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Honed resource segregation in Cloud, Fog and Edge computing using data consumption Churn

Suresh Kumar, Hari Narayanan (2019) Honed resource segregation in Cloud, Fog and Edge computing using data consumption Churn. Masters thesis, Dublin, National College of Ireland.

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Abstract

Data in day to day is in upturn trend due to an increase in the usage of technological gadgets. In this avant-garde era, all these data are stored in the cloud and managing these data efficiently in the cloud server is denounce. Even though the cloud servers have paved a way to develop the fog and edge servers, the decisive resource optimization method in all three servers (Cloud, Fog, and Edge) in order to reduce latency in them is still a claiming. I proposed an algorithm that can optimize the resource and hone them by using data analytics methodologies and the algorithm is named as the `Data churn algorithm' as it hinges on business churn algorithm. This algorithm takes an application logfile from a corresponding application and analyses them based on service time, bytes size, URLs, and etc.. The next step is to make a graph with them to detect a point of variation in the graph to split them into three halves. Each half is then made to fit into Cloud, Fog and Edge servers by an application load balancer that makes the URLs of the application in each instance such as cloud, fog, and edge respectively which is analyzed by the Data churn algorithm. The system performance is calculated by using the tracert command that estimates the latency of the experimented web application. On using the data churn algorithm, the tracert command depicts that there is three-fourth of improvement in latency is observed on comparing with the traditional methods. The following approach successfully reduces latency in the Multilevel servers (Cloud, Fog, and Edge) on comparing with the existing algorithm that they follow.

Item Type: Thesis (Masters)
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science

T Technology > T Technology (General) > Information Technology > Cloud computing
Divisions: School of Computing > Master of Science in Cloud Computing
Depositing User: CAOIMHE NI MHAICIN
Date Deposited: 23 Mar 2020 18:06
Last Modified: 23 Mar 2020 18:06
URI: http://norma.ncirl.ie/id/eprint/4146

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