Analysis of Different Load Balancing Algorithms in Cloud Computing

2021 ◽  
Vol 11 (4) ◽  
pp. 100-112
Author(s):  
Poonam Nandal ◽  
Deepa Bura ◽  
Meeta Singh ◽  
Sudeep Kumar
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Resource Utilization ◽  
Exponential Growth ◽  
Average Response ◽  
Average Response Time ◽  
It Industry ◽  
Time Processing ◽  
Processing Cost ◽  
Day By Day

In today's world, the IT industry is emerging day by day; therefore, the need for storage and computing is increasing multifold. Cloud computing has transformed the IT sector to much greater heights by virtualizing the systems, thereby reducing cost of the hardware to greater extent. Cloud computing is based on the pay as per use policy. Due to the exponential growth in cloud computing, users demand supplementary services and improved results which makes load balancing a major challenge. Load balancing distributes the workload across multiple nodes to optimize the performance of the system. Various load balancing algorithms exist to provide better resource utilization. This paper gives a brief analysis of load balancing algorithms and also compared these algorithms on the basis of certain metrics like average response time, processing cost, and data servicing time.

scholarly journals An Efficient Adaptive Load Balancing Algorithm for Cloud Computing Under Bursty Workloads

2015 ◽  
Vol 5 (3) ◽  
pp. 795-800 ◽  
Author(s):  
S. F. Issawi ◽  
A. Al Halees ◽  
M. Radi
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Quality Of Services ◽  
Average Response ◽  
Average Response Time ◽  
It Industry ◽  
Request Rate ◽  
Wide Range ◽  
Load Balancing Algorithm

Cloud computing is a recent, emerging technology in the IT industry. It is an evolution of previous models such as grid computing. It enables a wide range of users to access a large sharing pool of resources over the internet. In such complex system, there is a tremendous need for an efficient load balancing scheme in order to satisfy peak user demands and provide high quality of services. One of the challenging problems that degrade the performance of a load balancing process is bursty workloads. Although there are a lot of researches proposing different load balancing algorithms, most of them neglect the problem of bursty workloads. Motivated by this problem, this paper proposes a new burstness-aware load balancing algorithm which can adapt to the variation in the request rate by adopting two load balancing algorithms: RR in burst and Random in non-burst state. Fuzzy logic is used in order to assign the received request to a balanced VM. The algorithm has been evaluated and compared with other algorithms using Cloud Analyst simulator.  Results show that the proposed algorithm improves the average response time and average processing time in comparison with other algorithms.

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.

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.

Elastic Optical Network Service-Oriented Architecture (SOA) Used for Cloud Computing and Its Resource Mapping Optimization Scheme

2020 ◽  
Vol 15 (4) ◽  
pp. 442-449
Author(s):  
Xun Xia ◽  
Ling Chen
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Resource Utilization ◽  
Service Oriented Architecture ◽  
Optical Network ◽  
Spectrum Utilization ◽  
Mapping Algorithm ◽  
Resource Mapping ◽  
Elastic Optical Network ◽  
Service Oriented

In this study, starting from the elastic optical network, the layered and function isolated service-oriented architecture (SOA) is introduced, so as to propose an elastic optical network SOA for cloud computing, and further study the resource mapping of optical network. Linear mapping model, random routing mapping algorithm, load balancing mapping algorithm and link separation mapping algorithm are introduced respectively, and the resource utilization effect of different mapping algorithms for the proposed optical network is compared. During the experiment, firstly, the elastic optical network is tested. It is found that the node utilization and spectrum utilization of the underlying optical fiber level network are significantly improved. Within the average service time of 0.312 s∼0.416 s, the corresponding node utilization and spectrum utilization are 90% and 80% respectively. In the resource mapping experiment, load balancing algorithm and link separation algorithm can effectively improve the mapping success rate of services. Among them, the link separation mapping algorithm can improve the spectrum resource utilization of optical network by 15.6%. The elastic optical network SOA proposed in this study is helpful to improve the use of network resources.

scholarly journals Measuring the Performance on Load Balancing Algorithms

2019 ◽  
pp. 41-49 ◽  
Author(s):  
Saumendu Roy ◽  
Dr. Md. Alam Hossain ◽  
Sujit Kumar Sen ◽  
Nazmul Hossain ◽  
Md. Rashid Al Asif
Keyword(s):  
Cloud Computing ◽  
Reaction Time ◽  
Load Balancing ◽  
Virtual Machines ◽  
Huge Amount ◽  
Heavy Load ◽  
Cloud Server ◽  
Load Balancing Algorithm ◽  
Day By Day ◽  
Better Than

Load balancing is an integrated aspect of the environment in cloud computing. Cloud computing has lately outgoing technology. It has getting exoteric day by day residence widespread chance in close to posterior. Cloud computing is defined as a massively distributed computing example that is moved by an economic scale in which a repertory of abstracted virtualized energetically. The number of clients in cloud computing is increasing exponentially. The huge amount of user requests attempt to entitle the collection for numerous applications. Which alongside with heavy load not far afield off from cloud server. Whenever particular (Virtual Machine) VMs are overloaded then there are no more duties should be addressed to overloaded VM if under loaded VMs are receivable. For optimizing accomplishment and better response or reaction time the load has to be balanced between overloaded VMs (virtual machines). This Paper describes briefly about the load balancing accession and identifies which is better than others (load balancing algorithm).

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