Intelligent Admission Control Manager using Decision Tree Classifier in Fog Integrated Cloud

6 Pages Posted: 30 Jan 2020

See all articles by Eht E Sham

Eht E Sham

Jawaharlal Nehru University

Deo Prakash Vidyarthi

Jawaharlal Nehru University

Date Written: January 29, 2020

Abstract

Internet of Things (IoT) and related devices are producing the data, which are very large in volume, variety, and velocity. There are many time critical applications, and by the time the data is sent to cloud for analysis/execution, the opportunity to act might be gone. Consequently, we may face problem either financially or other way round where cost is intangible. So time sensitivity matters a lot, and such criticality could be achieved through smart admission control manager at the nearest node usually in form of fog layer architecture. In this paper, a smart admission control manager is being proposed which has the primary responsibility of placing the jobs based on the request parameters such as CPU, Memory, Disk Space etc. besides some other categorical parameters e.g. priority of request, time-sensitivity of request etc. Post-processing, data may be forwarded for further analysis to the Cloud. The proposed work applies a machine learning technique which first classifies the jobs into two or three categories, based on the requirement of the domain. Further, it will decide on job placement to the respective nodes using decision tree classifier.

Keywords: Fog Computing, Cloud Computing, Internet of Things (IoT), Machine Intelligence Resource Provisioning

Suggested Citation

Sham, Eht E and Prakash Vidyarthi, Deo, Intelligent Admission Control Manager using Decision Tree Classifier in Fog Integrated Cloud (January 29, 2020). 5th International Conference on Next Generation Computing Technologies (NGCT-2019), Available at SSRN: https://ssrn.com/abstract=3527394 or http://dx.doi.org/10.2139/ssrn.3527394

Eht E Sham (Contact Author)

Jawaharlal Nehru University ( email )

Vasant Vihar
Jawaharlal Nehru University
New Delhi, DE Delhi 110067
India
9818938592 (Phone)

HOME PAGE: http://https://jnu.ac.in/sites/default/files/scss/PDSG/

Deo Prakash Vidyarthi

Jawaharlal Nehru University ( email )

New Delhi
Jawaharlal Nehru University
New Delhi, 110067
India

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
85
Abstract Views
554
Rank
531,415
PlumX Metrics