• DocumentCode
    14084
  • Title

    Cross-Layer Cloud Resource Configuration Selection in the Big Data Era

  • Author

    Ranjan, Rajiv ; Kolodziej, Joanna ; Lizhe Wang ; Zomaya, Albert Y.

  • Volume
    2
  • Issue
    3
  • fYear
    2015
  • fDate
    May-June 2015
  • Firstpage
    16
  • Lastpage
    22
  • Abstract
    Cloud computing has transformed people´s perception of how Internet-based applications can be deployed in datacenters and offered to users in a pay-as-you-go model. Despite the growing adoption of cloud datacenters, challenges related to big data application management still exist. One important research challenge is selecting configurations of resources as infrastructure-as-a-service (IaaS) and platform-as-a-service (PaaS) layers such that big data application-specific service-level agreement goals (such as minimizing event-detection and decision-making delays, maximizing application and data availability, and maximizing the number of alerts sent per second) are constantly achieved for big data applications. This article discusses the issue of selecting resource configurations across multiple layers of a cloud computing stack by considering deployment of a real-time stock recommendation big data application over an Amazon Web Services public datacenter.
  • Keywords
    Big Data; Web services; cloud computing; recommender systems; resource allocation; Amazon Web Services public data center; Big Data application management; Big Data era; IaaS; Internet-based applications; PaaS; cloud computing; cross-layer cloud resource configuration selection; data centers; infrastructure-as-a-service; pay-as-you-go model; platform-as-a-service; realtime stock recommendation; service-level agreement; Big data; Cloud computing; Hardware; Internet; Linear programming; Servers; Throughput; big data; cloud; cloud services; datacenter; infrastructure as a service; platform as a service; service-level agreements;
  • fLanguage
    English
  • Journal_Title
    Cloud Computing, IEEE
  • Publisher
    ieee
  • ISSN
    2325-6095
  • Type

    jour

  • DOI
    10.1109/MCC.2015.64
  • Filename
    7158976