Advertisement

Resource Allocation in Cooperative Cloud Environments

  • Himansu Das
  • Ajay Kumar Jena
  • J. Chandrakant Badajena
  • Chittaranjan Pradhan
  • R. K. Barik
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 710)

Abstract

In cloud computing environment, cloud application services and resources belong to different virtual organizations with different objectives. Each component of cloud environment is self-governing and self-interested. They share their resources and services to achieve their objectives. The cloud computing environment provides infinite number of computing resources such as CPU, memory and storage to the users in such a way that they can dynamically increase or decrease their resources and its use according to their demands. In resource allocation model having two basic objectives as cloud provider wants to maximize their revenue by achieving high resource utilization while cloud users want to minimize their expenses while meeting their requirements. However, it is essential to allocate resources in an optimized way between two parties. In some situations, single cloud may not satisfy all the requirements of the users. To achieve this objective, two or more cloud providers cooperatively work together to satisfy the user’s requirements. These cooperative cloud providers should share and optimize the computational resources in a reasonable technique to make sure that no users get much resource than any other users and also improve the resource utilization.

Keywords

Cloud computing Resource allocation Cooperative Utilization bound 

References

  1. 1.
    R Buyya, CS Yeo, S Venugopal, J Broberg, I Brandic, “Cloud computing and emerging IT platforms: vision, hype, and reality for delivering computing as the 5th utility” Futur. Gener. Comput. Syst. 25(6), 599–616 (2009).Google Scholar
  2. 2.
    I. Foster, Y. Zhao, I. Raicu, and S. Lu. Cloud computing and grid computing 360-degree compared, In Proceedings of Grid Computing Environments Workshop, pages 1–10, 2008.Google Scholar
  3. 3.
    Xu, Xin, and Huiqun Yu. “A game theory approach to fair and efficient resource allocation in cloud computing.” Mathematical Problems in Engineering 2014 (2014).Google Scholar
  4. 4.
    Endo, Patricia Takako, Andre Vitor de Almeida Palhares, Nadilma Nunes Pereira, Glauco Estacio Goncalves, Djamel Sadok, Judith Kelner, Bob Melander, and Jan-Erik Mangs. “Resource allocation for distributed cloud: concepts and research challenges.” IEEE network 25, no. 4 (2011).Google Scholar
  5. 5.
    Sarkhel, Preeta, Himansu Das, and Lalit K. Vashishtha. “Task-Scheduling Algorithms in Cloud Environment.” In Computational Intelligence in Data Mining, pp. 553–562. Springer, Singapore, 2017.Google Scholar
  6. 6.
    Huang, Chenn-Jung, Chih-Tai Guan, Heng-Ming Chen, Yu-Wu Wang, Shun-Chih Chang, Ching-Yu Li, and Chuan-Hsiang Weng. “An adaptive resource management scheme in cloud computing.” Engineering Applications of Artificial Intelligence 26, no. 1 (2013): 382–389.Google Scholar
  7. 7.
    Tsai, Jinn-Tsong, Jia-Cen Fang, and Jyh-Horng Chou. “Optimized task scheduling and resource allocation on cloud computing environment using improved differential evolution algorithm.” Computers & Operations Research 40, no. 12 (2013): 3045–3055.Google Scholar
  8. 8.
    Kar, Ipsita, RN Ramakant Parida, and Himansu Das. “Energy aware scheduling using genetic algorithm in cloud data centers.” In Electrical, Electronics, and Optimization Techniques (ICEEOT), International Conference on, pp. 3545–3550. IEEE, 2016.Google Scholar
  9. 9.
    Pillai, Parvathy S., and Shrisha Rao. “Resource allocation in cloud computing using the uncertainty principle of game theory.” IEEE Systems Journal 10, no. 2 (2016): 637–648.Google Scholar
  10. 10.
    Hassan, Mohammad Mehedi, M. Shamim Hossain, AM Jehad Sarkar, and Eui-Nam Huh. “Cooperative game-based distributed resource allocation in horizontal dynamic cloud federation platform.” Information Systems Frontiers 16, no. 4 (2014): 523–542.Google Scholar
  11. 11.
    Wei, Guiyi, Athanasios V. Vasilakos, Yao Zheng, and Naixue Xiong. “A game-theoretic method of fair resource allocation for cloud computing services.” The journal of supercomputing 54, no. 2 (2010): 252–269.Google Scholar
  12. 12.
    Das, Himansu, Gouri Sankar Panda, Bhagaban Muduli, and Pradeep Kumar Rath. “The complex network analysis of power grid: a case study of the West Bengal power network.” In Intelligent Computing, Networking, and Informatics, pp. 17–29. Springer, New Delhi, 2014.Google Scholar
  13. 13.
    Das, Himansu, Sanjay Kumar Mishra, and Diptendu Sinha Roy. “The topological structure of the Odisha power grid: a complex network analysis.” IJMCA 1, no. 1 (2013): 012–016.Google Scholar
  14. 14.
    Das, Himansu, and D. S. Roy. “A grid computing service for power system monitoring.” International Journal of Computer Applications 62, no. 20 (2013).Google Scholar
  15. 15.
    Das, Himansu, A. K. Jena, P. K. Rath, B. Muduli, and S. R. Das. “Grid computing-based performance analysis of power system: a graph theoretic approach.” In Intelligent Computing, Communication and Devices, pp. 259–266. Springer, New Delhi, 2015.Google Scholar
  16. 16.
    Panigrahi, Chhabi Rani, Mayank Tiwary, Bibudhendu Pati, and Himansu Das. “Big Data and Cyber Foraging: Future Scope and Challenges.” In Techniques and Environments for Big Data Analysis, pp. 75–100. Springer International Publishing, 2016.Google Scholar
  17. 17.
    KHK Reddy, Himansu Das, D S Roy, “A Data Aware Scheme for Scheduling Big-Data Applications with SAVANNA Hadoop”, in Futures of Network, CRC Press, 2017.Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Himansu Das
    • 1
  • Ajay Kumar Jena
    • 1
  • J. Chandrakant Badajena
    • 2
  • Chittaranjan Pradhan
    • 1
  • R. K. Barik
    • 3
  1. 1.School of Computer EngineeringKIIT Deemed to be UniversityBhubaneswarIndia
  2. 2.Department of Information TechnologyCollege of Engineering & TechnologyBhubaneswarIndia
  3. 3.School of Computer ApplicationKIIT Deemed to be UniversityBhubaneswarIndia

Personalised recommendations