scholarly journals Dependability of the Users in Cloud Environment Using load Balancing and Integrity of Data

2019 ◽  
Vol 8 (6S) ◽  
pp. 410-416
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Distributed Computing ◽  
Load Balancing ◽  
File System ◽  
Cloud Environment ◽  
Secret Key ◽  
Remote Machine ◽  
Taking Care

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

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.

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.

scholarly journals An Attribute-Oriented Task Scheduling Strategy for Improvement of Quality of Service in Cloud Computing

2021 ◽  
Author(s):  
Jianying Miao
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Task Scheduling ◽  
Virtual Machines ◽  
Cloud Environment ◽  
Simulation Environment ◽  
Attribute Matching ◽  
Resource Allocation Strategy ◽  
And Task

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.

Performance Improvement in Cloud Computing Environment by Load Balancing-A Comprehensive Review

2021 ◽  
Vol 11 (2) ◽  
pp. 1386-1399
Author(s):  
Ramya K.
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Load Balancing ◽  
Cloud Service ◽  
Cloud Environment ◽  
Cloud Computing Environment ◽  
Consumption Cost ◽  
High Level ◽  
Near Future

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.

scholarly journals DELAY DIMINISHED EFFICIENT TASK SCHEDULING AND ALLOCATION FOR HETEROGENEOUS CLOUD ENVIRONMENT

2019 ◽  
Vol 01 (01) ◽  
pp. 51-62 ◽  
Author(s):  
Bhalaji N
Keyword(s):  
Genetic Algorithm ◽  
Cloud Computing ◽  
Quality Of Service ◽  
Task Scheduling ◽  
Cloud Environment ◽  
Wide Range ◽  
Heterogeneous Cloud ◽  
The Way

Cloud computing being a promising paradigm has become very prominent among a wide range of applications due to their timely service rendering capability. Attracted to the type of servicing and the way of servicing lots and lots of users, adapt to the cloud computing. This makes the time servicing of the cloud computing a tedious job. So in order to effectively handle the tasks the scheduling approach is entailed in the cloud computing. The paper proposes an efficient task scheduling for the heterogeneous cloud to render service at a minimized delay utilizing the genetic algorithm. The proposed method is validated through the, cloud simulator to understand the efficiency of the same in terms of delay and the quality of service.

scholarly journals Enhanced Auction Based Scheduling in Cloud Computing

2019 ◽  
Vol 8 (4S2) ◽  
pp. 764-769
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Distributed Computing ◽  
Tabu Search ◽  
Present Method ◽  
Due Date ◽  
After Effects ◽  
Cloud Management ◽  
Auction Sale

In distributed computing different cloud clients could demand number about cloud benefits all the while. Provisioning remains completed so that every resource was completed accessible in the direction of client's solicitation within an effective way toward fulfil their requirements. The present contribute dependent on interest because resources were planned based on specific arrangements. So as to battle as well as settle Virtual Machine (VM) planning issue during distributed computing, Novel Unique Tabu Search (NUTS) resource supported booking method while have its premise up auction sale method remains appeared via remembering numerous components incorporating the band with along with due date considering system as well as sale. The offers about customers were initially ordered inside the challenge due date. Besides, a displaying about the customer gathering remains completed as well as the VM resource such compares toward it remains arranged in understanding towards insignificant expense about the service suppliers. Ultimately, instalment cost remains settled via accepting normal instalment just as instalment completed via contenders into reflection in this way empowering auspicious finishing about VM resource job. The after-effects about reenactment examinations demonstrate the present method suggestion that was ready remains equipped for improving proficiently QoS otherwise Quality of Service about cloud context, and furthermore guarantee the present benefits about suppliers of cloud management as well as charge about resource usage of VMs were productively finished.

scholarly journals An Attribute-Oriented Task Scheduling Strategy for Improvement of Quality of Service in Cloud Computing

2021 ◽  
Author(s):  
Jianying Miao
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Task Scheduling ◽  
Virtual Machines ◽  
Cloud Environment ◽  
Simulation Environment ◽  
Attribute Matching ◽  
Resource Allocation Strategy ◽  
And Task

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.

Load Balancing in Heterogeneous Cluster Cloud Computing

2019 ◽  
pp. 146-169
Author(s):  
Nirmalan R. ◽  
Gokulakrishnan K. ◽  
Jesu Vedha Nayahi J.
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Research Work ◽  
Future Research ◽  
Cloud Environment ◽  
Heterogeneous Cluster ◽  
Multiple Servers ◽  
Management Of Resources ◽  
Qos Metrics

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.

scholarly journals Load Balancing in Cloud Computing

2019 ◽  
Vol 8 (6S3) ◽  
pp. 2164-2166 ◽  
Keyword(s):  
Cloud Computing ◽  
Distributed Computing ◽  
Load Balancing ◽  
Computational Models ◽  
The World ◽  
The Cost ◽  
Taking Care

Distributed computing is the best innovation today for every one of those individuals who needs to go with least speculation on foundation and needs to redistribute the weight of taking care of specialized issues to outsider by paying the charges for the administrations used. Today there is gigantic measure of interest from the customers to utilize cloud innovation as it gives various highlights and remove the heap of looking after foundation. This has made a tremendous measure of burden on servers . So it is must to deal with issues identified with load adjusting. This is essentially to see that the heap on a specific server is held most extreme to its edge level. So it can deal with the undertaking and furthermore can finish it in a quicker way. It limits the cost and time associated with the major computational models and improves appropriate usage of assets and framework execution. Numerous calculations are prescribed by different specialists from everywhere throughout the world to take care of the issue of burden adjusting. In this paper, we present another calculation named as combo calculation to address the issue of burden adjusting in a cloud situation. Catchphrases - Cloud registering improvement Load Balancing Network

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