Cloud Computing Service Quality

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System of Systems for Quality of Service Observation and Response in Cloud Computing Environments

System of Systems for Quality of Service Observation and Response in Cloud Computing Environments

The point of this review is to give an outline of early research works in the cloud QoS displaying space, arranging commitments as indicated by applicable territories and strategies utilized. Our approach endeavours to amplify scope of works, instead of surveying particular specialized difficulties or acquainting peruses with displaying methods. Specifically, we concentrate on late demonstrating works distributed from 2006 onwards concentrating on QoS in cloud frameworks. We additionally talk about a few methods initially produced for displaying and dynamic administration in big business server farms that have been progressively connected in the cloud setting. Moreover, the review considers QoS demonstrating systems for intelligent cloud administrations, for example, multi-level applications. Works concentrating on bunch applications, for example, those in view of the Map Reduce worldview, are along these lines not studied. Notwithstanding, complex frameworks that utilization distributed computing, for example, appeared in Fig. 1, are inclined to disappointment and security trade off in five principle territories .
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Quality of service in cloud computing with a profit maximization scheme

Quality of service in cloud computing with a profit maximization scheme

We consider the cloud provider platform as a multiserver approach with a carrier request queue. The clouds furnish assets for jobs in the form of virtual desktop (VM). In addition, the users post their jobs to the cloud wherein a job queuing process such as SGE, PBS, or Condor is used. All jobs are scheduled by the job scheduler and assigned to different VMs in a centralized method. Hence, we can remember it as a provider request queue. For illustration, Condor is a specialized workload administration process for compute intensive jobs and it presents a job queuing mechanism, scheduling coverage, priority scheme, resource monitoring, and useful resource administration. Customers submit their jobs to Condor, and Condor areas them right into a queue, chooses when and where to run them established upon a policy. An M/M/m+D queuing model is build for our multiserver method with various system dimension. After which, an gold standard configuration situation of profit maximization is formulated wherein many causes are taken into considerations, such as the market demand, the workload of requests, the server-level contract, the condominium cost of servers, the cost of vigor consumption, and so forth. The choicest solutions are solved for two distinctive circumstances, that are the perfect ultimate solutions and the genuine most excellent options.
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Ensuring an Efficient and Reliable Quality of Service for Customer Satisfaction in Cloud Computing

Ensuring an Efficient and Reliable Quality of Service for Customer Satisfaction in Cloud Computing

Like all business, the benefit of an authority co-op in cloud figuring is related to two segments, which are the cost and the income. For an authority co-op, the cost is the renting cost paid to the framework suppliers notwithstanding the power incurred significant injury expedited by imperativeness usage, and the wage is the administration charge to customers. At the point when all is said in done, an authority co-op rents a particular number of servers from the foundation supplier and develops unmistakable multiserver structures for different application spaces. Each multiserver structure is to execute an exceptional sort of administration sales and applications. In this way, the renting cost is in respect to the amount of servers in a multi server system. The power usage of a multiserver system is straightly relating to the quantity of servers and the server utilize, and to the square of execution speed. The pay of an authority co-op is related to the measure of administration and the idea of administration. To gather, the benefit of an authority organization is generally managed by the outline of its administration stage.
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Authorized Priority Mechanism with Guaranteed Quality of Service Orientation on Cloud Computing

Authorized Priority Mechanism with Guaranteed Quality of Service Orientation on Cloud Computing

purchased. Developers with innovative ideas for new interactive Internet services no longer require the large capital outlays in hardware to deploy their service or the human expense to operate it. They need not be concerned about over- provisioning for a service whose popularity does not meet their predictions, thus wasting costly resources, or under- provisioning for one that becomes widely popular, thus missing potential customers and revenue. Moreover, companies with large batch-oriented tasks can get their results as quickly as their programs can scale, since using 1000 servers for one hour costs no more than using one server for 1000 hours. This elasticity of resources, without paying a premium for large scale, is unprecedented in the history of IT. The economies of scale of very large-scale datacenters combined with ``pay-as-you-go'' resource usage has heralded the rise of Cloud Computing. It is now attractive to deploy an innovative new Internet service on a third party's Internet Datacenter rather than your own infrastructure, and to gracefully scale its resources as it grows or declines in popularity and revenue. Expanding and shrinking daily in response to normal diurnal patterns could lower cost even further. Cloud Computing transfers the risks of over- provisioning or under-provisioning to the Cloud Computing provider, who mitigates that risk by statistical multiplexing over a much larger set of users and who offers relatively low prices due to better utilization and from the economy of purchasing at a larger scale. We define terms, present an economic model that quantifies the key buy vs pay-as-you-go decision, offer a spectrum to classify Cloud Computing providers, and give our view of the top 10 obstacles and opportunities to the growth of Cloud Computing.
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Revenue Maximization with Good Quality of Service in Cloud Computing

Revenue Maximization with Good Quality of Service in Cloud Computing

Amazon EC2: Amazon Web Services (AWS) [3] is a set of cloud services, providing cloud-based computation, storage and other functionality that enable organizations and individuals to deploy applications and services on an on- demand basis and at commodity prices. Amazon Web Services’ offerings are accessible over HTTP, using REST and SOAP protocols. Amazon Elastic Compute Cloud (Amazon EC2) enables cloud users to launch and manage server instances in data centers using APIs or available tools and utilities. EC2 instances are virtual machines running on top of the Xen virtualization engine [5]. After creating and starting an instance, users can upload software and make changes to it. When changes are finished, they can be bundled as a new machine image. An identical copy can then be launched at any time. Users have nearly full control of the entire software stack on the EC2 instances that look like hardware to them.
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Quality-of-service in cloud computing: modeling techniques and their applications

Quality-of-service in cloud computing: modeling techniques and their applications

In the context of cloud computing, we have more application examples of Petri nets nets for dependability assessment, than for performance modeling. Applica- tions to cloud QoS modeling include the use of SPNs to evaluate the dependability of a cloud infrastructure [68], considering both reliability and availability. SPNs provide a convenient way in this setting to represent energy flow and cooling in the infrastructure. Wei et al. [69] proposes the use of GSPNs to evaluate the impact of virtualization mechanisms, such as VM consolidation and live migration, on cloud infrastructure dependability. GSPNs are used to provide fine-grained detail on the inner VM behaviors, such as separation of privileged and non-privileged instructions and successive handling by the VM or the VM monitor. Petri nets are here used in combination with other methods, i.e., Reliability Block Diagrams and Fault Trees, for analyzing mean time to failure (MTTF) and mean time between failures (MTBF).
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A Survey on Assured of Quality Service with Profit Maximization in Cloud Computing

A Survey on Assured of Quality Service with Profit Maximization in Cloud Computing

association of service profit and consumer loyalty. Moreover, we show two planning calculations that can viably offer for various sorts of VM occasions to make tradeoff amongst profit and consumer loyalty. We direct broad reproductions in light of the execution information of various sorts of Amazon EC2 cases and their value history. Our test comes about exhibit that the calculations perform well over the measurements of profit, consumer loyalty and example usage. In paper [7] creator clarified Power-mindful planning lessens CPU vitality utilization in hard continuous frameworks through dynamic voltage scaling (DVS). The essential thought of force mindful booking is to discover slacks accessible to undertakings and decrease CPU's recurrence or lower its voltage utilizing the discovered slacks. In this paper, we present transient workload of a framework which indicates what amount occupied its CPU is to finished the assignments at current time. Examining transient workload gives an adequate state of schedulability of preemptive early-due date first booking and a compelling strategy to distinguish and appropriate slacks created by early finished errands. The recreation comes about demonstrate that proposed calculation lessens the vitality utilization by 10-70% over the current calculation and its calculation multifaceted nature is O(n). Along these lines, useful on-line scheduler could be conceived utilizing the proposed calculation.
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Profit Maximization Mechanism with Guaranteed Quality of Service in Cloud Computing

Profit Maximization Mechanism with Guaranteed Quality of Service in Cloud Computing

A pricing model is developed for cloud computing which takes many factors into considerations, such as the requirement r of a service, the workload of an application environment, the configuration (m and s) of a multi-server system, the service level agreement c, the satisfaction (r ands0) of a consumer, the quality (W and T) of a service, the penalty d of a low-quality service, the cost of renting, the cost of energy consumption, and a service provider’s margin and profit. And this will schedules the job according to optimization of speed and size of the input hereby maximizing the profit.
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Brief Comparison Of Cloud’s Emerging Services: A Literature Review

Brief Comparison Of Cloud’s Emerging Services: A Literature Review

structure IT strategy, design, transition, operation and continuous service improvement. Cloud Computing has revolutionized the method several organizations operate and provides another worth for performance management and computing. There are reported edges like gracefulness, consolidation of resources, business opportunities and green IT [29]. There area unit things wherever organizations will improve their potency, technical potency, and quality of exploitation or accepted Cloud Computing services because of a mixture of mature technologies like visual, net services, knowledge retrieval, massive processing, visualization, storage and backup, high performance computation, API for mobile devices and Cloud Computing. Therefore, this makes for a remarkable consider understanding what styles of services area unit provided and what their offerings could offer. Among different existing and new services, some provide further price and innovation. for instance, Weather visualization as a Service could enable the overall public to grasp the world temperature distribution at identical time [30]. Healthcare information science as a Service permits scientists to grasp the quality of genes, proteins, DNA, tumors and human organs like the brain and heart [31]. Business Intelligence as a Service permits researchers and money consultants to calculate risk and come in real time and recommends best practices supported knowledge analysis. Integrated with package Analytics and package as a Service ________________________
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Cost Maximization Scheme with Guaranteed Quality of Service in Cloud Computing

Cost Maximization Scheme with Guaranteed Quality of Service in Cloud Computing

(SLA). In the event that organization provider gave the nature of administration with ensured nature of administration at that point, the administration is completely charged, something else, the specialist organization serves the demand for nothing as a punishment of low quality. To acquire higher income, an organization provider should lease more servers from the framework suppliers/base providers or scale up the server execution speed to guarantee that more administration demands are handled with high administration quality. Be that as it may, doing this would prompt sharp increment of the leasing cost or the power cost. In any case, expanded cost may pick up punishment lessening. Taking everything into account, the single leasing plan isn't a decent plan for specialist co-ops. In this paper, we propose a novel leasing plan for specialist organizations, which can fulfill nature of-benefit prerequisites, as well as can acquire more benefit.
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CLOUD IMPLEMENTATION IN EMERGING MARKET BANKS: THE IMPORTANCE OF SERVICE QUALITY

CLOUD IMPLEMENTATION IN EMERGING MARKET BANKS: THE IMPORTANCE OF SERVICE QUALITY

The service requirements for a cloud project are the same for a legacy system. Technical support is required 24x7 for maintenance and OS issues. The service level agreement for cloud projects is also the same as a general service contract. The SLA specifies requirements to achieve specific KPIs – repair in 4 hours or helpdesk in 15 minutes. Because of the high investment in the cloud system any delay is very costly. The SLA is the most important factor in the IT executive’s decision to choose an IT service provider for the cloud project. The IT cloud provider is responsible for the design; development and technology transfer for the cloud project. It is also expected that maintenance will also be provided. The IT provider is expected to maintain the continuity of the bank through preventive maintenance and problem solving a service interruption. It is important that the IT service provider can integrate the existing IT infrastructure with the cloud system. Service quality for the IT executive includes tangibility, reliability, timeliness, and assurance. The decision criteria are based more on comprehensive performance rather than only cost criteria. The cloud provider who can provide the integration of the legacy and cloud computing systems will have advantage. This includes proactive planning, guidance for operational practices and security. The cloud provider needs experience in banking. They should be responsive, flexible and adaptive. Collaboration is a major influence on the IT executive decision to choose a cloud provider.
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Customer Satisfaction Aware Scheduling For Utility Maximization in Cloud Computing

Customer Satisfaction Aware Scheduling For Utility Maximization in Cloud Computing

As cloud computing becomes more and more popular, understanding the economics of cloud computing becomes critically important. To maximize the profit, a service provider should understand both service charges and business costs, and how they are determined by the characteristics of the applications and the configuration of a multiserver system. The problem of optimal multiserver configuration for profit maximization in a cloud computing environment is studied. Our pricing model takes such factors into considerations as the amount of a service, the workload of an application environment, the configuration of a multiserver system, the service-level agreement, the satisfaction of a consumer, the quality of a service, the penalty of a low-quality service, the cost of renting, the cost of energy consumption, and a service provider's margin and profit. Our approach is to treat a multiserver system as an M/M/m queuing model, such that our optimization problem can be formulated and solved analytically. Two server speed and power consumption models are considered, namely, the idle-speed model and the constant-speed model. The probability density function of the waiting time of a newly arrived service request is derived. The expected service charge to a service request is calculated. The expected net business gain in one unit of time is obtained. Numerical calculations of the optimal server size and the optimal server speed are demonstrated.
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Components of service value in business-to-business Cloud Computing

Components of service value in business-to-business Cloud Computing

This study contributes to our understanding of the com- ponents associated with service value in the context of B2B cloud computing. This understanding is most im- portant from the perspective of the business customers. In addition, this research underscores issues of signifi- cance to IT decision-makers responsible for creating, measuring and managing the service value perceptions of IT-related services (e.g., cloud computing services). This study also supports the idea that cloud computing service providers, providing cloud services to other busi- nesses, can differentiate themselves and add value by having a greater understanding of what their business customers expect from the respective cloud services that they provision. In the current environment, that there are leading cloud providers and emerging competitors, the respective managers may now direct their efforts (e.g., marketing, product development and recruitment) towards increased service value that will enhance their organisation’s market leadership. This new understand- ing of service value components helps business cus- tomers of cloud computing to evaluate the importance of specific components during the decision-making process of repurchasing or continuing on with the current cloud service. Customers would now have a bet- ter understanding that service quality of any cloud com- puting provider is most significant during the evaluation process. Furthermore, customers will be reminded that while the branding (i.e., service equity) of a respective provider is important, this specific component will have to be managed well. Finally, customers have been articu- lating the importance of data security, data sovereignty, and service level agreements, referring to the additional component on cloud service governance. Customers would increasingly ensure that the provision of cloud services from their respective providers would adhere to appropriate processes.
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Cloud Computing in Libraries and Higher Education: An Innovative User Centric Quality of Service Model

Cloud Computing in Libraries and Higher Education: An Innovative User Centric Quality of Service Model

One of the emerging trends has been to move away from investing in physical server "hardware" and lean more towards the use of environments in the "cloud," thus providing broader access to products and services libraries acquire or subscribe to, or research data that libraries collect to support the higher education and research needs of their user base. This trend has been on the rise since the library budgets went on the decline in mid to late 2000’s. Such moves can be attributed to the need to save costs (hardware, technical support), the need for innovative flexibility, the need for libraries to become more of a community-run resource exploiting the wide and deep technical knowledge-base, the need to increase accessibility of library resources via OPACs (Online Public Access Catalogues) supported by cloud-hosted systems, and finally, the need to ensure libraries are constantly in sync with emerging technologies. Cloud Computing is an approach where Information Technology capabilities and services are delivered to the users through the Internet by a service provider [1]. Users only pay for the service they use [2]. Almost all cloud service providers charge for cycles or time used and an accounting or billing method is required based on the terms of the contract before using or providing the service. Cloud computing is becoming a necessity gradually as it is now frequently used by all linked with higher education, including students and instructors, and is increasingly being adopted worldwide. Sharing study or research material via the cloud or using the cloud to process large sets of data for scholarly research is starting to become the norm. Most of it is due to the micro-services structure offered by the cloud service providers which allows managing information and related transactions more efficiently.
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A SURVEY ON QUALITY OF SERVICE IMPLEMENTATIONS IN CLOUD COMPUTING

A SURVEY ON QUALITY OF SERVICE IMPLEMENTATIONS IN CLOUD COMPUTING

Cloud computing is a new terminology achieved by distributed, parallel and grid computing and a design pattern for large, distributed data centers. Cloud computing offers end customers a pay as go model. Quality of service plays an important factor in distributed computing. Cloud computing provides different types of resources like hardware and software as service via internet. Under cloud computing, computing resources are hosted in the internet and delivered to customers as services. Prior to that, the customers and cloud provider negotiate and enter into an agreement named service level agreement. The service level agreements clarify the roles, set charges and expectations and provide mechanisms for resolving service named problems within a specified and agreed upon time period. Service level agreements also cover performance, reliability conditions in terms of quality of service guarantees. In this paper, the authors present a comprehensive survey on quality of service implementations in cloud computing with respect to their implementation details, strengths and weaknesses.
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A Review paper on CPU Scheduling in Cloud Environment

A Review paper on CPU Scheduling in Cloud Environment

Akilandeswari. P and H. Srimathi (2016) [21] described “Cloud computing was utility based environment as pay per use model achieved by Parallel, Distributed and Cluster computing accessed through the Internet. A key advantage of cloud computing is on- demand self-service, scalability, and elasticity. In on- demand self-service, the cloud user can request, deploy their own software, customize and pay for their own services. Scalability is achieved through virtualization. Being elastic in nature, cloud service gives the infinite computing resources (CPU, Memory, Storage).In cloud environment to achieve the quality of service many scheduling algorithms are available, but the scalability of task execution increases, scheduling becomes more complex. So there is a need for better scheduling. This paper deals with the survey of dynamic scheduling, different classification and scheduling algorithms currently used in cloud providers”.
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Research on Profit Maximization Scheme with Guaranteed Quality of Service in Cloud Computing

Research on Profit Maximization Scheme with Guaranteed Quality of Service in Cloud Computing

Distributed computing is rapidly turning into a compelling and productive method for registering assets. By brought together administration of assets and administrations, distributed computing conveys facilitated administrations over the Internet. Distributed computing can give the most financially savvy and vitality productive method for figuring assets administration. Distributed computing transform's data innovation into normal things and utilities by utilizing the pay-per-use estimating model. An administration supplier rents assets from the foundation sellers, fabricates suitable multi server frameworks, and gives different administrations to clients.[6] A customer presents an administration solicitation to an administration supplier, gets the wanted result from the administration supplier with certain administration level assertion. At that point pays for the administration taking into account the measure of the administration and the nature of the administration. An administration supplier can fabricate diverse multi server frameworks for various application areas, such that administration solicitations of various natures are sent to various multi server frameworks. Inferable from repetition of PC framework systems and capacity framework cloud may not be solid for information, the security score is concerned.[2] In distributed computing security is massively enhanced on account of a predominant innovation security framework, which is currently effortlessly accessible and reasonable. Applications no more keep running on the desktop Personal Computer yet keep running in the cloud. This implies the PC does not require the preparing power or hard circle space as requested by customary desktop programming. Effective servers and so forth are no more required. The registering force of the cloud can be utilized to supplant or supplement inner figuring assets. Associations no more need to buy registering assets to handle the limit crests.[9]
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A Review paper on CPU Scheduling in Cloud Environment

A Review paper on CPU Scheduling in Cloud Environment

Akilandeswari. P and H. Srimathi (2016) [21] described “Cloud computing was utility based environment as pay per use model achieved by Parallel, Distributed and Cluster computing accessed through the Internet. A key advantage of cloud computing is on- demand self-service, scalability, and elasticity. In on- demand self-service, the cloud user can request, deploy their own software, customize and pay for their own services. Scalability is achieved through virtualization. Being elastic in nature, cloud service gives the infinite computing resources (CPU, Memory, Storage).In cloud environment to achieve the quality of service many scheduling algorithms are available, but the scalability of task execution increases, scheduling becomes more complex. So there is a need for better scheduling. This paper deals with the survey of dynamic scheduling, different classification and scheduling algorithms currently used in cloud providers”.
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A Survey on Profit Maximization Scheme with Guaranteed Quality of Service in Cloud Computing

A Survey on Profit Maximization Scheme with Guaranteed Quality of Service in Cloud Computing

can be utilized to supplant or supplement inward figuring assets. Associations no more need to buy processing assets to handle the limit crests. Cloud computing is rapidly turning into a viable and productive method for figuring assets. By brought together administration of assets and administrations, Cloud computing conveys facilitated administrations over the Internet. Cloud computing can give the most financially savvy and vitality effective method for registering assets administration. Cloud computing transform's data innovation into conventional items and utilities by utilizing the pay-per-use estimating model. An administration supplier rents assets from the framework sellers, fabricates suitable multi server frameworks, and gives different administrations to clients. A purchaser presents an administration solicitation to an administration supplier, gets the coveted result from the administration supplier with certain administration level assention. At that point pays for the administration taking into account the measure of the administration and the nature of the administration. An administration supplier can assemble diverse multi server frameworks for various application spaces, such that administration solicitations of various nature are sent to various multi server frameworks. Inferable from excess of PC framework systems and capacity framework cloud may not be solid for information, the security score is concerned. In Cloud computing security is enormously enhanced in view of a prevalent innovation security framework, which is presently effectively accessible and moderate. Applications no more keep running on the desktop Personal Computer however keep running in the cloud. This implies the PC does not require the preparing power or hard circle space as requested by conventional desktop programming. Effective servers and so forth are no more required. The figuring force of the cloud can be utilized to supplant or supplement interior registering assets. Associations no more need to buy registering assets to handle the limit crests.
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OPTIMIZING COMMUNICATION AND COOLING COSTS IN HPC DATA CENTER

OPTIMIZING COMMUNICATION AND COOLING COSTS IN HPC DATA CENTER

Cloud computing is one of device technology trends in the future since it combines the advantages of both device computing and cloud, Recent years have seen the massive migration of enterprise applications to the cloud. Cloud computing used in business organizations and educational institutions. One of the challenges posed by cloud applications is Quality-of-Service (QoS) management, which is the problem of allocating resources to the application to guarantee a service level along dimensions such as performance, availability and reliability. To improve the QoS in a system one must need to reduce the waiting time of the system. Genetic Algorithm (GA) is a heuristic search technique which produces the optimal solution of the tasks. This work produces one scheduling algorithm based on GA to optimize the waiting time of overall system. The cloud environment is divided into two parts mainly, one is Cloud User (CU) and another is Cloud Service Provider (CSP). CU sends service requests to the CSP and all the requests are stored in a Request Queue (RQ) inside CSP which directly communicates with GA Module Queue Sequencer (GAQS). GAQS perform background operation, like daemon, with extreme dedication and selects the best sequence of jobs to be executed which minimize the Waiting time (WT) of the tasks using Round Robin (RR) scheduling Algorithm and store them into Buffer Queue (BQ). Then the jobs must be scheduled by the Job Scheduler (JS) and select the particular resource from resource pool (RP) which it needs for execution.
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