Improved fuzzy Load-Balancing Algorithm for Cloud Computing System

2019 ◽  
Author(s):  
Mostefa Hamdani ◽  
Youcef Aklouf ◽  
Hadj Ahmed Bouarara
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Computing System ◽  
Cloud Computing System ◽  
Load Balancing Algorithm

scholarly journals An Efficient Novel Load Balancing Algorithm to Improve the Performance of the System in Cloud Environment

2019 ◽  
Vol 8 (S3) ◽  
pp. 105-108
Author(s):  
P. Neelima ◽  
A. Rama Mohan Reddy
Keyword(s):  
Load Balancing ◽  
Fitness Function ◽  
Dynamic Environment ◽  
Computing System ◽  
Dragonfly Algorithm ◽  
Main Challenge ◽  
Cloud Computing System ◽  
Load Balancing Algorithm ◽  
Load Balancer ◽  
Is Design

Distribution of workload in a balanced manner is a main challenge in cloud computing system. It distributes workload among multiple nodes, hence resources are properly utilized. This is an optimization problem and a good load balancer should be involved for this strategy to the types of tasks and dynamic environment. To overcome load balancing problem here a Novel Load balancing Algorithm is develop i.e. Dragonfly Algorithm is design and developed, to execute the entire task with shortest completion time and load balanced. Our algorithm will be presented with efficient solution representation, derivation of efficient fitness function (or multi-objective function) along with the usual Dragonfly operators. The performance of the algorithm will be analyzed based on the different evaluation measures. The algorithms like particle swarm optimization (PSO) and Genetic algorithm (GA) will be taken for the comparative analysis.

Enhanced active VM load balancing algorithm using fuzzy logic and K-means clustering

2021 ◽  
Vol 17 (1) ◽  
pp. 59-82
Author(s):  
Mostefa Hamdani ◽  
Youcef Aklouf
Keyword(s):  
Cloud Computing ◽  
Fuzzy Logic ◽  
Load Balancing ◽  
Response Time ◽  
Data Center ◽  
Service Rate ◽  
Dynamic Allocation ◽  
Use Of Resources ◽  
Cloud Computing System ◽  
Load Balancing Algorithm

With the rapid development of data and IT technology, cloud computing is gaining more and more attention, and many users are attracted to this paradigm because of the reduction in cost and the dynamic allocation of resources. Load balancing is one of the main challenges in cloud computing system. It redistributes workloads across computing nodes within cloud to minimize computation time, and to improve the use of resources. This paper proposes an enhanced ‘Active VM load balancing algorithm’ based on fuzzy logic and k-means clustering to reduce the data center transfer cost, the total virtual machine cost, the data center processing time and the response time. The proposed method is realized using Java and CloudAnalyst Simulator. Besides, we have compared the proposed algorithm with other task scheduling approaches such as Round Robin algorithm, Throttled algorithm, Equally Spread Current Execution Load algorithm, Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO). As a result, the proposed algorithm performs better in terms of service rate and response time.

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