scholarly journals Performance Analysis of an Improved Load Balancing Algorithm in Cloud Computing

2019 ◽  
Vol 8 (2) ◽  
pp. 47 ◽  
Author(s):  
Abdulrahman Abdulkarim ◽  
Ishaq Muhammed ◽  
Lele Mohammed ◽  
Abbas Babayaro
Keyword(s):  
Cloud Computing ◽  
Performance Analysis ◽  
Load Balancing ◽  
Load Balancing Algorithm

scholarly journals A Load Balancing Algorithm for the Data Centres to Optimize Cloud Computing Applications

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Dalia Abdulkareem Shafiq ◽  
NZ Jhanjhi ◽  
Azween Abdullah ◽  
Mohammed A AlZain
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Load Balancing Algorithm ◽  
Data Centres

scholarly journals Cloud Computing based on the Load Balancing Algorithm

2018 ◽  
Vol 7 (4.7) ◽  
pp. 131
Author(s):  
NV Abhinav Chand ◽  
A Hemanth Kumar ◽  
Surya Teja Marella
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
User Satisfaction ◽  
Easy Access ◽  
Future Research ◽  
Computing Technology ◽  
Main Challenge ◽  
Load Balancing Algorithm ◽  
And Performance ◽  
Time Resource

Emerging cloud computing technology is a big step in virtual computing. Cloud computing provides services to clients through the internet. Cloud computing enables easy access to resources distributed all over the world. Increase in the number of the population has further increased the challenge. The main challenge of cloud computing technology is to achieve efficient load balancing. Load balancing is a process of assigning load to available resources in such a way that it avoids overloading of resources. If load balancing is performed efficiently, it improves QoS metric including cost, throughput, response time, resource utilization and performance. Efficient load balancing techniques also provide better user satisfaction. Various load balancing algorithms are used in different scenarios for ensuring the same. In the current research, we will study different algorithms for load balancing and benefits and limitations caused to the system due to the algorithms. In this paper, we will compare static and dynamic load balancing algorithms for various measures of efficiency. These will be useful for future research in the concerned field. 

scholarly journals An Optimal Solution in cloud computing for Load Balancing using Genetic Algorithm

2019 ◽  
Vol 8 (6) ◽  
pp. 2490-2494
Keyword(s):  
Genetic Algorithm ◽  
Cloud Computing ◽  
Load Balancing ◽  
Virtual Machines ◽  
Optimal Solution ◽  
Cloud Services ◽  
Research Trend ◽  
Schedule Length ◽  
Research Gap ◽  
Load Balancing Algorithm

Cloud computing is a research trend which bring various cloud services to the users. Cloud environment face various challenges and issues to provide efficient services. In this paper, a novel Genetic Algorithm based load balancing algorithm has been implemented to balance the load in the network. The literature review has been studied to understand the research gap. More specifically, load balancing technique authenticate the network by enabling Virtual Machines (VM). The proposed technique has been further evaluated using the Schedule Length Runtime (SLR) and Energy consumption (EC) parameters. Overall, the effective results has been obtained such as 46% improvement in consuming the energy and 12 % accuracy for the SLR measurement. In addition, results has been compared with the conventional approaches to validate the outcomes.

Load Balancing pada Cloud Computing dengan Sumber Daya Terbatas Menggunakan Penggabungan Algoritma ESCE dan Throttled

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Endang Wahyu Pamungkas ◽  
Divi Galih Prasetyo Putri
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Load Balancing ◽  
High Reliability ◽  
Cloud Service ◽  
The Other ◽  
Limited Resources ◽  
Resource Quality ◽  
Cloud Computing Environment ◽  
Load Balancing Algorithm

Recently cloud computing technology has been implemented by many companies. This technology requires a really high reliability that closely related to hardware specification and management resource quality used. Adequate hardware would make resource allocation easier. On the other hand, resource allocation will be harder if the resources are limited. This is a common condition in a developing cloud service provider. In this paper, a load balancing algorithm to allocate resources in cloud computing environment that has limited resources has been proposed. This algorithm is developed by taking the advantages of the existing algorithms, Equally Spread Current Execution and Throttled. We merge those algorithm without losing the advantages and we try to eliminate the shortcoming of each algorithm. The result shows that this algorithm is able to give a significant improvement in the limited resources environment. In addition, the algorithm also able to compete with the other algorithm in the more adequate resource environment. Based on the consistent results, this algorithm is expected to be more adaptive in different resources environment.

A Proficient Approach for Load Balancing in Cloud Computing-Join Minimum Loaded Queue

2020 ◽  
Vol 11 (1) ◽  
pp. 12-36
Author(s):  
Minakshi Sharma ◽  
Rajneesh Kumar ◽  
Anurag Jain
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Response Time ◽  
Resource Utilization ◽  
Cloud Service ◽  
Cloud Environment ◽  
Cloud Service Provider ◽  
Qos Parameters ◽  
Load Balancing Algorithm

Cloud load balancing is done to persist the services in the cloud environment along with quality of service (QoS) parameters. An efficient load balancing algorithm should be based on better optimization of these QoS parameters which results in efficient scheduling. Most of the load balancing algorithms which exist consider response time or resource utilization constraints but an efficient algorithm must consider both perspectives from the user side and cloud service provider side. This article presents a load balancing strategy that efficiently allocates tasks to virtualized resources to get maximum resource utilization in minimum response time. The proposed approach, join minimum loaded queue (JMLQ), is based on the existing join idle queue (JIQ) model that has been modified by replacing idle servers in the I-queues with servers having one task in execution list. The results of simulation in CloudSim verify that the proposed approach efficiently maximizes resource utilization by reducing the response time in comparison to its other variants.

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