A fuzzy-based auto-scaler for web applications in cloud computing environments

Bingfeng Liu, Rajkumar Buyya, Adel Nadjaran Toosi

    Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

    Abstract

    Cloud computing provided the elasticity for its users allowing them to add or remove virtual machines depending on the load of their web applications. However, there is still no ideal auto-scaler which is both easy to use and sufficiently accurate to make web applications resilient under the dynamic load. The threshold-based auto-scaling approaches are among the most popular reactive auto-scaling strategies due to their high learnability and usability. However, the static threshold would become undesirable once the workload becomes highly dynamic and unpredictable. In this paper, we propose a novel fuzzy logic based approach that automatically and adaptively adjusts thresholds and cluster size for a web application. The proposed auto-scaler aims at reducing resource consumption without violation of Service Level Agreement (SLA). The performance evaluation is conducted with the real-life Wikipedia traces in the Amazon Web Services cloud platform. Experimental results demonstrate that our reactive auto-scaler efficiently reduces cloud resources usage and minimizes the SLA violations.

    Original languageEnglish
    Title of host publicationService-Oriented Computing
    Subtitle of host publication16th International Conference, ICSOC 2018 Hangzhou, China, November 12–15, 2018 Proceedings
    EditorsClaus Pahl, Maja Vukovic, Jianwei Yin, Qi Yu
    Place of PublicationCham Switzerland
    PublisherSpringer
    Pages797-811
    Number of pages15
    ISBN (Electronic)9783030035969
    ISBN (Print)9783030035952
    DOIs
    Publication statusPublished - 2018
    EventInternational Conference on Service Oriented Computing 2018 - Hangzhou, China
    Duration: 12 Nov 201815 Nov 2018
    Conference number: 16th
    https://waset.org/conference/2018/01/singapore/ICSOC

    Publication series

    NameLecture Notes in Computer Science
    PublisherSpringer
    Volume11236
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    ConferenceInternational Conference on Service Oriented Computing 2018
    Abbreviated titleICSOC 2018
    CountryChina
    CityHangzhou
    Period12/11/1815/11/18
    Internet address

    Cite this

    Liu, B., Buyya, R., & Nadjaran Toosi, A. (2018). A fuzzy-based auto-scaler for web applications in cloud computing environments. In C. Pahl, M. Vukovic, J. Yin, & Q. Yu (Eds.), Service-Oriented Computing: 16th International Conference, ICSOC 2018 Hangzhou, China, November 12–15, 2018 Proceedings (pp. 797-811). (Lecture Notes in Computer Science; Vol. 11236 ). Cham Switzerland: Springer. https://doi.org/10.1007/978-3-030-03596-9_57
    Liu, Bingfeng ; Buyya, Rajkumar ; Nadjaran Toosi, Adel. / A fuzzy-based auto-scaler for web applications in cloud computing environments. Service-Oriented Computing: 16th International Conference, ICSOC 2018 Hangzhou, China, November 12–15, 2018 Proceedings. editor / Claus Pahl ; Maja Vukovic ; Jianwei Yin ; Qi Yu. Cham Switzerland : Springer, 2018. pp. 797-811 (Lecture Notes in Computer Science).
    @inproceedings{7222c9673b4b49fcb91061a0a3bf4ff5,
    title = "A fuzzy-based auto-scaler for web applications in cloud computing environments",
    abstract = "Cloud computing provided the elasticity for its users allowing them to add or remove virtual machines depending on the load of their web applications. However, there is still no ideal auto-scaler which is both easy to use and sufficiently accurate to make web applications resilient under the dynamic load. The threshold-based auto-scaling approaches are among the most popular reactive auto-scaling strategies due to their high learnability and usability. However, the static threshold would become undesirable once the workload becomes highly dynamic and unpredictable. In this paper, we propose a novel fuzzy logic based approach that automatically and adaptively adjusts thresholds and cluster size for a web application. The proposed auto-scaler aims at reducing resource consumption without violation of Service Level Agreement (SLA). The performance evaluation is conducted with the real-life Wikipedia traces in the Amazon Web Services cloud platform. Experimental results demonstrate that our reactive auto-scaler efficiently reduces cloud resources usage and minimizes the SLA violations.",
    author = "Bingfeng Liu and Rajkumar Buyya and {Nadjaran Toosi}, Adel",
    year = "2018",
    doi = "10.1007/978-3-030-03596-9_57",
    language = "English",
    isbn = "9783030035952",
    series = "Lecture Notes in Computer Science",
    publisher = "Springer",
    pages = "797--811",
    editor = "Claus Pahl and Maja Vukovic and Jianwei Yin and Qi Yu",
    booktitle = "Service-Oriented Computing",

    }

    Liu, B, Buyya, R & Nadjaran Toosi, A 2018, A fuzzy-based auto-scaler for web applications in cloud computing environments. in C Pahl, M Vukovic, J Yin & Q Yu (eds), Service-Oriented Computing: 16th International Conference, ICSOC 2018 Hangzhou, China, November 12–15, 2018 Proceedings. Lecture Notes in Computer Science, vol. 11236 , Springer, Cham Switzerland, pp. 797-811, International Conference on Service Oriented Computing 2018, Hangzhou, China, 12/11/18. https://doi.org/10.1007/978-3-030-03596-9_57

    A fuzzy-based auto-scaler for web applications in cloud computing environments. / Liu, Bingfeng; Buyya, Rajkumar; Nadjaran Toosi, Adel.

    Service-Oriented Computing: 16th International Conference, ICSOC 2018 Hangzhou, China, November 12–15, 2018 Proceedings. ed. / Claus Pahl; Maja Vukovic; Jianwei Yin; Qi Yu. Cham Switzerland : Springer, 2018. p. 797-811 (Lecture Notes in Computer Science; Vol. 11236 ).

    Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

    TY - GEN

    T1 - A fuzzy-based auto-scaler for web applications in cloud computing environments

    AU - Liu, Bingfeng

    AU - Buyya, Rajkumar

    AU - Nadjaran Toosi, Adel

    PY - 2018

    Y1 - 2018

    N2 - Cloud computing provided the elasticity for its users allowing them to add or remove virtual machines depending on the load of their web applications. However, there is still no ideal auto-scaler which is both easy to use and sufficiently accurate to make web applications resilient under the dynamic load. The threshold-based auto-scaling approaches are among the most popular reactive auto-scaling strategies due to their high learnability and usability. However, the static threshold would become undesirable once the workload becomes highly dynamic and unpredictable. In this paper, we propose a novel fuzzy logic based approach that automatically and adaptively adjusts thresholds and cluster size for a web application. The proposed auto-scaler aims at reducing resource consumption without violation of Service Level Agreement (SLA). The performance evaluation is conducted with the real-life Wikipedia traces in the Amazon Web Services cloud platform. Experimental results demonstrate that our reactive auto-scaler efficiently reduces cloud resources usage and minimizes the SLA violations.

    AB - Cloud computing provided the elasticity for its users allowing them to add or remove virtual machines depending on the load of their web applications. However, there is still no ideal auto-scaler which is both easy to use and sufficiently accurate to make web applications resilient under the dynamic load. The threshold-based auto-scaling approaches are among the most popular reactive auto-scaling strategies due to their high learnability and usability. However, the static threshold would become undesirable once the workload becomes highly dynamic and unpredictable. In this paper, we propose a novel fuzzy logic based approach that automatically and adaptively adjusts thresholds and cluster size for a web application. The proposed auto-scaler aims at reducing resource consumption without violation of Service Level Agreement (SLA). The performance evaluation is conducted with the real-life Wikipedia traces in the Amazon Web Services cloud platform. Experimental results demonstrate that our reactive auto-scaler efficiently reduces cloud resources usage and minimizes the SLA violations.

    UR - http://www.scopus.com/inward/record.url?scp=85056837125&partnerID=8YFLogxK

    U2 - 10.1007/978-3-030-03596-9_57

    DO - 10.1007/978-3-030-03596-9_57

    M3 - Conference Paper

    SN - 9783030035952

    T3 - Lecture Notes in Computer Science

    SP - 797

    EP - 811

    BT - Service-Oriented Computing

    A2 - Pahl, Claus

    A2 - Vukovic, Maja

    A2 - Yin, Jianwei

    A2 - Yu, Qi

    PB - Springer

    CY - Cham Switzerland

    ER -

    Liu B, Buyya R, Nadjaran Toosi A. A fuzzy-based auto-scaler for web applications in cloud computing environments. In Pahl C, Vukovic M, Yin J, Yu Q, editors, Service-Oriented Computing: 16th International Conference, ICSOC 2018 Hangzhou, China, November 12–15, 2018 Proceedings. Cham Switzerland: Springer. 2018. p. 797-811. (Lecture Notes in Computer Science). https://doi.org/10.1007/978-3-030-03596-9_57