Hybrid Harmony Search with Firefly Algorithm for Job Scheduling in Big Data

Abstract

The bulk quantity of data can be allowed to dig out and to mine unknown information using the applications of big data analytics. In the proposed work, scheduling of jobs can be accomplished using Firefly Algorithm (FA). The objective is to minimize the job execution time, make best use of resources load. The difficulty in scheduling of jobs can be rectified using Multi-Stage Stochastic Integer Programming (MSSIP) and used to process ambiguity. This paper resolve ambiguity problem in big data analytics. To resolve job scheduling problem, Harmony Search Algorithm (HSA) and Firefly Algorithm (FA) is used, so that it make use of resources efficiently. It permits the resources to take the scheduling decisions on their own. The outcome demonstrates that the ambiguity can be resolved and the convergence rate can be improved using MSSIP algorithms in big data analytics.