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Hestia: A Cost-Effective Multi-dimensional Resource Utilization for Microservices Execution in the Cloud
Huang, Jiahua1,2; Kent, Kenneth B.3; Yen, Jerome4; Wang, Yang1,2
2022
Conference Name15th International Conference on Cloud Computing, CLOUD 2022, held as part of the Services Conference Federation, SCF 2022
Source PublicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13731 LNCS
Pages22-38
Conference Date10 December 2022through 14 December 2022
Conference PlaceHonolulu
CountryUSA
Author of SourceYe K., Zhang L.-J.
PublisherSpringer Science and Business Media Deutschland GmbH
Abstract

It is well-known that effective resource utilization is a critical factor in providing high quality microservicess in cloud computing. In a large-scale cluster, if each machine can save a small amount of resources, a huge effect could be made to significantly reduce the overall computing cost as the saved resources across the cluster can be gathered into a large resource pool to facilitate the computation as a whole. As such, how to effectively allocate the resources in a single host is critical to the success of this saving strategy. To this end, we propose a multi-dimensional resource allocation algorithm, called Hestia, for a single machine in a stand-alone environment with each dimension having limited resources. The algorithm is designed by leveraging dynamic programming (DP) techniques to squeeze the occupied resources of the existing microservices without compromising their performance, and leave the saved resources for other newly deployed microservices. Our experimental results show that compared with the default case, this method can save up to 15 of the resources for a single machine while ensuring the stability of online microservices.

KeywordResource Allocation Dynamic Programming Single-machine
DOI10.1007/978-3-031-23498-9_3
URLView the original
Language英語English
Scopus ID2-s2.0-85145200530
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Document TypeConference paper
CollectionFaculty of Science and Technology
Corresponding AuthorWang, Yang
Affiliation1.Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
2.University of Chinese Academy of Sciences, Beijing, China
3.University of New Brunswick Frederiction, Fredericton, Canada
4.University of Macau, Macao
Recommended Citation
GB/T 7714
Huang, Jiahua,Kent, Kenneth B.,Yen, Jerome,et al. Hestia: A Cost-Effective Multi-dimensional Resource Utilization for Microservices Execution in the Cloud[C]. Ye K., Zhang L.-J.:Springer Science and Business Media Deutschland GmbH, 2022, 22-38.
APA Huang, Jiahua., Kent, Kenneth B.., Yen, Jerome., & Wang, Yang (2022). Hestia: A Cost-Effective Multi-dimensional Resource Utilization for Microservices Execution in the Cloud. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13731 LNCS, 22-38.
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