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

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.

Author(s):  
Minakshi Sharma ◽  
Rajneesh Kumar ◽  
Anurag Jain

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 distributed computing is one of the most amazing administration offered by means of web which makes a stage to store and recover information Since client's close to home information is being put away in a decoded arrangement on a remote machine worked by outsider merchants who give different administrations, the effect of client's personality and unapproved access or revelation of records are extremely high.In this proposed system is using Dependability of the Users,Privacy and Integrity of Data (DPI) algorithms using improve the Execution assessment of Cloud Computing foundations is required to anticipate and measure the money saving advantage of a technique portfolio and the relating Quality of Service (QoS) experienced by clients. Along these lines, concentrating on Load adjusting in the distributed computing condition importantly affects the presentation. This paper deals with multi target asset provisioning plan for taking care of different errand classes for different outstanding task at hand office. In this proposal, project is using a Best Partition Searching for distributing a file system to another cloud environment. This methodology gives a security regarding client verification for "approval" to enter the system which is made by means of Image Sequencing secret key to demonstrate that the personality is unique client, RSA calculation to encode the information to give information respectability, a profoundly parallel conveyed information the executives administration that empowers to peruse/compose and add gigantic informational collections that are divided and circulated at a huge scale. Subsequently this methodology gives a general security to the customer's close to home information and the issue of simultaneousness, volume of information can be settled with these procedures


Author(s):  
Nirmalan R. ◽  
Gokulakrishnan K. ◽  
Jesu Vedha Nayahi J.

Cloud computing is a modern exemplar to provide services through the internet. The development of cloud computing has eliminated the need of manpower, which is mainly used for the management of resources. During the cloud computing process, the term cloud balancing is a vital one. It deals with distribution of workloads and computing resources. The load balancing allows the company to balance the load according to the demands by the allocation of the resources to multiple servers or networks. The quality of service (QoS) metrics, including cost, response time, performance, throughput, and resource utilization are improved by means of load balancing. In this chapter, the authors study the literature on the load-balancing algorithms in heterogeneous cluster cloud environment with some of its classification. Additionally, they provide a review in each of these categories. Also, they provide discernment into the identification of open issues and guidance for future research work.


Author(s):  
Ravindra Kumar Singh Rajput ◽  
Dinesh Goyal

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.


2016 ◽  
Vol 13 (10) ◽  
pp. 7655-7660 ◽  
Author(s):  
V Jeyakrishnan ◽  
P Sengottuvelan

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.


2020 ◽  
Vol 17 (6) ◽  
pp. 2430-2434
Author(s):  
R. S. Rajput ◽  
Dinesh Goyal ◽  
Rashid Hussain ◽  
Pratham Singh

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.


2021 ◽  
Author(s):  
Jianying Miao

This thesis describes an innovative task scheduling and resource allocation strategy by using thresholds with attributes and amount (TAA) in order to improve the quality of service of cloud computing. In the strategy, attribute-oriented thresholds are set to decide on the acceptance of cloudlets (tasks), and the provisioning of accepted cloudlets on suitable resources represented by virtual machines (VMs,). Experiments are performed in a simulation environment created by Cloudsim that is modified for the experiments. Experimental results indicate that TAA can significantly improve attribute matching between cloudlets and VMs, with average execution time reduced by 30 to 50% compared to a typical non-filtering policy. Moreover, the tradeoff between acceptance rate and task delay, as well as between prioritized and non-prioritized cloudlets, may be adjusted as desired. The filtering type and range and the positioning of thresholds may also be adjusted so as to adapt to the dynamically changing cloud environment.


2021 ◽  
Vol 11 (2) ◽  
pp. 1386-1399
Author(s):  
Ramya K.

With the advent of cloud computing, the affinity between business and technology had increased manifold, allowing users to access IT resources at their convenience through the pay-per-use scheme. With such huge demand surging day to day, the cloud environment must cater to the user requirements flawlessly and also should be rewarding to the providers of cloud service. To maintain its high level of efficiency, there are several challenges that the cloud environment should tackle. One amongst those challenges is the balancing of load. It is one of the primary features of cloud computing that focuses on avoiding the overloading of nodes where there may be idle nodes or nodes with lesser load present at the same juncture. By keeping an effective check on the load several the Quality of Service (QoS) parameters including response time, throughput, resource utilization, energy consumption, cost etc., can be improved, adding to better performance of the entire cloud environment. Even distribution of load among datacenters will contribute to optimal energy consumption and keeps a check on carbon emissions. In this paper we have presented a methodical review on literature pertaining to load balancing strategies that had been proposed in the cloud environment. We had made in-depth analyses of available load balancing techniques and had come up with their advantages, limitations along with the challenges to be addressed by researchers for developing efficient load balancing strategies in the near future. We had also suggested prospective insights about the aspects in load balancing that could be applied in the cloud environment.


Author(s):  
Diyurman Gea

Work efficiency and service quality improvement are two important things in competing with other businesses. Keep costs as low as possible with a satisfactory quality of service, can be optimized through the use of technology. One type of business that has the potential to be improved quality of service is a document copying services as implemented in Binus University. In addition to the staff and lecturers, students need the service for various types of documents such as copying lecture materials and other administrative documents. By leveraging the technology capabilities possessed by a photocopy machine to connect to a network computer, a system that supports the printing of documents through the Internet can be made. The online printing system is web-based, and capable of storing printing information into a database, so records can provide tracking information, which affects the quality of service and good performance. 


Author(s):  
Deepa Bura ◽  
Meeta Singh ◽  
Poonam Nandal

This article describes how cloud computing utilizes the benefits of web engineering and its applications by improving the performance and reducing the load on cloud providers. As the cloud is one of the emerging technology in the field of computing, it is used to provide various services to the user through the internet. One of the major concerns in cloud computing is accessibility of cloud. For estimating the availability of cloud, various load balancing algorithms are deployed in data centers of the cloud environment. Load balancing is a technique that distributes a signal load across various computers for optimizing resource usage, reducing response time, etc. There are different load balancing algorithms, for performing the load distribution across various centers. This article analyses different load balancing algorithms and develop a new algorithm for efficient load balancing. The proposed load balancing algorithm utilizes the concepts of web engineering to prioritize the request of end user using parsing technique, which will assign the resources to the end users based on the priority set by the data centers.


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