Resource Allocation Strategy with Lease Policy and Dynamic Load Balancing

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Pooja S. Kshirsagar 1,* Anita M. Pujar 1

1. CSE dept., Walchand Institute of Technology, Solapur, 413006, India

* Corresponding author.


Received: 20 Oct. 2016 / Revised: 15 Nov. 2016 / Accepted: 8 Dec. 2016 / Published: 8 Feb. 2017

Index Terms

Cloud computing, ACWN, haizea, load balancing, VM scheduling


Cloud Computing has managed to attract the entire buzz in the growing era of technology due to its on-demand services for resource request. Despite of the enormous growth of cloud computing, there are many problems related to resource allocation in cloud that are still unaddressed. Current work for resource allocation strategy focuses on various methods to place Virtual Machine per appropriate requests. The current state of art focuses on the dynamic nature of the work load on cloud. But there is still scope of improvement in the resource allocation strategies that have been proposed in terms of well-balanced network even at the resource contention.
This study proposes a hybrid model composed of lease methodology and dynamic load balancing algorithm, with an attempt to overcome the problems of resource contention and starvation and a well-balanced network even at the input of varying loads. An attempt to increase the CPU utilization and throughput along with no request rejection is taken. The work also retains the lease options for its clients thus maintaining the anti-starvation for pre-emptible requests.

Cite This Paper

Pooja S. Kshirsagar, Anita M. Pujar, "Resource Allocation Strategy with Lease Policy and Dynamic Load Balancing", International Journal of Modern Education and Computer Science(IJMECS), Vol.9, No.2, pp.27-33, 2017. DOI:10.5815/ijmecs.2017.02.03


[1]Kurdi, Heba, Ebtesam Aloboud, Sarah Alhassan, and Ebtehal T. Alotaibi. "An Algorithm for Handling Starvation and Resource Rejection in Public Clouds." Elsevier publication, The 9th International Conference on Future Networks and Communications Procedia Computer Science 34 (2014): 242-48.
[2]V.vinothina, V., Dr. R. sridaran, and Dr. padmavathi Ganapathi. "A Survey on Resource Allocation Strategies in Cloud Computing." International Journal of Advanced Computer Science and Applications IJACSA 3.6 (2012)
[3]Abdullah Yousafzai1, Abdullah Gani, RafidahMd Noor, Mehdi Sookhak, Hamid Talebian, Muhammad Shiraz and Muhammad Khurram Khan. “Cloud resource allocation schemes: review, taxonomy, and opportunities” Springer-Verlag London 2016.
[4]Endo, P., de Almeida Palhares, A., Pereira, N., Goncalves, G., Sadok, D., Kelner, J., Melander, B. and Mangs, J.-E. (2011) ‘Resource allocation for distributed cloud: Concepts and research challenges’, IEEE Network, 25(4), pp. 42–46. Doi: 10.1109/mnet.2011.5958007.
[5]Pawar, Chandrashekhar S., and Rajnikant B. Wagh. "Priority Based Dynamic Resource Allocation in Cloud Computing." IEEE, 2013 International Symposium on Cloud and Services Computing (2013)
[6]Eawna, MarwahHashim, Salma Hamdy Mohammed, and El-Sayed M. El-Horbaty. "Hybrid Algorithm for Resource Provisioning of Multi-Tier Cloud Computing." Elsevier publication, Procedia Computer Science 65 (2015): 682-90.
[7]Capacity Leasing in Cloud Systems Using the Open Nebula Engine (n.d): n. pag. Web.
[8]Nagpure Mahesh B., PrashantDahiwale, and PunamMarbate. "An Efficient Dynamic Resource Allocation Strategy for VM Environment in Cloud.” IEEE, 2015 International Conference on Pervasive Computing (ICPC) (2015)
[9]Kumar, Narander, and Swati Saxena. "A Preference-based Resource Allocation in Cloud Computing Systems." Elsevier publication, Procedia Computer Science 57 (2015): 104-11.
[10]Lin, Weiwei, James Z. Wang, Chen Liang, and Deyu Qi. "A Threshold-based Dynamic Resource Allocation Scheme for Cloud Computing." Elsevier publication, Procedia Engineering 23 (2011): 695-703.
[11]Saraswathi, A.t., Y. R. A. Kalaashri, and S. Padmavathi. "Dynamic Resource Allocation Scheme in Cloud Computing." Elsevier publication, Procedia Computer Science 47 (2015): 30-3
[12]Sudeepa R, Dr. H S Guruprasad. “Resource Allocation in Cloud Computing.” IJMCTR, ISSN: 2321-0850, Volume-2, Issue-4, April 2014.
[13]Wolke, A., Bichler, M., Chirigati, F. and Steeves, V. (2016) ‘Reproducible experiments on dynamic resource allocation in cloud data centers’, Information Systems, 59, pp. 98–101. doi: 10.1016/
[14]M Katyal and A Mishra. “A Comparative Study of Load Balancing Algorithms in Cloud Computing Algorithms” IJDCC, Volume 1, Issue 2, December 2013.
[15]Shahdi-Pashaki, S. et al. "Group Technology-Based Model and Cuckoo Optimization Algorithm for Resource Allocation in Cloud Computing". IFAC-Papers Online 48.3 (2015): 1140-1145. Web.