research-article

Workload Characterization: Survey of Current Approaches and Research Challenges

Authors:

S. R. Shishira,

K. ChandrasekaranAuthors Info & Claims

ICCCT-2017: Proceedings of the 7th International Conference on Computer and Communication Technology

Pages 151 - 156

https://doi.org/10.1145/3154979.3155003

Published: 24 November 2017 Publication History

Abstract

Workload is a set of inputs given to a infrastructure for processing. Performance can be measured based on the efficient processing of the workloads. Different workloads has different set of characteristics. In this paper, we have mainly focused on cloud workloads. Understanding the characteristics of workloads is the key to make an optimal configuration decisions and improve the system performance. This paper describes various computing workloads and relates them to their resource utilization. Specifically, the paper concentrates on cloud workloads characterization. We have classified the workloads based on different aspects from the literature also we have provided the characteristic features of the workload to know the properties and make it more understandable for the researchers.

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Cited By

Esmaili MChristensen K(2025)Performance Modeling of Public Permissionless Blockchains: A SurveyACM Computing Surveys10.1145/371509457:7(1-35)Online publication date: 20-Feb-2025
https://dl.acm.org/doi/10.1145/3715094
Aghili RQin QLi HKhomh F(2024)Understanding Web Application Workloads and Their Applications: Systematic Literature Review and Characterization2024 IEEE International Conference on Software Maintenance and Evolution (ICSME)10.1109/ICSME58944.2024.00050(474-486)Online publication date: 6-Oct-2024
https://doi.org/10.1109/ICSME58944.2024.00050
Chaudhari PKaneko SOkamura T(2023)Estimating Power Consumption of Collocated Workloads in a Real-World Data Center2023 International Conference on Software, Telecommunications and Computer Networks (SoftCOM)10.23919/SoftCOM58365.2023.10271681(1-7)Online publication date: 21-Sep-2023
https://doi.org/10.23919/SoftCOM58365.2023.10271681
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cover image ACM Other conferences

ICCCT-2017: Proceedings of the 7th International Conference on Computer and Communication Technology

November 2017

157 pages

ISBN:9781450353243

DOI:10.1145/3154979

Copyright © 2017 ACM.

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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Publication History

Published: 24 November 2017

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ICCCT-2017

ICCCT-2017: International Conference on Computer and Communication Technology

November 24 - 26, 2017

Allahabad, India

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ICCCT-2017 Paper Acceptance Rate 33 of 124 submissions, 27%;

Overall Acceptance Rate 33 of 124 submissions, 27%

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Cited By

Esmaili MChristensen K(2025)Performance Modeling of Public Permissionless Blockchains: A SurveyACM Computing Surveys10.1145/371509457:7(1-35)Online publication date: 20-Feb-2025
https://dl.acm.org/doi/10.1145/3715094
Aghili RQin QLi HKhomh F(2024)Understanding Web Application Workloads and Their Applications: Systematic Literature Review and Characterization2024 IEEE International Conference on Software Maintenance and Evolution (ICSME)10.1109/ICSME58944.2024.00050(474-486)Online publication date: 6-Oct-2024
https://doi.org/10.1109/ICSME58944.2024.00050
Chaudhari PKaneko SOkamura T(2023)Estimating Power Consumption of Collocated Workloads in a Real-World Data Center2023 International Conference on Software, Telecommunications and Computer Networks (SoftCOM)10.23919/SoftCOM58365.2023.10271681(1-7)Online publication date: 21-Sep-2023
https://doi.org/10.23919/SoftCOM58365.2023.10271681
Sampaio ABeschastnikh IMaier DBourne DSundaresen VLiu AMuccini H(2023)Auto-Tuning Elastic Applications in ProductionProceedings of the 45th International Conference on Software Engineering: Software Engineering in Practice10.1109/ICSE-SEIP58684.2023.00038(355-367)Online publication date: 17-May-2023
https://dl.acm.org/doi/10.1109/ICSE-SEIP58684.2023.00038
Uma VMarimuthu R(2023)D-wash – A dynamic workload aware adaptive cache coherance protocol for multi-core processor systemMicroelectronics Journal10.1016/j.mejo.2022.105675132:COnline publication date: 1-Feb-2023
https://dl.acm.org/doi/10.1016/j.mejo.2022.105675
Liang YChen KYi LSu XJin X(2023)DeGTeCFuture Generation Computer Systems10.1016/j.future.2022.11.014141:C(81-95)Online publication date: 1-Apr-2023
https://dl.acm.org/doi/10.1016/j.future.2022.11.014
Raza ZJangu N(2022)Workload ClassificationInternational Journal of Systems and Service-Oriented Engineering10.4018/IJSSOE.29713512:1(1-14)Online publication date: 4-Mar-2022
https://dl.acm.org/doi/10.4018/IJSSOE.297135
Matoussi WHamrouni T(2022)A new temporal locality-based workload prediction approach for SaaS services in a cloud environmentJournal of King Saud University - Computer and Information Sciences10.1016/j.jksuci.2021.04.00834:7(3973-3987)Online publication date: Jul-2022
https://doi.org/10.1016/j.jksuci.2021.04.008
E JR V(2022)Enhancing the performance of asymmetric architectures and workload characterization using LSTM learning algorithmAdvances in Engineering Software10.1016/j.advengsoft.2022.103266173:COnline publication date: 1-Nov-2022
https://dl.acm.org/doi/10.1016/j.advengsoft.2022.103266
Sindhu KSeshadri KKollengode C(2022)Workload characterization and synthesis for cloud using generative stochastic processesThe Journal of Supercomputing10.1007/s11227-022-04597-y78:17(18825-18855)Online publication date: 13-Jun-2022
https://doi.org/10.1007/s11227-022-04597-y
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