• DocumentCode
    2431128
  • Title

    Resource Allocation Techniques in Cloud Computing -- Research Challenges for Applications

  • Author

    Mohan, N.R.R. ; Raj, E.B.

  • Author_Institution
    Comput. & Inf. Tech., Manonmaniam Sundaranar Univ., Tirunelveli, India
  • fYear
    2012
  • fDate
    3-5 Nov. 2012
  • Firstpage
    556
  • Lastpage
    560
  • Abstract
    The computational humanity is flattering extremely bulky and multifaceted. Cloud computing is becoming one of the most expanding methodologies in the computing industry. It is a novel approach for the deliverance of IT services on the World Wide Web. This model provides computing resources in the puddle for consumers, all the way through Internet. In cloud computing, resource allocation and scheduling of numerous aggregate web services is an imperative and demanding quandary. This paper estimates the various network resource allocation strategies and their applications in Cloud Computing Environment. A brief description for network resource allocation in Cloud Computing, based on differentially adapted dynamic proportions, has also been done. This paper addresses and categorizes the foremost challenges normal to the resource allocation progress of cloud computing in terms of diverse types of resource allocation techniques.
  • Keywords
    Web services; cloud computing; resource allocation; scheduling; IT service; Internet; Web service scheduling; World Wide Web; cloud computing environment; computing industry; computing resource; differentially adapted dynamic proportion; network resource allocation strategy; resource allocation technique; Bandwidth; Cloud computing; Processor scheduling; Quality of service; Resource management; Scheduling; Servers; cloud computing; distributed computing; resource allocation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Communication Networks (CICN), 2012 Fourth International Conference on
  • Conference_Location
    Mathura
  • Print_ISBN
    978-1-4673-2981-1
  • Type

    conf

  • DOI
    10.1109/CICN.2012.177
  • Filename
    6375175