• DocumentCode
    3717146
  • Title

    ATOM: Automated tracking, orchestration and monitoring of resource usage in infrastructure as a service systems

  • Author

    Min Du;Feifei Li

  • Author_Institution
    School of Computing, University of Utah
  • fYear
    2015
  • Firstpage
    271
  • Lastpage
    278
  • Abstract
    We present ATOM, an efficient and effective framework to enable automated tracking, monitoring, and orchestration of resource usage in an Infrastructure as a Service (IaaS) system. We design a novel tracking method to continuously track important performance metrics with low overhead, and develop a principal component analysis (PCA) based approach with quality guarantees to continuously monitor and automatically find anomalies based on the approximate tracking results. Lastly, when potential anomalies are identified, we use introspection tools to perform memory forensics on virtual machines (VMs) to identify malicious behavior inside a VM. We deploy ATOM in an IaaS system to monitor VM resource usage, and to detect anomalies. Various attacks are used as examples to demonstrate how ATOM is both effective and efficient to track and monitor resource usage, detect anomalies, and orchestrate system resource usage.
  • Keywords
    "Monitoring","Cloud computing","Principal component analysis","Observers","Atomic measurements","Algorithm design and analysis"
  • Publisher
    ieee
  • Conference_Titel
    Big Data (Big Data), 2015 IEEE International Conference on
  • Type

    conf

  • DOI
    10.1109/BigData.2015.7363764
  • Filename
    7363764