• DocumentCode
    2445703
  • Title

    A Hybrid and Secure Mechanism to Execute Parameter Survey Applications on Local and Public Cloud Resources

  • Author

    Sun, Hao ; Aida, Kento

  • Author_Institution
    Dept. of Inf. Process., Tokyo Inst. of Technol., Yokohama, Japan
  • fYear
    2010
  • fDate
    Nov. 30 2010-Dec. 3 2010
  • Firstpage
    118
  • Lastpage
    126
  • Abstract
    A parameter survey application (PSA) is a typical application running on high-performance computing (HPC) systems. A PSA consists of a lot of independent tasks with different input parameters that are executed in parallel on different CPU cores. Infrastructure-as-a-Service Cloud (IaaS Cloud) is expected to be used as an HPC infrastructure to run PSAs, and some reports have discussed hybrid execution mechanisms to utilize both local resources and IaaS Clouds. However, users still have security problems in running applications with confidential data on an IaaS Cloud. We propose a hybrid and secure execution mechanism to run PSAs utilizing both local computing resources with a batch scheduler and an IaaS Cloud. The proposed mechanism utilizes both local resources and IaaS Clouds to meet the deadline of user applications. We conducted experiments running a natural language processing application, which uses machine learning to detect abusive language on Internet bulletin board systems. The experimental results showed that the proposed mechanism effectively allocated resources and met the deadlines of the user application.
  • Keywords
    cloud computing; learning (artificial intelligence); multiprocessing systems; natural language processing; parallel machines; security of data; CPU core; HPC system; IaaS cloud; Internet bulletin board system; PSA; abusive language detection; batch scheduler; data confidentiality; high-performance computing; infrastructure-as-a-service cloud; machine learning; natural language processing; parallel execution; parameter survey application; public cloud resource; secure execution; Cloud computing; Logic gates; Scheduling algorithm; Security; Support vector machines; Training data; Virtual private networks; Grid and Cloud; hybrid execution mechanism; scheduling middleware;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cloud Computing Technology and Science (CloudCom), 2010 IEEE Second International Conference on
  • Conference_Location
    Indianapolis, IN
  • Print_ISBN
    978-1-4244-9405-7
  • Electronic_ISBN
    978-0-7695-4302-4
  • Type

    conf

  • DOI
    10.1109/CloudCom.2010.61
  • Filename
    5708442