scholarly journals ALGORITHM FOR TASK CONSOLIDATION IN CLOUD COMPUTING: A COMPARATIVE SURVEY

2018 ◽  
Vol 6 (5) ◽  
pp. 340-345
Author(s):  
Rajat Pugaliya ◽  
Madhu B R

Cloud Computing is an emerging field in the IT industry. Cloud computing provides computing services over the Internet. Cloud Computing demand increasing drastically, which has enforced cloud service provider to ensure proper resource utilization with less cost and less energy consumption. In recent time various consolidation problems found in cloud computing like the task, VM, and server consolidation. These consolidation problems become challenging for resource utilization in cloud computing. We found in the literature review that there is a high level of coupling in resource utilization, cost, and energy consumption. The main challenge for cloud service provider is to maximize the resource utilization, reduce the cost and minimize the energy consumption. The dynamic task consolidation of virtual machines can be a way to solve the problem. This paper presents the comparative study of various task consolidation algorithms.

Author(s):  
Trinathbasu Miriyala ◽  
JKR Sastry

<p><span lang="EN-US">Cloud computing technologies are being used by many who need computing resources such as software, platform and infrastructure as per their business requirements in terms of provisioning and pay for the usage as per actual consumption of the services based on the SLA signed by the user and cloud service provider. Software running on a physical machine is being provided as services to the end users. For the reasons of cost economies access to software that uses a database is being provided to multiple users. The access to the software is provided either directly or through a virtual machine. The software being provided as service uses the same database for many of the users who have requisitioned for the same. As a result, there could be encroachments by the users into the data of others. There is a need to secure the data belonging to several users while all of them access the data using the same application. In this paper an efficient method is presented for securing the data processed by software which is offered as a service to multiple users either directly or through virtual machines.    </span></p>


2018 ◽  
Vol 7 (1.7) ◽  
pp. 21
Author(s):  
G Soniya Priyatharsini ◽  
N Malarvizhi

In this modern world, people are not ready to waste their time in waiting for long duration. That’s why cloud computing is such an enormous number of fans that it can be rented and also pay per use. The cloud service provider is concern about the data owner’s satisfaction in cloud usage. The main area they concentrate will be the security of the owner’s data and the resource allocation as per the request. This paper explains how the resources are efficiently allocated and scheduled to the clients. It follows four steps; firstly it identifies the active PMs. Next it defragments the identified machines. Then it balances the load along with the threshold feature to enhance the usage of the resource utilization. Finally it allocates the efficient Virtual Machines (VM) to the data owner as per the request. This is done using cloudsim along with java.


Author(s):  
Sovban Nisar ◽  
Deepika Arora

A structural design in which virtual machines are implicated and connect to the cloud service provider is called cloud computing. On the behalf of the users, the virtual machines connect to the cloud service provider. The uncertainties overload the virtual machines. The genetic algorithm is implemented for the migration of virtual machine in the earlier study. The genetic algorithm is low depicts latency within the network is high at the time of virtual machine migration. The genetic algorithm is implemented for virtual machine migration in this study. The proposed algorithm is applied in MATLAB in this work. The obtained results are compared with the results of earlier algorithm. Various parameters like latency, bandwidth consumption, and space utilization are used to analyze the achieved results.


Cloud service provider in cloud environment will provide or provision resource based on demand from the user. The cloud service provider (CSP) will provide resources as and when required or demanded by the user for execution of the job on the cloud environment. The CSP will perform this in a static and dynamic manner. The CSP should also consider various other factors in order to provide the resources to the user, the prime among that will be the Service Level Agreement (SLA), which is normally signed by the user and cloud service provider during the inception phase of service. There are many algorithm which are used in order to allocate resources to the user in cloud environment. The algorithm which is proposed will be used to reduce the amount of energy utilized in performing various job execution in cloud environment. Here the energy utilized for execution of various jobs are taken into account by increasing the number of virtual machines that are used on a single physical host system. There is no thumb rule to calculate the number of virtual machines to be executed on a single host. The same can be derived by calculating the amount of space, speed required along with the time to execute the job on a virtual machine. Based up on this we can derive the number of Virtual machine on a single host system. There can be 10 virtual machines on a single system or even 20 number of virtual machines on single physical system. But if the same is calculated by the equation then the result will be exactly matching with the threshold capacity of the physical system[1]. If more number of physical systems are used to execute fewer virtual machines on each then the amount of energy consumed will be very high. So in order to reduce the energy consumption , the algorithm can be used will not only will help to calculate the number of virtual machines on single physical system , but also will help to reduce the energy as less number of physical systems will be in need[2].


2022 ◽  
pp. 205-224
Author(s):  
Dhiviya Ram

One of the most unique forms of contracting is apparent in cloud computing. Cloud computing, unlike other conventional methods, has adopted a different approach in the formation of binding contract that will be used for the governance of the cloud. This method is namely the clickwrap agreement. Click wrap agreement follows a take it or leave it basis in which the end users are provided with limited to no option in terms of having a say on the contract that binds them during the use of cloud services. The terms found in the contract are often cloud service provider friendly and will be less favourable to the end user. In this article, the authors examine the terms that are often found in the cloud computing agreement as well as study the benefit that is entailed in adopting this contracting method. This chapter has undertaken a qualitative study that comprises interviews of cloud service providers in Malaysia. Hence, this study is a novel approach that also provides insight in terms of the cloud service provider perspective regarding the click wrap agreement.


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.


Author(s):  
Bhupesh Kumar Dewangan ◽  
Amit Agarwal ◽  
Venkatadri M. ◽  
Ashutosh Pasricha

Cloud computing is a platform where services are provided through the internet either free of cost or rent basis. Many cloud service providers (CSP) offer cloud services on the rental basis. Due to increasing demand for cloud services, the existing infrastructure needs to be scale. However, the scaling comes at the cost of heavy energy consumption due to the inclusion of a number of data centers, and servers. The extraneous power consumption affects the operating costs, which in turn, affects its users. In addition, CO2 emissions affect the environment as well. Moreover, inadequate allocation of resources like servers, data centers, and virtual machines increases operational costs. This may ultimately lead to customer distraction from the cloud service. In all, an optimal usage of the resources is required. This paper proposes to calculate different multi-objective functions to find the optimal solution for resource utilization and their allocation through an improved Antlion (ALO) algorithm. The proposed method simulated in cloudsim environments, and compute energy consumption for different workloads quantity and it increases the performance of different multi-objectives functions to maximize the resource utilization. It compared with existing frameworks and experiment results shows that the proposed framework performs utmost.


Author(s):  
Ebin Deni Raj ◽  
L. D. Dhinesh Babu

Cloud computing is the most utilized and evolving technology in the past few years and has taken computing to a whole new level such that even common man is receiving the benefits. The end user in cloud computing always prefers a cloud service provider which is efficient, reliable and best quality of service at the lowest possible price. A cloud based gaming system relieves the player from the burden of possessing high end processing and graphic units. The storage of games hosted in clouds using the latest technologies in cloud has been discussed in detail. The Quality of service of games hosted in cloud is the main focus of this chapter and we have proposed a mathematical model for the same. The various factors in dealing with the quality of service on cloud based games have been analyzed in detail. The quality of experience of cloud based games and its relation with quality of service has been derived. This chapter focuses on the various storage techniques, quality of experience factors and correlates the same with QoS in cloud based games.


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.


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