Author : Sirisati Ranga Swamy 1
Date of Publication :26th April 2018
Abstract: Cloud computing can provide on-demand storage as well as computing services that have a high performance level along with high scalability. The increasing consumption of energy in the cloud data centers is a very prominent problem today. The cloud performance has been affected because of the issues in security. Thereby, the service providers have been held responsible for taking proper care of these systems here and the scheduling will be held responsible for the choice of best and also most suitable resources in the task execution by means of taking certain types of static as well as dynamic parameters along with the restrictions of such tasks into consideration. The scheduling in that of cloud computing will belong to one category of the problems that are called the Non-deterministic Polynomial (NP)-hard based problems owing to the solution space and so it takes a long time in identifying an optimal solution. Here in this work, the fuzzy logic and the methods are greedy in terms of the methods that were proposed. For calculating the value of the fitness in the fuzzy inference system the membership function is used to determine the degree until which these parameters belonging to a fuzzy set which is relevant. The work also introduced another new idea for integrating the approaches in solving the hard problems that are combinatorial. This proposed methodology which shall evaluate all the objects in a manner that can combine the fuzzy reasoning along with a greedy mechanism. It also means that the fuzzy solution space is exploited with some greedy methods. The results of the experiment proved that this method proposed can achieve better performance than that of the fuzzy logic
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