Open AccessA fuzzy energy and security aware scheduling in cloud
Author(s) -
Sirisati Ranga Swamy,
Sridhar Mandapati
Publication year - 2017
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i1.2.9021
Subject(s) - cloud computing , computer science , fuzzy logic , scheduling (production processes) , fuzzy inference , distributed computing , job scheduler , mathematical optimization , fuzzy control system , adaptive neuro fuzzy inference system , operating system , artificial intelligence , mathematics
The cloud computing is the one that deals with the trading of the resources efficiently in accordance to the user’s need. A Job scheduling is the choice of an ideal resource for any job to be executed with regard to waiting time, cost or turnaround time. A cloud job scheduling will be an NP-hard problem that contains n jobs and m machines and every job is processed with each of these m machines to minimize the make span. The security here is one of the top most concerns in the cloud. In order to calculate the value of fitness the fuzzy inference system makes use of the membership function for determining the degree up to which the input parameters that belong to every fuzzy set is relevant. Here the fuzzy is used for the purpose of scheduling energy as well as security in the cloud computing.