An Efficient Architecture and Algorithm for Resource Provisioning in Fog Computing

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Swati Agarwal 1,* Shashank Yadav 2 Arun Kumar Yadav 3

1. Department of Computer Science and Technology, UPTU University, Lucknow, U.P. India

2. Department of Computer Science and Technology, Hindustan Institute of Tech. & Mgmt., Agra, U.P., India

3. Department of Computer Science and Technology, ITM University Gwalior, M.P., India

* Corresponding author.


Received: 16 Oct. 2015 / Revised: 12 Nov. 2015 / Accepted: 2 Dec. 2015 / Published: 8 Jan. 2016

Index Terms

Cloud Computing, Fog Computing, Resource Allocation, virtual machine and virtualization


Cloud computing is a model of sharing computing resources over any communication network by using virtualization. Virtualization allows a server to be sliced in virtual machines. Each virtual machine has its own operating system/applications that rapidly adjust resource allocation. Cloud computing offers many benefits, one of them is elastic resource allocation. To fulfill the requirements of clients, cloud environment should be flexible in nature and can be achieve by efficient resource allocation. Resource allocation is the process of assigning available resources to clients over the internet and plays vital role in Infrastructure-as-a-Service (IaaS) model of cloud computing. Elastic resource allocation is required to optimize the allocation of resources, minimizing the response time and maximizing the throughput to improve the performance of cloud computing. Sufficient solutions have been proposed for cloud computing to improve the performance but for fog computing still efficient solution have to be found. Fog computing is the virtualized intermediate layer between clients and cloud. It is a highly virtualized technology which is similar to cloud and provide data, computation, storage, and networking services between end users and cloud servers. This paper presents an efficient architecture and algorithm for resources provisioning in fog computing environment by using virtualization technique.

Cite This Paper

Swati Agarwal, Shashank Yadav, Arun Kumar Yadav, "An Efficient Architecture and Algorithm for Resource Provisioning in Fog Computing", International Journal of Information Engineering and Electronic Business(IJIEEB), Vol.8, No.1, pp.48-61, 2016. DOI:10.5815/ijieeb.2016.01.06


[1]Kamyab Khajehei, “Role of virtualization in cloud computing”, International Journal of Advance Research in Computer Science and Management Studies Volume 2, Issue 4, April 2014.
[2]Ivan Stojmenovic, sheng Wen, “The Fog Computing Paradigm: Scenarios and security issues” Proceedings of the IEEE International Fedrerated Conference on Computer Science and Information Systems, 2014, pp. 1-8.
[3]N.R.RamMohan, E.Baburaj “Resource Allocation Techniques in Cloud computing-Research Challenges for Applications”, Proc. Of the IEEE Fourth International Conference on Computational Intelligence and Communication Networks, 2012, pp. 556-560
[4]Eman Elghoneimy, Othmane Bouhali, Hussein Alnuweiri, “Resource Allocation and scheduling in Cloud Computing”, Proc. Of the IEEE International Workshop on Computing, Networking and Communications, 2012, pp. 309 – 314.
[5]Liang Luo,Wenjun Wu, Dichen Di, fei Zhang, Yizhou yan, Yaokuan Mao, “ A Resource scheduling algorithm of cloud computing based on energy efficient optimization methods”, Proc. Of the IEEE International Green Computing Conference (IGCC), 2012, pp. 1 – 6.
[6]Aditya Marphatia, Aditi Muhnot, Tanveer Sachdeva, Esha Shukla, Prof. Lakshmi Kurup,” Optimization of FCFS Based Resource Provisioning Algorithm for Cloud Computing” , IOSR Journal of Computer Engineering (IOSR-JCE) e-ISSN: 2278-0661, p- ISSN: 2278-8727Volume 10, Issue 5 (Mar. - Apr. 2013), PP 01-05.
[7]Shimpy, Jagandeep Sidhu,” Different Scheduling Algorithms In Different Cloud Environment”, International Journal of Advanced Research in Computer and Communication Engineering Vol. 3, Issue 9, September 2014.
[8]Savani Nirav M, Prof. Amar Buchade, “Priority Based Allocation in Cloud Computing”, International Journal of Engineering Research & Technology (IJERT) ISSN: 2278-0181 IJERTV3IS051140 Vol. 3 Issue 5, May – 2014.
[9]Chandrasekhar S. Pawar, Rajnikant B. Wagh,” Priority Based Dynamic resource allocation in Cloud Computing with modified Waiting Queue”, Proceeding of the IEEE 2013 International Conference on Intelligent System and Signal Processing(ISSP) Pages 311-316.
[10]Endo P.T., de Almeida Palhares, A.V., Pereira, N.N., Goncalves, G.E., “Resource allocation for distributed cloud: concepts and research challenges”, Proceeding of the IEEE Network Vol. 24, Issue 4, July 2011, pp.42-46.
[11]Yusen Li, Xueyan Tang, Wentong Cai,” Dynamic Bin packing for on demand cloud resource allocation ”, Proceedings of the IEEE Transactions on Parallel and Distributed Systems ,2015,Paged 1-14.
[12]Zhengqiu Yang, Meiling Liu, Jiapeng Xiu, Chen Liu, ” Study on cloud resource allocation strategy based on particle swarm ant colony optimization algorithm” ,IEEE 2nd International Conference on Cloud Computing and Intelligent Systems (CCIS),Nov. 2012 ,pp. 488 – 491.
[13]Harpreet Kaur, Maninder Singh,” A Task Scheduling and Resource Allocation Algorithm for Cloud using Live Migration and Priorities”, International Journal of Computer Applications (0975 – 8887) Volume 84 – No 13, December 2013.
[14]Zhen Xiao, Senior Member, IEEE, Weijia Song, and Qi Chen, “Dynamic Resource Allocation Using Virtual Machines for Cloud Computing Environment”, “,IEEE Transactions on Parallel and Distributed Systems, Vol.24, No. 6, June 2013, pp. 1107-1117.
[15]Kunal Kishor, Vivek Thapar, “ An Efficient Service Broker Policy for cloud computing environment”, International Journal of Computer Science Trends and Technology (IJCST) – Volume 2 Issue 4, July-Aug 2014.
[16]Swati Agarwal, Shashank Yadav, Arun Kumar Yadav,” An architecture for elastic resource allocation in Fog computing”, International Journal of Computer Science and Communication, Vol. 6 Number 2 April - Sep 2015 pp. 201-207.
[17]Rahul Malhotra, Prince Jain,” Study and Comparison of Various Cloud Simulators Available in the Cloud Computing”, International Journal of Advanced Research in Computer science and Software Engineering ISSN: 2277 128X Vol. 3, Issue 9, September 2013.
[18]Bhathiya Wickremasinghe “Cloud Analyst: A CloudSim Based Tool For Modeling And Analysis Of Large Scale Cloud Computing Environments. MEDC Project”, Report 2010.
[19]Hetal V. Patel, Ritesh Patel, “Cloud Analyst: An Insight of Service Broker Policy”, International Journal of Advanced Research in Computer and Communication Engineering Vol. 4, Issue 1, January 2015.
[20]R. Buyya, R. Ranjan, and R. N. Calheiros, “Modeling And Simulation Of Scalable Cloud Computing Environments And The CloudSim Toolkit: Challenges And Opportunities,” Proc. Of The 7th High Performance Computing and Simulation Conference (HPCS 09), IEEE Computer Society, June 2009.