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Prioritized task scheduling in fog computing

Published: 29 March 2018 Publication History

Abstract

Fog computing, similar to edge computing, has been proposed as a model to introduce a virtualized layer between the end users and the back-end cloud data centers. Fog computing has attracted much attention due to the recent rapid deployment of smart devices and Internet-of-Things (IoT) systems, which often requires real-time, stringent-delay services. The fog layer placed between client and cloud layers aims to reduce the delay in terms of transmission and processing times, as well as the overall cost. To support the increasing number of IoT, smart devices, and to improve performance and reduce cost, this paper proposes a task scheduling algorithm in the fog layer based on priority levels. The proposed architecture, queueing and priority models, priority assignment module, and the priority-based task scheduling algorithms are carefully described. Performance evaluation shows that, comparing with existing task scheduling algorithms, the proposed algorithm reduces the overall response time and notably decreases the total cost. We believe that this work is significant to the emerging fog computing technology, and the priority-based algorithm is useful to a wide range of application domains.

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Cited By

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  • (2024)Honey bee inspired resource allocation scheme for IoT-driven smart healthcare applications in fog-cloud paradigmPeerJ Computer Science10.7717/peerj-cs.248410(e2484)Online publication date: 19-Nov-2024
  • (2024)Improved Double Deep Q Network-Based Task Scheduling Algorithm in Edge Computing for Makespan OptimizationTsinghua Science and Technology10.26599/TST.2023.901005829:3(806-817)Online publication date: Jun-2024
  • (2024)A Comprehensive Analysis of optimization of task scheduling algorithms for IOT applications in a Combined Environment of Cloud, Fog and Edge2024 Third International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN)10.1109/ICSTSN61422.2024.10670804(1-6)Online publication date: 18-Jul-2024
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    cover image ACM Conferences
    ACMSE '18: Proceedings of the 2018 ACM Southeast Conference
    March 2018
    246 pages
    ISBN:9781450356961
    DOI:10.1145/3190645
    • Conference Chair:
    • Ka-Wing Wong,
    • Program Chair:
    • Chi Shen,
    • Publications Chair:
    • Dana Brown
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    New York, NY, United States

    Publication History

    Published: 29 March 2018

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    Author Tags

    1. cloud computing
    2. fog computing
    3. priority levels
    4. resource allocation
    5. task scheduling

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    ACM SE '18
    Sponsor:
    ACM SE '18: Southeast Conference
    March 29 - 31, 2018
    Kentucky, Richmond

    Acceptance Rates

    ACMSE '18 Paper Acceptance Rate 34 of 41 submissions, 83%;
    Overall Acceptance Rate 502 of 1,023 submissions, 49%

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    Cited By

    View all
    • (2024)Honey bee inspired resource allocation scheme for IoT-driven smart healthcare applications in fog-cloud paradigmPeerJ Computer Science10.7717/peerj-cs.248410(e2484)Online publication date: 19-Nov-2024
    • (2024)Improved Double Deep Q Network-Based Task Scheduling Algorithm in Edge Computing for Makespan OptimizationTsinghua Science and Technology10.26599/TST.2023.901005829:3(806-817)Online publication date: Jun-2024
    • (2024)A Comprehensive Analysis of optimization of task scheduling algorithms for IOT applications in a Combined Environment of Cloud, Fog and Edge2024 Third International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN)10.1109/ICSTSN61422.2024.10670804(1-6)Online publication date: 18-Jul-2024
    • (2024)D-NPGA : a new approach for tasks offloading in fog/cloud environment2024 10th International Conference on Control, Decision and Information Technologies (CoDIT)10.1109/CoDIT62066.2024.10708605(193-198)Online publication date: 1-Jul-2024
    • (2024)Data-Priority Aware Fair Task Scheduling for Stream Processing at the Edge2024 IEEE Cloud Summit10.1109/Cloud-Summit61220.2024.00026(117-122)Online publication date: 27-Jun-2024
    • (2024)ETPAM: An Efficient Task Pre-Assignment and Migration Algorithm in Heterogeneous Edge-Cloud Computing Environments2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD)10.1109/CSCWD61410.2024.10580834(2400-2405)Online publication date: 8-May-2024
    • (2024)EdgeMatch: A Smart Approach for Scheduling IoT-Edge Tasks With Multiple Criteria Using Game TheoryIEEE Access10.1109/ACCESS.2024.335055612(7609-7623)Online publication date: 2024
    • (2024)Research allocation in mobile volunteer computing systemFuture Generation Computer Systems10.1016/j.future.2024.01.015154:C(251-265)Online publication date: 25-Jun-2024
    • (2024)Streamlining Task Planning Systems for Improved Enactment in Contemporary Computing SurroundingsSN Computer Science10.1007/s42979-024-03267-55:8Online publication date: 28-Oct-2024
    • (2024)MOTORS: multi-objective task offloading and resource scheduling algorithm for heterogeneous fog-cloud computing scenarioThe Journal of Supercomputing10.1007/s11227-024-06315-280:15(22315-22361)Online publication date: 23-Jun-2024
    • Show More Cited By

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