changes in network topology and the number of connected devices are the norm in edge networks, rather than the exception as in cloud data centers.This article presents a service scheduling algorithm, labeled "Swirly", for fog and edge networks containing hundreds of thousands of devices, which is capable of incorporating changes in network conditions and connected devices. The theoretical performance is explored, and a model of the behaviour and limits of fog nodes is constructed. An evaluation of Swirly is performed, showing that it is capable of managing service meshes for at least 300.000 devices in near real-time.},
  articleno    = {34},
  author       = {Goethals, Tom and De Turck, Filip and Volckaert, Bruno},
  issn         = {2192-113X},
  journal      = {JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS},
  keywords     = {Fog computing,Fog networks,Edge networks,Service mesh,Service,scheduling,Edge computing},
  language     = {eng},
  number       = {1},
  pages        = {17},
  title        = {Near real-time optimization of fog service placement for responsive edge computing},
  url          = {http://dx.doi.org/10.1186/s13677-020-00180-z},
  volume       = {9},
  year         = {2020},
}

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