A Review on Load Balancing Model Using Best Partition Technique

2017 ◽  
Vol 7 (8) ◽  
pp. 284
Author(s):  
M. Chaitanya ◽  
K. Durga Charan
Keyword(s):  
Cloud Computing ◽  
Fault Tolerance ◽  
Load Balancing ◽  
Load Balance ◽  
Large Impact ◽  
Cloud Environment ◽  
Public Cloud ◽  
The Public ◽  
Partition Technique ◽  
Textual Content

Load balancing makes cloud computing greater knowledgeable and could increase client pleasure. At reward cloud computing is among the all most systems which offer garage of expertise in very lowers charge and available all the time over the net. However, it has extra vital hassle like security, load administration and fault tolerance. Load balancing inside the cloud computing surroundings has a large impact at the presentation. The set of regulations relates the sport idea to the load balancing manner to amplify the abilties in the public cloud environment. This textual content pronounces an extended load balance mannequin for the majority cloud concentrated on the cloud segregating proposal with a swap mechanism to select specific strategies for great occasions.

scholarly journals Factors Affecting Fault Tolerance during Load Balancing in Cloud Computing

2021 ◽  
Vol 12 (11) ◽  
pp. 1523-1533
Author(s):  
Bidush Kumar Sahoo , Et. al.
Keyword(s):  
Cloud Computing ◽  
Fault Tolerance ◽  
Load Balancing ◽  
South India ◽  
Analysis Tool ◽  
Factors Affecting ◽  
Software Firms ◽  
Statistical Analysis Tool ◽  
Cost Efficient ◽  
Support Cost

Cloud computing is built upon the advancement of virtualization and distributed computing to support cost-efficient usage of computing resources and to provide on demand services. After methodical analysis on various factors affecting fault tolerance during load balancing is performed and it is concluded that the factors influencing fault tolerance in load balancing are cloud security, adaptability etc. in comparatively more software firms. In this paper, we have created a model for various IT industries for checking the fault tolerance during Load balancing. An exploration is done with the help of some renowned IT farms and industries in South India. This work consists of 20 hypotheses which may affect the fault tolerance during load balancing in South India. It is verified by using potential statistical analysis tool i.e. Statistical Package for Social Science (SPSS).

scholarly journals A Conceptual Model for Cloud Computing Adoption by SMEs in Australia

2016 ◽  
pp. 307-334 ◽  
Author(s):  
Ishan Senarathna ◽  
Matthew Warren ◽  
William Yeoh ◽  
Scott Salzman
Keyword(s):  
Cloud Computing ◽  
Conceptual Model ◽  
Business Service ◽  
Perceived Benefits ◽  
Public Cloud ◽  
Total Cost ◽  
The Public ◽  
Software Applications ◽  
On Demand ◽  
Cloud Computing Adoption

Cloud Computing is an increasingly important worldwide development in business service provision. The business benefits of Cloud Computing usage include reduced IT overhead costs, greater flexibility of services, reduced TCO (Total Cost of Ownership), on-demand services, and improved productivity. As a result, Small and Medium-Sized Enterprises (SMEs) are increasingly adopting Cloud Computing technology because of these perceived benefits. The most economical deployment model in Cloud Computing is called the Public Cloud, which is especially suitable for SMEs because it provides almost immediate access to hardware resources and reduces their need to purchase an array of advanced hardware and software applications. The changes experienced in Cloud Computing adoption over the past decade are unprecedented and have raised important issues with regard to privacy, security, trust, and reliability. This chapter presents a conceptual model for Cloud Computing adoption by SMEs in Australia.

Auto-Scaling in the Cloud Environment

2020 ◽  
pp. 84-98
Author(s):  
Ravindra Kumar Singh Rajput ◽  
Dinesh Goyal
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
The Internet ◽  
Data Traffic ◽  
Cloud Environment ◽  
Software Application ◽  
Workload Balancing ◽  
Specific Configuration ◽  
Using Data ◽  
Auto Scaling

Every software application has its own minimum set of requirements like CPU, storage, memory, networking, and power. These have to be integrated into a specific configuration to allow the smooth functioning of the software application. When data traffic becomes higher than expected, higher resources are required. There may not be enough time to provision new resources manually; in such cases, an auto-scaling system is required for managing these situations. Cloud computing means using data, programs, and other resources pooled in the data center and accessed through the internet instead of the user's computer. In the chapter, the authors discussed some aspects related to cloud computing like cloud workload, load balancing, load balancing algorithms, scaling techniques, and auto-scaling to fulfill cloud workload balancing requirements.

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.

Receiver Initiated Deadline Aware Load Balancing Strategy (RDLBS) for Cloud Environment

2017 ◽  
Vol 8 (3) ◽  
pp. 53-73
Author(s):  
Raza Abbas Haidri ◽  
Chittaranjan Padmanabh Katti ◽  
Prem Chandra Saxena
Keyword(s):  
Cloud Computing ◽  
Performance Evaluation ◽  
Load Balancing ◽  
Virtual Machines ◽  
Turnaround Time ◽  
Cloud Environment ◽  
Computing Technology ◽  
Trade Off ◽  
The Cost ◽  
State Of Art

The emerging cloud computing technology is the attention of both commercial and academic spheres. Generally, the cost of the faster resource is more than the slower ones, therefore, there is a trade-off between deadline and cost. In this paper, the authors propose a receiver initiated deadline aware load balancing strategy (RDLBS) which tries to meet the deadline of the requests and optimizes the rate of revenue. RDLBS balances the load among the virtual machines (VMs) by migrating the request from the overloaded VMs to underloaded VMs. Turnaround time is also computed for the performance evaluation. The experiments are conducted by using CloudSim simulator and results are compared with existing state of art algorithms with similar objectives.

scholarly journals A Comprehensive Study of Load Balancing Approaches in the Cloud Computing Environment and a Novel Fault Tolerance Approach

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 130500-130526
Author(s):  
Muhammad Asim Shahid ◽  
Noman Islam ◽  
Muhammad Mansoor Alam ◽  
Mazliham Mohd Su'ud ◽  
Shahrulniza Musa
Keyword(s):  
Cloud Computing ◽  
Fault Tolerance ◽  
Load Balancing ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Tolerance Approach ◽  
Comprehensive Study

Migration of applications to the Cloud: a user-driven approach

2016 ◽  
Vol 2 (1) ◽  
Author(s):  
Anastasia Panori ◽  
Agustín González-Quel ◽  
Miguel Tavares ◽  
Dimitris Simitopoulos ◽  
Julián Arroyo
Keyword(s):  
Cloud Computing ◽  
Smart City ◽  
Public Services ◽  
Cloud Services ◽  
Cloud Environment ◽  
Public Cloud ◽  
Cloud Infrastructure ◽  
Migration Process ◽  
Empirical Application ◽  
Selection Of

During the last decade, there has been an increased interest on cloud computing and especially on the adoption of public cloud services. The process of developing cloud-based public services or migrating existing ones to the Cloud is considered to be of particular interest—as it may require the selection of the most suitable applications as well as their transformation to fit in the new cloud environment. This paper aims at presenting the main findings of a migration process regarding smart city applications to a cloud infrastructure. First, it summarises the methodology along with the main steps followed by the cities of Agueda (Portugal), Thessaloniki (Greece) and Valladolid (Spain) in order to implement this migration process within the framework of the STORM CLOUDS project. Furthermore, it illustrates some crucial results regarding monitoring and validation aspects during the empirical application that was conducted via these pilots. These findings should be received as a helpful experience for future efforts designed by cities or other organisations that are willing to move their applications to the Cloud.

A Survey on Load Balancing Algorithms for Cloud Environment

2019 ◽  
Vol 16 (2) ◽  
pp. 764-767
Author(s):  
P. Chitra ◽  
Karthika D. Renuka ◽  
K. Senathipathi ◽  
S. Deepika ◽  
R. Geethamani
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Comparative Analysis ◽  
Load Balancing ◽  
Resource Utilization ◽  
The Internet ◽  
Cloud Environment ◽  
Web Based ◽  
Qos Metrics

Cloud computing is the cutting edge technology in the information field to provide services to the users over the internet through web–based tools and applications. One of the major aspects of cloud computing is load balancing. Challenges like Quality of service (QoS) metrics and resource utilization can be improved by balancing the load in cloud environment. Specific scheduling criteria can be applied using load balancing for users prioritization. This paper surveys different load balancing algorithms. The approaches that are existing are discussed and analyzed to provide fair load balancing and also a comparative analysis was presented for the performance of the existing different load balancing schemes.

Efficient on Demand Dynamic Availability-Distribution-Span Scheduling and Load Balancing Scheme for Cloud Computing

2016 ◽  
Vol 13 (10) ◽  
pp. 7655-7660 ◽  
Author(s):  
V Jeyakrishnan ◽  
P Sengottuvelan
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Resource Utilization ◽  
Scheduling Algorithms ◽  
Time Factor ◽  
Cloud Environment ◽  
On Demand ◽  
Availability Factor ◽  
Scheduling Method

The problem of load balancing in cloud environment has been approached by different scheduling algorithms. Still the performance of cloud environment has not been met to the point and to overcome these issues, we propose a naval ADS (Availability-Distribution-Span) Scheduling method to perform load balancing as well as scheduling the resources of cloud environment. The method performs scheduling and load balancing in on demand nature and takes dynamic actions to fulfill the request of users. At the time of request, the method identifies set of resources required by the process and computes Availability Factor, Distributional Factor and Span Time factor for each of the resource available. Based on all these factors computed, the method schedules the requests to be processed in least span time. The proposed method produces efficient result on scheduling as well as load balancing to improve the performance of resource utilization in the cloud environment.

Provisioning of Virtual Machines in the Context of an Auto-Scaling Cloud Computing Environment

2020 ◽  
Vol 17 (6) ◽  
pp. 2430-2434
Author(s):  
R. S. Rajput ◽  
Dinesh Goyal ◽  
Rashid Hussain ◽  
Pratham Singh
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Resource Utilization ◽  
Virtual Machines ◽  
Cloud Environment ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Auto Scaling ◽  
Adequate Resource ◽  
Cloud Resources

The cloud computing environment is accomplishing cloud workload by distributing between several nodes or shift to the higher resource so that no computing resource will be overloaded. However, several techniques are used for the management of computing workload in the cloud environment, but still, it is an exciting domain of investigation and research. Control of the workload and scaling of cloud resources are some essential aspects of the cloud computing environment. A well-organized load balancing plan ensures adequate resource utilization. The auto-scaling is a technique to include or terminate additional computing resources based on the scaling policies without involving humans efforts. In the present paper, we developed a method for optimal use of cloud resources by the implementation of a modified auto-scaling feature. We also incorporated an auto-scaling controller for the optimal use of cloud resources.

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