• DocumentCode
    3562863
  • Title

    Algorithmic approach to deadlock detection for resource allocation in heterogeneous platforms

  • Author

    Ha Huy Cuong Nguyen ; Van Son Le ; Thanh Thuy Nguyen

  • Author_Institution
    Dept. of Inf. Technol., Quang Nam Univ., Quang Nam, Vietnam
  • fYear
    2014
  • Firstpage
    97
  • Lastpage
    103
  • Abstract
    An allocation of resources to a virtual machine specifies the maximum amount of each individual element of each resource type that will be utilized, as well as the aggregate amount of each resource of each type. An allocation is thus represented by two vectors, a maximum elementary allocation vector and an aggregate allocation vector. There are more general types of resource allocation problems than those we consider here. In this paper, we present an approach for improving parallel deadlock detection algorithm, to schedule the policies of resource which supply for resource allocation in heterogeneous distributed platform. Parallel deadlock detection algorithm has a run time complexity of O(min(m,n)), where m is the number of resources and n is the number of processes. We propose the algorithm for allocating multiple resources to competing services running in virtual machines on a heterogeneous distributed platform. The experiments also compare the performance of the proposed approach with other related work.
  • Keywords
    cloud computing; computational complexity; concurrency control; parallel algorithms; resource allocation; virtual machines; algorithmic approach; heterogeneous distributed platform; maximum elementary allocation vector; parallel deadlock detection algorithm; resource allocation; run time complexity; virtual machine; Aggregates; Detection algorithms; Random access memory; Resource management; System recovery; Vectors; Virtual machining; Cloud computing; Deadlock detection; Heterogeneous Platforms; Resource allocation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Smart Computing (SMARTCOMP), 2014 International Conference on
  • Print_ISBN
    978-1-4799-5710-1
  • Type

    conf

  • DOI
    10.1109/SMARTCOMP.2014.7043845
  • Filename
    7043845