Energy efficiency in cloud data centres using parallel hybrid Jaya algorithm

Abstract

Purpose Data centres evolve constantly in size, complexity and power consumption. Energy-efficient scheduling in a cloud data centre is a critical and challenging research problem. It becomes essential to minimize the overall operational costs as well as environmental impact and to guarantee the service-level agreements for the services provided by the cloud data centres. Resource scheduling in cloud data centres is NP-hard and often requires substantial computational resources. Design/methodology/approach To overcome these problems, the authors propose a novel model that leads to nominal operational cost and energy consumption in cloud data centres. The authors propose an effective approach, parallel hybrid Jaya algorithm, that performs parallel processing of Jaya algorithm and genetic algorithm using multi-threading and shared memory for interchanging the information to enhance convergence premature rate and global exploration. Findings Experimental results reveal that the proposed approach reduces the power consumption in cloud data centres up to 38% and premature convergence rate up to 60% compared to other algorithms. Originality/value Experimental results reveals that our proposed approach reduces the power consumption in cloud data centres up to 38% and premature convergence rate up to 60% compared to other algorithms.

Classification and Performance Study of Task Scheduling Algorithms in Cloud Computing Environment

“…Black Widow Optimization is not trapped at local minima, so, the authors suggests that this property can be promising for new computing paradigm. (Kollu & Sucharita, 2021) have launched an energy-efficient task scheduling technique in a cloud data centers (DCs) using parallel implementation of hybrid Jaya optimization algorithm (JA). The aim of this model is to decrease energy consumption and maximize the physical resource utilization by considering efficient task scheduling and VM allocation in cloud data centers (DCs).…”