Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Call For Paper : Vol 11, Issue 03, March 2024

Call for Paper

Vol 11, Issue 03, March 2024

Indexing

Resource Provision and Allocation Algorithms In Cloud Computing: A Survey

Author : Kalaiyarasi N 1 Dr.Madhumathi R 2

PDF

Date of Publication :24th January 2018

Abstract: Cloud computing is an on-demand service resource which includes applications to data centers on a pay-per-use basis. In order to provide and allocate these resources properly and satisfy users’ demands, an efficient and flexible resource allocation mechanism is needed. Due to increasing user demand, the resource provider and allocating process has become more challenging and difficult. One of the main focuses of research scholars is how to develop optimal solutions for this process. In this paper, a survey on resource provision and allocation algorithms is discussed.

Reference :

    1. Samah Alnajdi, Maram Dogan, Ebtesam Al-Qahtani “A Survey of Resource Allocation in Cloud Computing”, Science Direct, vol. 6, No. 5, 2016.
    2. Siva Theja Maguluri , R. Srikant, Lei Ying, “Heavy traffic optimal resource allocation algorithms for cloud Computing clusters”, Science Direct, vol. 81, pp. 20–39, 2014.
    3. B. Magesh Kumar, C. Ramesh, “Vibrant Resource Allocation Algorithms using Virtual Machine in CloudSurvey”, Science Direct, vol.2, Special Issue 1, 2014.
    4. Pandaba Pradhan, Prafulla Ku. Behera, B N B Ray, ”Modified Round Robin Algorithm for Resource Allocation In Cloud Computing”, Science Direct, vol85, pp. 878 – 890, 2016.
    5. M. Miller, “Cloud Computing: Web-based applications that change the way you work and collaborate online”, Que, 2008.
    6. R.Rajkumar, C.Lee, J.P.Lehoczky, and D.P.Siewiorek, “Practical solutions for QoS-based resource allocation problems”. In IEEE Real-Time, 2015.
    7. Aman kumar, Emmanueel S.Pilli and R.C.Jshi,” An efficient framework for resource allocation in cloud computing”, in IEEE 4th ICCCNT, 2013.
    8. Chenn-Jung Huang, Chih-TaiGuan, Heng- MingChen, Yu-WuWang,Shun-ChihChang, Ching-Yu Li and Chuan HsiangWeng, “An Adaptive Resourc ManagementSchemeinCloud Computing”, vol. 26, pp. 382- 389, Science Direct, 2016 .
    9. X. Z. Hai Zhong, Kun Tao, “An approach to optimized resource scheduling algorithm for open-source cloud systems,” The Fifth Annual China Grid Conference, 2010.
    10. M. c. D. Pandit and N. Chaki, “Resource allocation in cloud computing using simulated annealing,” IEEE applications and innovations in mobile computing, 2014.
    11. E. G. Coffman, M. R. Garey, and D. S. Johnson, “Approximation algorithms for bin packing: A survey, Approximation algorithms” PWS Publishing Company 2014.
    12. K.A. Dowsland, Simulated Annealing. In Modern Heuristic Techniques for Combinatorial Problems (ed. Reeves, C.R.), McGraw-Hill, 2015.
    13. R. E. J. Kennedy, “Particle swarm optimization (pso),” vol. 96, pp. 121, IEEE International conference on Neural Networks, 2011.
    14. K. G. Thamarai Selvi Somasundaram, “Cloudrb: A framework for scheduling and managing high-performance computing (hpc) applications in science cloud,” Future Generation Computer Systems, vol. 34, pp. 47–65, 2014.
    15. Chandrashekar S.Pawar and Rajnikant B.Wagh,“PriorityBasedDynamic Resource Allocation in Cloud Computing, International Symposium on Cloud and Services Computing, pp. 1-6, 2014.
    16. Jiayin Li, Meikang Qiu, Jian-Wei Niu, Yu Chen, Zhong Ming, “Adaptive Resource Allocation for Preemptable Jobs in Cloud Systems”, pp. 31-36, 10th International Conference on Intelligent System Design and Application, 2015.
    17. Q. Bai, “Analysis of particle swarm optimization algorithm,” vol. 3, Computer and Information Science, 2015.

Recent Article