Nature Inspired Data Placement Strategy in Distributed Cloud Environment Using Improved Firefly Algorithm

Abstract

The execution of scientific applications needs high-processing computers and requires massive storage. This resulted in deploying applications in a distributed environment with high performance and extensive storage. Applications processed in cloud platforms face intolerable delays due to data movement across the centres. Optimized distribution of datasets among the global data centres has become an essential issue in the distributed cloud environment. This work proposes an improved data placement called IFA Data Placement (IFA-DP) method for a heterogeneous cloud environment. An effective and efficient optimal data placement strategy is proposed using a metaheuristic global optimisation firefly algorithm. The metaheuristic behavior of fireflies finds a better optimal solution. The primary aim of this work is to reduce the response time and execution cost, which is then proved by the simulation results. The access time of the Proposed IFA-DP is less by at least 2s compared to the existing methods.