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Improving Load Balancing for Modern Data Centers Through Resource Equivalence Classes

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Service-Oriented Computing (ICSOC 2021)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 13121))

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Abstract

Load balancing is one of the most significant concerns for data center (DC) management, and the basic method is reassigning applications from overloaded servers to underloaded servers. However, to ensure the service availability, during the reassignment of an application, some resources (i.e., transient resources) are consumed simultaneously on its initial server and its target server, which imposes a challenge for load balancing. The latest research has proposed a concept called resource equivalence class (REC: a set of resource configurations such that a latency-critical (LC) application running with any one of them can meet the QoS target). In this paper, we use the REC to improve the load balancing for a DC where multiple LC applications have already been co-located on servers with the service availability and QoS requirements. We formulate the proposed load rebalancing problem as a multi-objective constrained programming model. To solve the proposed problem, we propose to use a machine learning-based classification model to construct the RECs for applications, and we develop a local search (LS) algorithm to approximate the optimal solution. We evaluate the proposed algorithm via simulated experiments using real LC applications. To our knowledge, it is the first time to use REC for improving load balancing.

This work is supported by State Key Lab of Computer Architecture, ICT, CAS, under Grant No. CARCHB202013; NSFC (U1833114, 61872201); Science and Technology Development Plan of Tianjin (18ZXZNGX00140, 18ZXZNGX00200, 20JCZDJC00610).

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Notes

  1. 1.

    https://github.com/harisgavranovic/roadef-challenge2012-S41.

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Authors and Affiliations

  1. College of CS, Nankai University, Tianjin, China

    Kaiyue Duan, Yusen Li, Gang Wang & Xiaoguang Liu

  2. Department of Mathematics, Ryerson University, Toronto, Canada

    Trent G. Marbach

Authors
  1. Kaiyue Duan
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  2. Yusen Li
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  3. Trent G. Marbach
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  4. Gang Wang
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  5. Xiaoguang Liu
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Corresponding author

Correspondence to Yusen Li .

Editor information

Editors and Affiliations

  1. Zayed University, Dubai, United Arab Emirates

    Hakim Hacid

  2. Technical University of Berlin, Berlin, Germany

    Odej Kao

  3. Informatica Automatica Gestio, Sapienza University of Rome, Rome, Italy

    Massimo Mecella

  4. Departement d'Informatique, University of Quebec, Montreal, QC, Canada

    Naouel Moha

  5. UNSW Sydney, Sydney, NSW, Australia

    Hye-young Paik

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Duan, K., Li, Y., Marbach, T.G., Wang, G., Liu, X. (2021). Improving Load Balancing for Modern Data Centers Through Resource Equivalence Classes. In: Hacid, H., Kao, O., Mecella, M., Moha, N., Paik, Hy. (eds) Service-Oriented Computing. ICSOC 2021. Lecture Notes in Computer Science(), vol 13121. Springer, Cham. https://doi.org/10.1007/978-3-030-91431-8_34

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  • DOI: https://doi.org/10.1007/978-3-030-91431-8_34

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  • Print ISBN: 978-3-030-91430-1

  • Online ISBN: 978-3-030-91431-8

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