An Improved Resource Utilization System for Fog Computing Environment

Authors

  • Nassa H Department of Computer Science and Engineering, Deenbandhu Chhotu Ram University of Science and Technology, India
  • Kumar J Department of Computer Science and Engineering, Deenbandhu Chhotu Ram University of Science and Technology, India

DOI:

https://doi.org/10.26438/ijcse/v7i6.395400

Keywords:

Fog Computing, Internet of things (IoT), Virtual Machine (VM), Quality of Service (QoS), Data Centers (DC)

Abstract

Fog computing has expanded the horizons of cloud computing services near to the users. Firstly the IoT devices were used exclusively VMs but this results in high energy consumption. At the cloud layer the problem of resource utilization has been practised. But at the Fog layer the problem of Overutilization and Underutilization of resources occur. So, to overcome this problem we are designing a model for resource utilization that achieves best result for both service provider and end users. The current system incorporates an adaptive way for the utilization of resources at the cloud layer. But at the Fog layer the adaptive way of cloud layer are not being practised. The Fog layer allows pre-processing of requests but have limited resources. In order to overcome this problem, this paper, proposes a mechanism for improving the resource utilization at fog computing layer. Our proposed model is not only beneficial for the fog service providers in terms of good resource utilization but also equally beneficial for the fog service users in terms of good response time.

References

[1] Xu et al. “Dynamic resource allocation for load balancing in fog environment,” Vol. 2018.

[2] Deyu Qi et al. “A threshold-based dynamic resource allocation scheme for cloud computing,”pp.695-703, 2011.

[3] Vadde Usha , Dr. Vijaya Sri Kompalli ,”survey of resource management techniques in fog computing,” pp. 3761-3765,2018.

[4] P. Hu, S. Dhelim, H. Ning, and T. Qiu, “Survey on fog computing: architecture, key technologies, applications and open issues,” vol. 98, pp. 27–42, 2017.

[5] P.Jue et al. “Fog Computing: Towards Minimizing Delay in the Internet of Things,”2017.

[6] Buyya et al. “latency-aware application module management for fog computing environments,” article 9 November 2018.

[7] Turuk et al. “Mathematical Modeling of QoS-Aware Fog Computing Architecture for IoT Services,” pp.13-21, 2019.

[8] A. Khakimov, A. Muthanna, M. Muthanna,” Study of Fog Computing Structure,” pp.51-54, 2018.

[9] Z. Patrikakis et al. “A Cooperative Fog Approach for Effective Workload Balancing,”pp.36-45, 2017.

[10] O. Salman, I. Elhajj, A. Kayssi and A. Chehab “Edge computing enabling the Internet of Things,” pp. 603-608, 2015.

[11] M. Aazam and E. N. Huh, “Dynamic resource provisioning through Fog micro datacenter,” 2015.

[12] C. Prazeres, M. Serrano, “SOFT-IoT: Self-Organizing FOG of Things,” 2016.

[13] Hua-Jun Hong,” From Cloud Computing to Fog Computing: Unleash the Power of Edge and End Devices,” pp.331-334, 2017.

[14] Yung-Chiao Chen, Yao-Chung Chang,” Cloud-Fog Computing for Information-Centric Internet-of-Things Applications,”pp.637-640, 2017.

[15] Samson Busuyi Akintoye,Antoine Bagula,” Improving Quality-of-Service in Cloud/FogComputing through Efficient Resource Allocation ,”2019.

[16] Cheol-Ho Hong, Blesson Varghese,” Resource Management in Fog/Edge Computing: A Survey,”2018.

[17] Deeksha Arya, Mayank Dave,”Security-Based Service Broker Policy for Fog Computing Environment,”2017.

[18] R. Buyya et al. “Fog computing: Principles, architectures, and applications,” 2016.

[19] J. Kumar, A. Malik, SK. D hurandher ,” Demand-Based Computation Offloading Framework for Mobile Devices,”2017.

Downloads

Published

2019-06-30
CITATION
DOI: 10.26438/ijcse/v7i6.395400
Published: 2019-06-30

How to Cite

[1]
H. Nassa and J. Kumar, “An Improved Resource Utilization System for Fog Computing Environment”, Int. J. Comp. Sci. Eng., vol. 7, no. 6, pp. 395–400, Jun. 2019.

Issue

Section

Research Article