Energy-Aware Fruitfly Optimisation Algorithm for Load Balancing in Cloud Computing Environments
Journal Title: International Journal of Intelligent Engineering and Systems - Year 2017, Vol 10, Issue 1
Abstract
An effective task scheduling is one of the vital aspects for effectually hitching the potential of cloud computing. The most important aspect of task scheduling focuses on balancing the load of tasks among virtual machines, which is independent in nature. Energy conservation is one of the major key issues in cloud environment which in turn reduces operation costs in cloud datacenter. Meanwhile, Energy-aware load balancing optimisation technique is a promising way to attain the goal. To ensure fast processing time and optimum utilization of the cloud resources, we propose an energy-aware Fruit fly optimisation algorithm (EFOA-LB) for balancing the load among virtual machines in the cloud system. The energy-aware EFOA-LB is a modern swarm intelligence algorithm inspired by the foraging behavior of fruit flies, aims to attain well-balanced load on virtual machines and reduces energy consumption accordingly. Based on results obtained from our simulations, the proposed algorithms minimizes makespan and reduces the energy consumption of the datacenter, while meeting the task performance. The experiment results indicate that the energy-aware EFOA-LB algorithm is more efficient than the existing load balancing algorithms.
Authors and Affiliations
M LawanyaShri
Keywords
Related Articles
- EP ID EP229396
- DOI 10.22266/ijies2017.0228.09
- Views 125
- Downloads 0
Efficient Dissemination of Rainfall Forecasting to Safeguard Farmers from Crop Failure Using Optimized Neural Network Model
In the field of weather forecasting, especially in rainfall prediction many researchers employed different data mining techniques. There is numerous method of organizing agricultural engineering substance and it remains...
Routing for Center Concentrated Mesh
As the number of cores increases this affects the performance of the mesh and leads to investigation of new topological concept that is center concentrated Mesh. The topology designed seems to be efficient but the routin...
Feature Selection Optimization using Hybrid Relief-f with Self-adaptive Differential Evolution
In various classification areas, the curse of dimensionality becomes a major challenge among the researchers. Thus, feature selection plays an important role in overcoming dimensionality problem. Relief-f is one of the f...
Evolutionary Programming Approach for Deregulated Power Systems to Optimal Positioning of FACTS Devices
From past decade, the major issues involved in deregulated power systems are branch loading and voltage stability. To address this issue, in this paper an evolutionary programming algorithm was proposed for optimal posit...
Performance Evaluation of Association Rule Mining with Enhanced Apriori Algorithm Incorporated with Artificial Bee Colony Optimization Algorithm
In data mining, association rules are produced in view of solid relations and regularities existing among the variables in extensive exchanges. These association rules go for extricating connections, frequent patterns an...