article

Task scheduling algorithms for multi-cloud systems: allocation-aware approach

Authors:

Sanjaya K. Panda,

Indrajeet Gupta,

Prasanta K. JanaAuthors Info & Claims

Information Systems Frontiers, Volume 21, Issue 2

Pages 241 - 259

https://doi.org/10.1007/s10796-017-9742-6

Published: 01 April 2019 Publication History

Abstract

Cloud computing has gained enormous popularity for on-demand services on a pay-per-use basis. However, a single data center may be limited in providing such services, particularly in the peak demand time as it may not have unlimited resource capacity. Therefore, multi-cloud environment has been introduced in which multiple clouds can be integrated together to provide a unified service in a collaborative fashion. However, task scheduling in such environment is much more challenging than that is used in the single cloud environment. In this paper, we propose three allocation-aware task scheduling algorithms for a multi-cloud environment. The algorithms are based on the traditional Min-Min and Max-Min algorithm and extended for multi-cloud environment. All the algorithms undergo three common phases, namely matching, allocating and scheduling to fit them in the multi-cloud environment. We perform extensive simulations on the proposed algorithms and test with various benchmark and synthetic datasets. We evaluate the performance of the proposed algorithms in terms of makespan, average cloud utilization and throughput and compare the results with the existing algorithms in such system. The comparison results clearly demonstrate the efficacy of the proposed algorithms.

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Jawade PRamachandram S(2024)DAGWO based secure task scheduling in Multi-Cloud environment with risk probabilityMultimedia Tools and Applications10.1007/s11042-023-15687-183:1(2527-2550)Online publication date: 1-Jan-2024
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Task scheduling algorithms for multi-cloud systems: allocation-aware approach
1. Software and its engineering
  1. Software creation and management
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2. Theory of computation
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      1. Online learning algorithms
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      1. Reinforcement learning

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cover image Information Systems Frontiers

Information Systems Frontiers Volume 21, Issue 2

April 2019

261 pages

ISSN:1387-3326

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Copyright © Copyright © 2019 Springer Science+Business Media, LLC, part of Springer Nature.

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Kluwer Academic Publishers

United States

Publication History

Published: 01 April 2019

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Cited By

Jawade PRamachandram S(2024)DAGWO based secure task scheduling in Multi-Cloud environment with risk probabilityMultimedia Tools and Applications10.1007/s11042-023-15687-183:1(2527-2550)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1007/s11042-023-15687-1
Stavrinides GKaratza H(2024)Security, Cost and Energy Aware Scheduling of Real-Time IoT Workflows in a Mist Computing EnvironmentInformation Systems Frontiers10.1007/s10796-022-10304-226:4(1223-1241)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1007/s10796-022-10304-2
Singh SSingh PTanwar S(2023)Energy aware resource allocation via MS-SLnO in cloud data centerMultimedia Tools and Applications10.1007/s11042-023-15521-882:29(45541-45563)Online publication date: 1-Dec-2023
https://dl.acm.org/doi/10.1007/s11042-023-15521-8
Jawade PRamachandram S(2022)Multi-objective secure task scheduling based on SLA in multi-cloud environmentMultiagent and Grid Systems10.3233/MGS-22036218:1(65-85)Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.3233/MGS-220362
Neelakantan PYadav N(2022)Multi objective task scheduling based on hybrid metaheuristic algorithm for cloud environmentMultiagent and Grid Systems10.3233/MGS-22021818:2(149-169)Online publication date: 1-Jan-2022
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Tak MJoshi APanda SSahni SSaxena VIyengar S(2022)Cloud Task Scheduling Algorithms using Teaching-Learning-Based Optimization and Jaya AlgorithmProceedings of the 2022 Fourteenth International Conference on Contemporary Computing10.1145/3549206.3549227(106-113)Online publication date: 4-Aug-2022
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Hamid LJadoon AAsghar H(2022)Comparative analysis of task level heuristic scheduling algorithms in cloud computingThe Journal of Supercomputing10.1007/s11227-022-04382-x78:11(12931-12949)Online publication date: 1-Jul-2022
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Yuan SDas SRamesh RQiao C(2022)Availability-Aware Virtual Resource Provisioning for Infrastructure Service Agreements in the CloudInformation Systems Frontiers10.1007/s10796-022-10302-425:4(1495-1512)Online publication date: 20-Jun-2022
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Yang YRen FZhang M(2022)A Hybrid Multiagent-Based Rescheduling Mechanism for Open and Stochastic Environments Concerning the Execution StageAI 2021: Advances in Artificial Intelligence10.1007/978-3-030-97546-3_45(556-569)Online publication date: 2-Feb-2022
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Shi LXu JWang LChen JJin ZOuyang TXu JFan Y(2021)Multijob Associated Task Scheduling for Cloud Computing Based on Task Duplication and InsertionWireless Communications & Mobile Computing10.1155/2021/66317522021Online publication date: 1-Jan-2021
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