Multi objective firefly and raindrop optimization for cloud service provisioning

Abstract

Cloud environment is an essential computing resource for energy utilization and cloud service provisioning.Recently, many research works are designed for attaining efficient resource utilization in cloud environment. However, service provisioning on stored data in cloud has not been addressed sufficiently and there is scope for more research. The proposed methods are introduced for improving the cloud resource utilization with reduced energy consumption. At first, the proposed method Pearson Service Correlation based Firefly Resource Cost Optimization (PSC-FRCO) technique is developed. Next, Whale Optimized Multicriterion Correlation (WOMC) technique is implemented. Finally, a Matthews Service Correlations Based Multi-Objective Raindrop Random Optimization (MSCMRRO) technique is introduced. The performance analysis of proposed methods such as, PSCFRCO technique, WOMC technique and MSCMRRO technique is executed using Java Language with CloudSim simulator. From the experimental analysis, the proposed technique is seen to give and enhanced resource utilization efficiency. The simulation results show that consumption of energy and memory is lessened by 30% and 28%. This is achieved due to the presence of minimum response time which is reduced by 30 %. With minimum response time and energy consumption, service provisioning efficiency is enhanced by 26% and resource utilization efficiency is increased by 28% when compared to other state of the art methods. newline