research-article

An Improved Task Allocation Scheme in Serverless Computing Using Gray Wolf Optimization (GWO) Based Reinforcement Learning (RIL) Approach

Authors:

T. Karthikeyan,

K. PraghashAuthors Info & Claims

Wireless Personal Communications, Volume 117, Issue 3

Pages 2403 - 2421

https://doi.org/10.1007/s11277-020-07981-0

Published: 01 April 2021 Publication History

Abstract

Serverless computing offers a wide variety of event-driven integrations and cloud services, easy development and implementation frameworks, and complex balancing and control of costs. With these benefits into consideration, the growing implementation of serverless systems means that the performance of the serverless system is measured and new techniques created to maximize the potential of the software. The serverless or system runtime features have shown major performance and cost advantages for event-driven cloud applications. While serverless runtimes are limited to applications requiring lightweight data and storage, such as the prediction and inference of machine learning, these applications have been improved beyond other cloud runtimes. In this paper, we propose a machine learning model to parallelize the jobs allocated to the event queue and the dispatcher of the serverless framework. We hence use Gray Wolf Optimization (GWO) model to improve the process of task allocation. Further, to optimize GWO, we use the Reinforcement Learning (RIL) approach that simultaneously optimizes the parameters of GWO and improves the task allocation. The simulation studies show that the proposed GWO-RIL offers reduced runtimes and it adapts with varying load conditions.

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Cited By

Altunbas YTurk K(2024)Power Allocation with Meta-heuristic Algorithms for Indoor MIMO-NOMA Based VLC SystemsWireless Personal Communications: An International Journal10.1007/s11277-024-11340-8136:1(617-630)Online publication date: 1-May-2024
https://dl.acm.org/doi/10.1007/s11277-024-11340-8
Yan SXia Y(2024)A distributed task allocation method for heterogeneous UAVs in dynamic and communication-constrained environmentsThe Journal of Supercomputing10.1007/s11227-024-06517-881:1Online publication date: 16-Oct-2024
https://dl.acm.org/doi/10.1007/s11227-024-06517-8
Ghorbian MGhobaei-Arani MEsmaeili L(2024)A survey on the scheduling mechanisms in serverless computing: a taxonomy, challenges, and trendsCluster Computing10.1007/s10586-023-04264-827:5(5571-5610)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1007/s10586-023-04264-8
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cover image Wireless Personal Communications: An International Journal

Wireless Personal Communications: An International Journal Volume 117, Issue 3

Apr 2021

896 pages

ISSN:0929-6212

Issue’s Table of Contents

© Springer Science+Business Media, LLC, part of Springer Nature 2020.

Publisher

Kluwer Academic Publishers

United States

Publication History

Published: 01 April 2021

Accepted: 11 November 2020

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Cited By

Altunbas YTurk K(2024)Power Allocation with Meta-heuristic Algorithms for Indoor MIMO-NOMA Based VLC SystemsWireless Personal Communications: An International Journal10.1007/s11277-024-11340-8136:1(617-630)Online publication date: 1-May-2024
https://dl.acm.org/doi/10.1007/s11277-024-11340-8
Yan SXia Y(2024)A distributed task allocation method for heterogeneous UAVs in dynamic and communication-constrained environmentsThe Journal of Supercomputing10.1007/s11227-024-06517-881:1Online publication date: 16-Oct-2024
https://dl.acm.org/doi/10.1007/s11227-024-06517-8
Ghorbian MGhobaei-Arani MEsmaeili L(2024)A survey on the scheduling mechanisms in serverless computing: a taxonomy, challenges, and trendsCluster Computing10.1007/s10586-023-04264-827:5(5571-5610)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1007/s10586-023-04264-8
Wen JChen ZJin XLiu X(2023)Rise of the Planet of Serverless Computing: A Systematic ReviewACM Transactions on Software Engineering and Methodology10.1145/357964332:5(1-61)Online publication date: 21-Jul-2023
https://dl.acm.org/doi/10.1145/3579643
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