A review of methods for resource allocation and operational framework in cloud computing

Subject Areas : Cloud, Cluster, Grid and P2P Computing

Hadi Moei Emamqeysi ¹ , Nasim Soltani ² , Masomeh Robati ³ , Mohamad Davarpanah ⁴

1 - Department of Electrical and Computer Engineering, Foolad Institute of Technology, Fooladshahr, Isfahan , Iran
2 - Department of Software Engineering, Allame Naeini Higher Education Institute, Naein, Isfahan, Iran
3 - Department of Software Engineering Pooyesh Higher Education Institute, Qom, qom, Iran
4 - Department of Electrical and Computer Engineering, Foolad Institute of Technology, Fooladshahr, Isfahan , Iran

Received: 2017-03-12 Accepted : 2017-09-03 Published : 2017-08-01

Keywords: Resource Allocation, virtualization, virtual machine migration, cloud computing, resource management,

Abstract :

The issue of management and allocation of resources in cloud computing environments, according to the breadth of scale and modern technology implementation, is a complicated issue. Issues such as: the heterogeneity of resources, resource dependencies to each other, the dynamics of the environment, virtualization, workload diversity as well as a wide range of management objectives of cloud service providers to provide services in this environment. In this paper, first, the description of cloud computing environment and related issues have been reported. According to the performed studies, challenges such as: the absence of a comprehensive management for resources in the cloud environment, the method of predicting the resource allocation process, optimum resource allocation methods to reduce energy consumption and reducing the time to access resources and also implementation of dynamic resources allocation methods in the mobile cloud environments, have been addressed. Finally, with regard to the challenges, some recommendations to improve the process of allocation of resources in a cloud computing environment is has been proposed.

References:

[1] Q. Zhang, L. Cheng, and R. Boutaba, "Cloud computing: state-of-the-art and research challenges," Journal of internet services and applications, vol. 1, pp. 7-18, 2010.
[2] S. Taherian Dehkordi and V. Khatibi Bardsiri, "Optimization Task Scheduling Algorithm in Cloud Computing," Journal of Advances in Computer Engineering and Technology, vol. 1, pp. 17-22, 2015.
[3] Z. Chen and J. Yoon, "IT auditing to assure a secure cloud computing," in Services (SERVICES-1), 2010 6th World Congress on, 2010, pp. 253-259.
[4] K. Bakshi, "Cisco cloud computing-Data center strategy, architecture, and solutions," CISCO White Paper. Retrieved October, vol. 13, p. 2010, 2009.
[5] S. Ray and A. De Sarkar, "Execution analysis of load balancing algorithms in cloud computing environment," International Journal on Cloud Computing: Services and Architecture (IJCCSA), vol. 2, pp. 1-13, 2012.
[6] V. Yarmolenko, R. Sakellariou, D. Ouelhadj, and J. M. Garibaldi, "SLA based job scheduling: A case study on policies for negotiation with resources," in Proceedings of e-Science All Hands Meeting (AHM2005), 2005, pp. 20-22.
[7] R. Buyya, C. S. Yeo, S. Venugopal, J. Broberg, and I. Brandic, "Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility," Future Generation computer systems, vol. 25, pp. 599-616, 2009.
[8] B. B. Nasim Soltani, Behzad Soleimani Neysiani, "Job Scheduling based on Single and Multi Objective Meta- Heuristic Algorithms in Cloud Computing: A Survey," Conference: International Conference on Information Technology, Communications and Telecommunications (IRICT), , vol. 2, March 2016.
[9] V. Vinothina and R. Sridaran, "A survey on resource allocation strategies in cloud computing," International Journal of Advanced Computer Science & Applications, vol. 1, pp. 97-104, 2012.
[10] M. Al-Fares, A. Loukissas, and A. Vahdat, "A scalable, commodity data center network architecture," in ACM SIGCOMM Computer Communication Review, 2008, pp. 63-74.
[11] I. Robinson, J. Webber, and E. Eifrem, Graph databases: new opportunities for connected data: " O'Reilly Media, Inc.", 2015.
[12] J. Hamilton, "Cooperative expendable micro-slice servers (CEMS): low cost, low power servers for internet-scale services," in Conference on Innovative Data Systems Research (CIDR’09)(January 2009), 2009.
[13] S. Abirami and S. Ramanathan, "Linear scheduling strategy for resource allocation in cloud environment," International Journal on Cloud Computing: Services and Architecture (IJCCSA), vol. 2, pp. 9-17, 2012.
[14] R. Madhumathi, R. Radhakrishnan, and A. Balagopalan, "Dynamic resource allocation in cloud using bin-packing technique," in Advanced Computing and Communication Systems, 2015 International Conference on, 2015, pp. 1-4.
[15] W. Ju-Hua, "Research of Resource Allocation in Cloud Computing Based on Improved Dual Bee Colony Algorithm," International Journal of Grid and Distributed Computing, vol. 8, pp. 117-126, 2015.
[16] Z. Xiao, W. Song, and Q. Chen, "Dynamic resource allocation using virtual machines for cloud computing environment," IEEE transactions on parallel and distributed systems, vol. 24, pp. 1107-1117, 2013.
[17] S. Parida and S. C. Nayak, "Emperical Resource Allocation Using Dynamic Distributed Allocation Policy in Cloud Computing."
[18] G. K. Shyam and S. S. Manvi, "Resource allocation in cloud computing using agents," in Advance Computing Conference (IACC), 2015 IEEE International, 2015, pp. 458-463.
[19] G. Portaluri, S. Giordano, D. Kliazovich, and B. Dorronsoro, "A power efficient genetic algorithm for resource allocation in cloud computing data centers," in Cloud Networking (CloudNet), 2014 IEEE 3rd International Conference on, 2014, pp. 58-63.
[20] R. Madhumathi, R. Radhakrishnan, and A. S. Balagopalan, "Dynamic Resource Allocation in Cloud Using Bin-Packing Technique," 2015 International Conference on Advanced Computing and Communication Systems, 2015.
[21] Ronak Patel and S. Patel, "Survey on Resource Allocation Strategies in Cloud Computing," International Journal of Engineering Research & Technology (IJERT), vol. 2, 2013.
[22] Abirami S and S. Ramanathan, "Linear Scheduling Strategy for Resource Allocation in Cloud Environment," International Journal on Cloud Computing: Services and Architecture(IJCCSA), vol. 12, 2012.
[23] Anand Prabu P, Dhanasekar P, and S. S. G, "Dynamic Resource Allocation Using Nephele Framework in Cloud," International Journal of Innovative Research in Computer and Communication Engineering, vol. 2, 2014.
[24] Aman Kumar and E. S, "An Efficient Framework for Resource Allocation in Cloud Computing," 4th ICCCNT 2013, 2013.
[25] Gopal Kirshna Shyam, SunilKumar, and S. Manvi, "Resource Allocation in Cloud Computing Using Agents," 2015 IEEE International Advance Computing Conference (IACC), 2015.
[26] Siva Theja Maguluri , R. Srikant , and L. Ying, "Heavy traffic optimal resource allocation algorithms for cloud computing clusters," journal homepage: www.elsevier.com/locate/peva, 2014.
[27] Dilip Kumar and B. Sahoo, "Energy Efficient Heuristic Resource Allocation for Cloud Computing," Computer Science & Engineering, National Institute of Technology, 2014.
[28] Mansoor Alicherry and T. V. Lakshman, "Net work Aware Resource Allocation in Distributed Clouds," Proceedings IEEE INFOCOM, 2012.
[29] Mina Sedaghat, Francisco Hernández-Rodriguez, and E. Elmroth, "Autonomic Resource Allocation for Cloud Data Centers: A Peer to Peer Approach," 2014 IEEE International Conference on Cloud and Autonomic Computing, 2014.
[30] Giuseppe Portaluri, Stefano Giordano, Dzmitry Kliazovich, and B. e. Dorronsoro. (2014, A Power Efficient Genetic Algorithm for Resource Allocation in Cloud Computing Data Centers. 2014 IEEE 3rd International Conference on Cloud Networking (CloudNet).
[31] W. ju-Hu, "Research of Resource Allocation in Cloud Computing Based on Improved Dual Bee Colony Algorithm," International Journal of Grid Distribution Computing, 2015.
[32] Wanneng Shu, W. Wang, and Y. Wang, "A novel energy-efficient resource allocation algorithm based on immune clonal optimization for green cloud computing," Shu et al. EURASIP Journal on Wireless Communications and Networking 2014, 2014.