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Deadline-based Priority Management in Cloud

  • E. Iniya Nehru
  • Saswati Mukherjee
  • Abhishek Kumar
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 325)

Abstract

In cloud computing, the word “cloud” is used as metaphor for “the Internet,” so the phrase cloud computing means “a type of Internet-based computing” where different services such as servers, storage, and applications are delivered to an organization’s computer and devices through the Internet. Today, cloud computing is on demand that means cloud providers provide their services in pay-as-you-manner. So, there must be a provision that all resources are made available to requesting users in efficient manner to satisfy their needs. Since this resource allocation schemes offered by cloud computing, effective scheduling algorithms are important to utilize these benefits. There are many scheduling algorithms such as task grouping, priority aware, and SJF (shortest job first) to reduce the waiting time and maximize the resource allocation. In this paper, a new algorithm has been proposed namely deadline–first scheduling algorithm, which considers deadline as a crucial factor. Deadline is a major concept in negotiation of SLA in cloud computing to prevent penalties.

Keywords

Cloud Computing Schedule Algorithm Cloud Provider Average Waiting Time Dynamic Resource Allocation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    S. Selevarani, G. Sadhasivam, Improved cost-based algorithm for task scheduling in cloud computing, in Computational Intelligence and Computing Research (ICCIC), IEEE International Conference (2010)Google Scholar
  2. 2.
    J. Ru, J. Keung, An Empirical investigation on the simulation of priority and shortest-job-first scheduling for cloud-based software systems, in 22nd Australian Conference on Software Engineering (2013)Google Scholar
  3. 3.
    S. Sivanandam, S. Deepa, Introduction to Genetic Algorithms (Springer Publishing Company, Incorporated, Berlin, 2007)Google Scholar
  4. 4.
    A. Silberschatz, P. Galvin, G. Gagne, A. Silberschatz, Operating System Concepts. (Addison-Wesley, Boston, 1998), p. 4Google Scholar
  5. 5.
    X. Li, N. Ye, T. Liu, Y. Sun, Job scheduling to minimize the weighted waiting time variance of jobs. Comput. Ind. Eng. 52(1), 41–56 (2007)CrossRefGoogle Scholar
  6. 6.
    R.N. Calheiros, R. Ranjan, A. Beloglazov, C.A. De Rose, R. Buyya, CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms (2010)Google Scholar
  7. 7.
    P.G.J. Leelipushpam, J. Sharmila, Live VM Migration techniques in cloud environment—a survey, in Information & Communication Technologies (ICT) (2013)Google Scholar

Copyright information

© Springer India 2015

Authors and Affiliations

  • E. Iniya Nehru
    • 1
  • Saswati Mukherjee
    • 2
  • Abhishek Kumar
    • 3
  1. 1.National Informatics CentreChennaiIndia
  2. 2.College of EngineeringAnna UniversityChennaiIndia
  3. 3.Master of Computer Applications DepartmentPondicherry UniversityKalapetIndia

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