QCon: QoS-aware network resource management for fog computing

Cheol Ho Hong, Kyungwoon Lee, Minkoo Kang, Hyuck Yoo

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Fog computing is a new computing paradigm that employs computation and network resources at the edge of a network to build small clouds, which perform as small data centers. In fog computing, lightweight virtualization (e.g., containers) has been widely used to achieve low overhead for performance-limited fog devices such as WiFi access points (APs) and set-top boxes. Unfortunately, containers have a weakness in the control of network bandwidth for outbound traffic, which poses a challenge to fog computing. Existing solutions for containers fail to achieve desirable network bandwidth control, which causes bandwidth-sensitive applications to suffer unacceptable network performance. In this paper, we propose qCon, which is a QoS-aware network resource management framework for containers to limit the rate of outbound traffic in fog computing. qCon aims to provide both proportional share scheduling and bandwidth shaping to satisfy various performance demands from containers while implementing a lightweight framework. For this purpose, qCon supports the following three scheduling policies that can be applied to containers simultaneously: proportional share scheduling, minimum bandwidth reservation, and maximum bandwidth limitation. For a lightweight implementation, qCon develops its own scheduling framework on the Linux bridge by interposing qCon’s scheduling interface on the frame processing function of the bridge. To show qCon’s effectiveness in a real fog computing environment, we implement qCon in a Docker container infrastructure on a performance-limited fog device—a Raspberry Pi 3 Model B board.

Original languageEnglish
Article number3444
JournalSensors (Switzerland)
Volume18
Issue number10
DOIs
Publication statusPublished - 2018 Oct 13

Fingerprint

resources management
fog
Weather
Fog
containers
Containers
Quality of service
scheduling
bandwidth
Bandwidth
Scheduling
traffic
Set-top boxes
Network performance
Telecommunication traffic
boxes
resources
Equipment and Supplies
causes
Processing

Keywords

  • Fog computing
  • IoT architecture
  • Network resource management
  • QoS policy

ASJC Scopus subject areas

  • Analytical Chemistry
  • Atomic and Molecular Physics, and Optics
  • Biochemistry
  • Instrumentation
  • Electrical and Electronic Engineering

Cite this

QCon : QoS-aware network resource management for fog computing. / Hong, Cheol Ho; Lee, Kyungwoon; Kang, Minkoo; Yoo, Hyuck.

In: Sensors (Switzerland), Vol. 18, No. 10, 3444, 13.10.2018.

Research output: Contribution to journalArticle

Hong, Cheol Ho ; Lee, Kyungwoon ; Kang, Minkoo ; Yoo, Hyuck. / QCon : QoS-aware network resource management for fog computing. In: Sensors (Switzerland). 2018 ; Vol. 18, No. 10.
@article{63f508cfa3a348309efb4c6789db8b5f,
title = "QCon: QoS-aware network resource management for fog computing",
abstract = "Fog computing is a new computing paradigm that employs computation and network resources at the edge of a network to build small clouds, which perform as small data centers. In fog computing, lightweight virtualization (e.g., containers) has been widely used to achieve low overhead for performance-limited fog devices such as WiFi access points (APs) and set-top boxes. Unfortunately, containers have a weakness in the control of network bandwidth for outbound traffic, which poses a challenge to fog computing. Existing solutions for containers fail to achieve desirable network bandwidth control, which causes bandwidth-sensitive applications to suffer unacceptable network performance. In this paper, we propose qCon, which is a QoS-aware network resource management framework for containers to limit the rate of outbound traffic in fog computing. qCon aims to provide both proportional share scheduling and bandwidth shaping to satisfy various performance demands from containers while implementing a lightweight framework. For this purpose, qCon supports the following three scheduling policies that can be applied to containers simultaneously: proportional share scheduling, minimum bandwidth reservation, and maximum bandwidth limitation. For a lightweight implementation, qCon develops its own scheduling framework on the Linux bridge by interposing qCon’s scheduling interface on the frame processing function of the bridge. To show qCon’s effectiveness in a real fog computing environment, we implement qCon in a Docker container infrastructure on a performance-limited fog device—a Raspberry Pi 3 Model B board.",
keywords = "Fog computing, IoT architecture, Network resource management, QoS policy",
author = "Hong, {Cheol Ho} and Kyungwoon Lee and Minkoo Kang and Hyuck Yoo",
year = "2018",
month = "10",
day = "13",
doi = "10.3390/s18103444",
language = "English",
volume = "18",
journal = "Sensors (Switzerland)",
issn = "1424-8220",
publisher = "Multidisciplinary Digital Publishing Institute (MDPI)",
number = "10",

}

TY - JOUR

T1 - QCon

T2 - QoS-aware network resource management for fog computing

AU - Hong, Cheol Ho

AU - Lee, Kyungwoon

AU - Kang, Minkoo

AU - Yoo, Hyuck

PY - 2018/10/13

Y1 - 2018/10/13

N2 - Fog computing is a new computing paradigm that employs computation and network resources at the edge of a network to build small clouds, which perform as small data centers. In fog computing, lightweight virtualization (e.g., containers) has been widely used to achieve low overhead for performance-limited fog devices such as WiFi access points (APs) and set-top boxes. Unfortunately, containers have a weakness in the control of network bandwidth for outbound traffic, which poses a challenge to fog computing. Existing solutions for containers fail to achieve desirable network bandwidth control, which causes bandwidth-sensitive applications to suffer unacceptable network performance. In this paper, we propose qCon, which is a QoS-aware network resource management framework for containers to limit the rate of outbound traffic in fog computing. qCon aims to provide both proportional share scheduling and bandwidth shaping to satisfy various performance demands from containers while implementing a lightweight framework. For this purpose, qCon supports the following three scheduling policies that can be applied to containers simultaneously: proportional share scheduling, minimum bandwidth reservation, and maximum bandwidth limitation. For a lightweight implementation, qCon develops its own scheduling framework on the Linux bridge by interposing qCon’s scheduling interface on the frame processing function of the bridge. To show qCon’s effectiveness in a real fog computing environment, we implement qCon in a Docker container infrastructure on a performance-limited fog device—a Raspberry Pi 3 Model B board.

AB - Fog computing is a new computing paradigm that employs computation and network resources at the edge of a network to build small clouds, which perform as small data centers. In fog computing, lightweight virtualization (e.g., containers) has been widely used to achieve low overhead for performance-limited fog devices such as WiFi access points (APs) and set-top boxes. Unfortunately, containers have a weakness in the control of network bandwidth for outbound traffic, which poses a challenge to fog computing. Existing solutions for containers fail to achieve desirable network bandwidth control, which causes bandwidth-sensitive applications to suffer unacceptable network performance. In this paper, we propose qCon, which is a QoS-aware network resource management framework for containers to limit the rate of outbound traffic in fog computing. qCon aims to provide both proportional share scheduling and bandwidth shaping to satisfy various performance demands from containers while implementing a lightweight framework. For this purpose, qCon supports the following three scheduling policies that can be applied to containers simultaneously: proportional share scheduling, minimum bandwidth reservation, and maximum bandwidth limitation. For a lightweight implementation, qCon develops its own scheduling framework on the Linux bridge by interposing qCon’s scheduling interface on the frame processing function of the bridge. To show qCon’s effectiveness in a real fog computing environment, we implement qCon in a Docker container infrastructure on a performance-limited fog device—a Raspberry Pi 3 Model B board.

KW - Fog computing

KW - IoT architecture

KW - Network resource management

KW - QoS policy

UR - http://www.scopus.com/inward/record.url?scp=85054888814&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85054888814&partnerID=8YFLogxK

U2 - 10.3390/s18103444

DO - 10.3390/s18103444

M3 - Article

C2 - 30322161

AN - SCOPUS:85054888814

VL - 18

JO - Sensors (Switzerland)

JF - Sensors (Switzerland)

SN - 1424-8220

IS - 10

M1 - 3444

ER -