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Cloud services means that services created offered to users on demand via the web from a cloud computing provider's servers as against being provided from a company's own on-premises servers. Cloud services are designed to produce simple, climbable access to applications, resources and services, and are totally managed by a cloud services supplier. A cloud service will dynamically scale to satisfy the wants of its users, and since the service supplier provides the hardware and package necessary for the service, there’s no would like for a corporation to provision or deploy its own resources or allot IT workers to manage the service. samples of cloud services embrace on-line knowledge storage and backup solutions, Web-based e-mail services, hosted workplace suites and document collaboration services, info process, managed technical support services and a lot of.
A cloud service is any resource that's provided over the web. the foremost common cloud service resources are package as a Service (SaaS), Platform as a Service (PaaS) and Infrastructure as a Service (IaaS). SaaS could be a package distribution model during which applications are hosted by a seller or service supplier and created offered to customers over a network, generally the web. PaaS refers to the delivery of operative systems and associated services over the web while not downloads or installation. IaaS involves outsourcing the instrumentation accustomed support operations, together with storage, hardware, servers and networking parts, all of that are created accessible over a network. SaaS, PaaS and IaaS are typically stated together because the SPI model. Cloud services are constant factor as net services. However, the term cloud services has been a lot of usually used as cloud computing has become a lot of pervasive.
Cloud computing is an emerging technology in the IT world. Some features of cloud, such as low cost, scalability, robustness and availability are attracting large-scale industries as well as small business towards cloud. A virtual machine (VM) can be defined as a software that can run its own operating systems and applications like an operating system in physical computer. As the number of users increases, allocation of resources and scheduling become a complex task. The optimization of VM provisioning policies offer improvement like increasing provider's profit, energy savings and load balancing in large data centres. In cloud computing when resource requirement of user's requests exceed resources limits of cloud provider, to fulfil the requests the cloud provider outsources to other cloud providers resources, this concept is known as cloud federation. In this paper we propose an algorithm for VM provisioning in federated cloud environment. The approach tries to improve the cloud providers profit. We have used the CloudSim to find-out the results and result show that how Cloud federation help to Cloud providers in order to improve its profit.
As an increasing number of infrastructure-as-a-service (IaaS) cloud providers start to provide cloud computing services, they form a competition market to compete for users of these services. Due to different resource capacities and service workloads, users may observe different finishing times for their cloud computing tasks and experience different levels of service qualities as a result. To compete for cloud users, it is critically important for each cloud service provider to select an "optimal" price that best corresponds to their service qualities, yet remaining attractive to cloud users. To achieve this goal, the underlying rationale and characteristics in this competition market need to be better understood. In this paper, we present an in-depth game theoretic study of such a competition market with multiple competing IaaS cloud providers. We characterize the nature of non cooperative competition in an IaaS cloud market, with a goal of capturing how each IaaS cloud provider will select its optimal prices to compete with the others. Our analyses lead to sufficient conditions for the existence of a Nash equilibrium, and we characterize the equilibrium analytically in special cases. Based on our analyses, we propose iterative algorithms for IaaS cloud providers to compute equilibrium prices, which converge quickly in our study.
Typically in collaborative cloud systems, the collaborations are formed based on pre-negotiated terms and conditions. Care is taken to ensure that the resources are planned in such a way so as to satisfy the SLA requirements. However, these static collaborations pose certain challenges in the long run, which arise due to the changes in quality of resources and provider capabilities. In such a scenario, there is a need to dynamically establish appropriate collaborations so as to back-fill the resource quality and overcome shortfalls in provider capabilities. Our paper puts forth a mathematical model for cloud provider capabilities along with an approach to establish dynamic cloud provider collaborations. In our approach, once the under functioning resource is identified, we are able to find the most suitable replacement resource from within the same cloud provider or if need be, establish a new collaboration with another provider based on the required resource capabilities. This choice for new collaboration is based on the tenancy requirements, current state of resource utilization and capacity, and health of the specific resource to be replaced. Our algorithms to determine the replacement resource and form the collaboration links are illustrated along with a running example and proof-of-concept implementation.
Cloud computing is quickly becoming the next wave of technological evolution as a new approach to providing IT capabilities needed by business. Driving interest and investment in cloud computing is the revolutionary change to the economic model. Cloud computing also promises to allow IT to respond more quickly to the needs of the business. Key tenets of cloud computing include being on-demand and self-service. This shift to the way that a business engages IT services creates new challenges including regulating how internal business units purchase cloud services. How does a business assess cloud providers services for security, privacy, and service levels? The purpose of this study is to develop an instrument for evaluating a cloud provider's transparency of security, privacy, and service level competencies via its self-service web portals and web publications, and then to empirically evaluate cloud service providers to measure how transparent by using the instrument.
The number of online real-time streaming services deployed over network topologies like P2P or centralized ones has remarkably increased in the recent years. This has revealed the lack of networks that are well prepared to respond to this kind of traffic. A hybrid distribution network can be an efficient solution for real-time streaming services. This paper contains the experimental results of streaming distribution in a hybrid architecture that consist of mixed connections among P2P and Cloud nodes that can interoperate together. We have chosen to represent the P2P nodes as Planet Lab machines over the world and the cloud nodes using a Cloud provider's network. First we present an experimental validation of the Cloud infrastructure's ability to distribute streaming sessions with respect to some key streaming QoS parameters: jitter, throughput and packet losses. Next we show the results obtained from different test scenarios, when a hybrid distribution network is used. The scenarios measure the improvement of the multimedia QoS parameters, when nodes in the streaming distribution network (located in different continents) are gradually moved into the Cloud provider infrastructure. The overall conclusion is that the QoS of a streaming service can be efficiently improved, unlike in traditional P2P systems and CDN, by deploying a hybrid streaming architecture. This enhancement can be obtained by strategic placing of certain distribution network nodes into the Cloud provider infrastructure, taking advantage of the reduced packet loss and low latency that exists among its datacenters..
The number of online real-time streaming services deployed over network topologies like P2P or centralized ones has remarkably increased in the recent years. This has revealed the lack of networks that are well prepared to respond to this kind of traffic. A hybrid distribution network can be an efficient solution for real-time streaming services. This paper contains the experimental results of streaming distribution in a hybrid architecture that consist of mixed connections among P2P and Cloud nodes that can interoperate together. We have chosen to represent the P2P nodes as Planet Lab machines over the world and the cloud nodes using a Cloud provider's network. First we present an experimental validation of the Cloud infrastructure's ability to distribute streaming sessions with respect to some key streaming QoS parameters: jitter, throughput and packet losses. Next we show the results obtained from different test scenarios, when a hybrid distribution network is used. The scenarios measure the improvement of the multimedia QoS parameters, when nodes in the streaming distribution network (located in different continents) are gradually moved into the Cloud provider infrastructure. The overall conclusion is that the QoS of a streaming service can be efficiently improved, unlike in traditional P2P systems and CDN, by deploying a hybrid streaming architecture. This enhancement can be obtained by strategic placing of certain distribution network nodes into the Cloud provider infrastructure, taking advantage of the reduced packet loss and low latency that exists among its datacenters. .
The erosion of trust boundaries already happening in organizations is amplified and accelerated by Cloud computing. One of the most important security challenges is to manage and assure a secure Cloud usage over multi-provider Inter-Cloud environments with dedicated communication infrastructures, security mechanisms, processes and policies. This paper focuses on the identification of functions for different roles within future Inter-Cloud environments that belongs to the Cloud Security Management functional spectrum. Therefore, we describe all identified functional aspects and the distribution of these objects in order to define a platform independent model for the Security Management functional spectrum for Inter-Cloud called SMICS. SMICS will assist Cloud providers to analyze the necessary further development for their security management systems in order to support future Inter-Cloud environments. In addition, the better comprehension of the security management spectrum from a functional perspective will enable the Cloud provider community to design more efficient portals and gateways between Inter-Cloud providers itself respective their customer, and facilitate the adoption of this results in scientific and standardization environments.
This paper studies a cloud computing market where a cloud provider rents a set of computing resources from Windows Azure operated by Microsoft. The cloud provider can integrate value-added services to the resources. Then, the services can be sold to customers, and the cloud provider can earn a profit. Moreover, the cloud provider could save much cost and increase higher profit with the 6-month subscription plan offered by Windows Azure. However, the maximization of profit is not trivial to be achieved since the amount of the customers' demand cannot be perfectly known in advance. Consequently, the subscription plan could not be optimally purchased. To deal with such a maximization problem, the paper proposes a stochastic programming model with two-stage recourse. The numerical studies show that the model can maximize the profit under the customers' demand uncertainty..
This paper represents an analytical economic cost model for cloud computing aiming at comprising all kinds of cost of a commercial environment. To extend conventional state-of- the-art models considering only fixed cost, we developed a concise, but comprehensive analytical model which does not only include fixed cost, but also variable cost allowing for the development and evaluation of business strategies for cloud environments. These strategies can be used for both, cloud providers and cloud consumers. The major goal of our model is to comprise all important economic fundamentals and methods. Thus, this new model supports the decision-making process to be applied with business cases and enables cloud consumers and cloud providers to determine their own business strategies and to analyze the respective impact on their business. Based on this model, the energy efficiency of cloud systems can also be evaluated according to chosen business models.
Cloud computing is an emerging technology in the IT world. Some features of cloud, such as low cost, scalability, robustness and availability are attracting large-scale industries as well as small businesses towards cloud. A virtual machine (VM) is a software that can run its own operating system and applications just like an operating system on a physical computer. As the number of users increases, allocation of resources and scheduling become a complex task in a cloud. In a federated cloud environment when resource requirements of user requests exceed resource limits of cloud provider, to fulfil the requests the cloud provider can out-source to other cloud providers' resources. Under these circumstances it is desirable to minimize the Service Level Agreement (SLA) violations. This can be achieved through load balancing. This paper proposes a load balancing algorithm that is threshold based. We consider two types of pricing models for VMs, on-demand and reserved. Simulation results show that the proposed algorithm reduces the SLA violations.
Cloud federation has been proposed as a new paradigm that allows providers to avoid the limitation of owning only a restricted amount of resources, which forces them to reject new customers when they have not enough local resources to fulfill their customers' requirements. Federation allows a provider to dynamically outsource resources to other providers in response to demand variations. It also allows a provider that has underused resources to rent part of them to other providers. Both things could make the provider to get more profit when used adequately. This requires that the provider has a clear understanding of the potential of each federation decision, in order to choose the most convenient depending on the environment conditions. In this paper, we present a complete characterization of providers' federation in the Cloud, including decision equations to outsource resources to other providers, rent free resources to other providers (i.e. insourcing), or shutdown unused nodes to save power, and we characterize these decisions as a function of several parameters. Then, we demonstrate in the evaluation section how a provider can enhance its profit by using these equations to exploit federation, and how the different parameters influence which is the best decision on each situation..
As Cloud Computing is an emerging field, many improvements are being proposed to provide users with better services and facilities. This paper deals with the illusion of infinite resource availability on demand, one of the aspect in Cloud Computing. A new approach has been discussed here to continue providing this illusion. This work provides an efficient way for the cloud provider to decide on his strategies to execute a job i.e., whether to use his own services to execute (self-execute) or to pay rent to other cloud providers. A utility function has been formulated that considers the factors related to resource requirement, execution time and waiting probability. Further, a combination of forecasting models and game theoretic approaches have been proposed to identify the best strategy based on the values from this utility function. The design considers both the previous as well as current demand to decide on the provider's strategy so as to make the results more accurate. The results obtained show an almost equal distribution of Rent and Self-execute strategies.
Cloud provider assessment is important for cloud consumers to determine, when outsourcing computing work, which providers can serve their business and system requirements. This paper presents an initial attempt to assess security requirements compliance of cloud providers by following the Goal Question Metric approach and defining a weighted scoring model for the assessment. The security goals and questions that address the goals are taken from Cloud Security Alliance's Cloud Controls Matrix and Consensus Assessments Initiative Questionnaire. We then transform such questions into more detailed ones and define metrics that help provide quantitative answers to the transformed questions based on evidence of security compliance provided by the cloud providers. The scoring is weighted by quality of evidence, i.e. its compliance with the associated questions and its completeness. We propose a scoring system architecture which utilizes CloudAudit and assess Amazon Web Services as an example.
Auctioning constitutes a market-driven scheme for the allocation of cloud-based computing capacities. It is practically applied today in the context of Infrastructure as a Service offers, specifically, virtual machines. However, the maximization of auction profits poses a challenging task for the cloud provider, because it involves the concurrent determination of equilibrium prices and distribution of virtual machine instances to the underlying physical hosts in the data center. In the work at hand, we propose an optimal approach, based on linear programming, as well as a heuristic approach to tackle this Equilibrium Price Auction Allocation Problem (EPAAP). Through an evaluation based on realistic data, we show the practical applicability and benefits of our contributions. Specifically, we find that the heuristic approach reduces the average computation time to solve an EPAAP by more than 99.9%, but still maintains a favorable average solution quality of 96.7% in terms of cloud provider profit, compared to the optimal approach.
The purpose of this study is to investigate the cloud computing service security and access, by taking into account the service provider, and the customer's concerns. New trends of challenges from the two types of concerns are identified based on literature review. Especially, strategies to deal with the challenges in the mobile environment are proposed. It is expected that practitioners will be able to systematically consider the cloud provider, service provider and the customers' concern, in order to integrate as well as balance the need for cloud computing security and access. .
This paper presents a novel economic model to regulate capacity sharing in a federation of hybrid cloud providers (CPs). The proposed work models the interactions among the CPs as a repeated game among selfish players that aim at maximizing their profit by selling their unused capacity in the spot market but are uncertain of future workload fluctuations. The proposed work first establishes that the uncertainty in future revenue can act as a participation incentive to sharing in the repeated game. We, then, demonstrate how an efficient sharing strategy can be obtained via solving a simple dynamic programming problem. The obtained strategy is a simple update rule that depends only on the current workloads and a single variable summarizing past interactions. In contrast to existing approaches, the model incorporates historical and expected future revenue as part of the virtual machine (VM) sharing decision. Moreover, these decisions are not enforced neither by a centralized broker nor by predefined agreements. Rather, the proposed model employs a simple grim trigger strategy where a CP is threatened by the elimination of future VM hosting by other CPs. Simulation results demonstrate the performance of the proposed model in terms of the increased profit and the reduction in the variance in the spot market VM availability and prices.
The objective of this research is to evaluate the risk of cloud computing in Indonesia. Risk assessment is conducted on the system and recommendation of control is provided to help cloud provider in Indonesia to reduce risks. The assessment result should increase level of awareness to threats in cloud environment and help consumers to choose the right cloud providers. At the end, this paper can be used as a guide for Indonesian government to prepare the required infrastructure by cloud providers to run their business in Indonesia.
Cloud Computing is a new computing paradigm. Among the incredible number of challenges in this field two of them are considered of great relevance: SLA management and Security management. The level of trust in such context is very hard to define and is strictly related to the problem of management of SLA in cloud applications and providers. In this paper we will try to show how it is possible, using acloud-oriented API derived from the mOSAIC project, to build up an SLA-oriented cloud application which enables the management of security features related to user authentication and authorization to an Infrastructure as a Service (IaaS) Cloud Provider. As Cloud Provider we will adopt the perf-Cloudsolution, which uses GRID-based solutions for security management and service delivery. So the proposed solution can be used in order to build up easily a SLA-based interface for any GRID system.
A main incentive in favor of migrating to the cloud is delegating the management of large volumes of data to cloud providers. To make the notion of data cloud successful, providers must ensure availability, reliability, and data integrity among other qualities. Few researches so far have addressed the potential benefits data cloud provisioning can offer for energy efficiency. In this case study carried out in a multi-national telecommunication organization, we investigate under which circumstances delegating data management to the cloud can add value to cloud customers, in terms of both energy consumption (hence efficiency) and cost when archiving data in the cloud. Results show that data cloud migration is beneficial only if consumers yield certain characteristics in terms of type of data, retention period, and frequency of usage. We design a framework called “Value of Energy framework”, that estimates wastes in the way a company manages data, and hence identify what data can and should be migrated to acloud provider.
Cloud computing's transition from a subject of research and innovation to a critical infrastructure is proceeding incredibly quickly. One potentially dangerous consequence of this speedy transition is the premature adoption and ossification of the models, technologies, and standards underlying this critical infrastructure. Further exacerbating this issue, innovative research on production-scale platforms is becoming the purview of just a few public cloud providers. Specifically, academic research communities are effectively excluded from contributing meaningfully to the evolution--not to mention innovation and healthy mutation--of cloud computing technologies. As our society and economy's dependency on cloud computing increases, so does the realization that the academic research community can't be shut out from contributing to the design and evolution of this critical infrastructure. Here, the authors provide an alternative vision--the Open Cloud Exchange (OCX), a public cloudmarketplace in which many stakeholders, rather than just a single cloud provider, participate in implementing and operating the cloud. This will create an ecosystem to bring the innovation of a broader community to bear on a much healthier and more efficient cloud marketplace.
Nowadays, a typical scenario in the panorama of cloud computing includes an IaaS cloud provideroffering on-demand VM hosting services to its clients. In this field, famous examples of large scale commercial providers are Amazon and Rackspace. However, how to arrange analogous providers with open source tools is not totally clear. Moreover, the integration between an IaaS cloud middleware with third party legacy software systems, today, represents a difficult task to accomplish. CLEVER is an open source cloud IaaS middleware allowing the allocation and management of VMs. In this paper, through the development of a REST interface, we discuss how a CLEVER-based cloud provider can be integrated with third party systems, hence satisfying their VM allocation requests..
We consider geographically distributed datacenters forming a collectively managed cloud computing system. Multiple SaaS providers host their SOA-based, context-aware applications in the cloud. Typically, the context-aware applications serve multiple classes of customers (end users) classified on economic considerations, which determine the Quality of Service (QoS) received by each class. This need for differentiated QoS for each customer class is incorporated into a Service Level Agreement (SLA) negotiated between the context-aware application provider and the cloud provider. A QoS metric that has been explored in large distributed applications is the percentile of response times, this metric provides a form of guarantees on the shape of the response time distribution for the customer. Typical SLAs require the response time of a certain percentile of the input requests from particular classes of customers to be less than a specified value, if this value is exceeded, a penalty is charged to the cloudprovider. In addition, the applications we consider are data-intensive with strict temporal order constraints that have to be enforced on requests within the same session of a customer. We propose Data-aware Session-grained Allocation with gi-FIFO Scheduling (DSAgS), a novel decentralized request management scheme deployed in each of the geographically distributed datacenters, to globally reduce the penalty charged to the cloud computing system. Our simulation evaluation shows that our dynamic scheme far outperforms commonly deployed management policies (typically employing static or random allocation with First In First Out, Weighted Round Robin or dynamic priority-based scheduling). We further optimize our solution for dynamic, data-intensive context-aware applications, by proposing a "context level" cache replacement policy. Our evaluation shows that, when used in conjunction with DSAgS, the replacement policy decreases the total penalty charged to the cloud..
Cloud computing has emerged as a new paradigm, which is the long-held dream of computing as utility, customer get it on an on-demand model. When discuss about performance requirement and QoS (Quality of Service) of service, it is hard to tackle these problem in a round consideration. In this work we propose an SLA-aware (Service Level Agreement aware) framework cloud service provider (CSP) for cloud service (cloud infrastructure) delivery, and making allowance for the benefit of stakeholder ofcloud service provider and service consumer. By using our proposed system and hierarchy SLA monitoring model we reached our win-win objective which is maximum revenue of cloud provider and minimum SLA violation.
Cloud computing provides users and companies a cost-efficient and flexible service. However, for acloud computing client, one of most worrying problems is that IT infrastructure is under control of thecloud provider. To secure cloud users' computation, efficient remote attestation protocol is required. In this paper, by combining trusted computing and dynamic accumulators, we put forward an anonymous remote attestation scheme for cloud computing service provider. Under the help of online or offline trusted third parties, a user can attest remote trusted nodes and establish a secure communication. In addition, the scheme can also protect privacy of trusted nodes and greatly reduce the cost of storage and management.
Cloud storage is an emerging service model that enables individuals and enterprises to outsource the storage of data backups to remote cloud providers at a low cost. However, cloud clients must enforce security guarantees of their outsourced data backups. We present Fade Version, a secure cloudbackup system that serves as a security layer on top of today's cloud storage services. Fade Version follows the standard version-controlled backup design, which eliminates the storage of redundant data across different versions of backups. On top of this, Fade Version applies cryptographic protection to data backups. Specifically, it enables fine-grained assured deletion, that is, cloud clients can assuredly delete particular backup versions or files on the cloud and make them permanently inaccessible to anyone, while other versions that share the common data of the deleted versions or files will remain unaffected. We implement a proof-of-concept prototype of Fade Version and conduct empirical evaluation atop Amazon S3. We show that Fade Version only adds minimal performance overhead over a traditional cloud backup service that does not support assured deletion.
In cloud computing, interoperability typically refers to the ability to easily move workloads and data from one cloud provider to another or between private and public clouds. A common tactic for enabling interoperability is the use of open standards, so there is currently a large amount of active work in standards development for the Cloud. This paper explores the role of standards in cloud-computing interoperability. It covers standard-related efforts, discusses several cloud interoperability use cases, and provides some recommendations for moving forward with cloud-computing adoption regardless of the maturity of standards for the cloud.
Security and interoperability is the biggest challenge to promote cloud computing currently. Trust has proved to be one of the most important and effective alternative means to construct security in distributed systems. In order to efficiently and safely construct entities' trust relationship in cloud and cross-clouds environment, this paper proposed a novel cloud trust model and a new cloud security framework. The propose trust model is domain-based. It divides one cloud provider's resource nodes into the same trust domain. It designs different trust strategies for different roles. Trust recommendation is treated as one type of cloud services just like computation or storage. Based on the proposed trust model, it introduced a novel cloud security framework with an independent trust management module. Using the proposed security model, it introduced some trust-based security mechanisms. Results of simulation experiments show that the proposed security model can achieve high transaction success rate with high trust accuracy.
This paper aims to develop an approach that enables cloud computing clients to verify health regulatory compliance claimed by cloud computing providers. In this approach, clients of cloud computing could check automatically how the cloud provider meets the regulatory compliance such as HIPAA legislation for their health records. Although cloud providers often furnish their services with third party certifications on meeting regulatory compliances, the client does not have any means to verify how regulatory compliances are actually achieved in a wide variety of cloud service scenarios in relation to their electronic protected health information (e-PHI). Our approach is based on three processes: (i) Mechanisms to represent health regulations in machine processable form; (ii) Collection of service specific compliance related real-time data from cloud servers; and (iii) Automatic reasoning about the compliances between the machine processable regulations and the collected data from servers.
Cloud computing has gained immense momentum during recent years and has ultimately become a viable solutions not only for larger firms, but also for small and medium-sized enterprises (SMEs). For smaller companies to stay competitive, many have therefore decided in favour of adapting cloudsolutions. Given the multitude of issues and challenges that occur during the cloud migration phase, this work proposes a novel framework that helps SMEs to master migration related impediments. Firstly, the work takes into account SME specific requirements and articulates their importance during the cloudprovider selection phase. The elicitation results demonstrate that factors such as security, reliability, cost, performance as well as flexibility and service and support have a pivotal role to play and require close attention. Secondly, decisive attributes were defined that qualify business components and services as cloud-fit. Finally, the framework itself was proposed, which focuses on a systematic service-oriented approach and helps companies to analyse their existing business processes in the course of cloud migration. The framework was verified in its practicability using a concrete scenario and a subsequent prototypical cloud implementation.
Cloud computing is emerging as a major trend in the ICT industry. While most of the attention of the research community is focused on considering the perspective of the Cloud providers, offering mechanisms to support scaling of resources and interoperability and federation between Clouds, the perspective of developers and operators willing to choose the Cloud without being strictly bound to a specific solution is mostly neglected. We argue that Model-Driven Development can be helpful in this context as it would allow developers to design software systems in a cloud-agnostic way and to be supported by model transformation techniques into the process of instantiating the system into specific, possibly, multiple Clouds. The MODAClouds (MOdel-Driven Approach for the design and execution of applications on multiple Clouds) approach we present here is based on these principles and aims at supporting system developers and operators in exploiting multiple Clouds for the same system and in migrating (part of) their systems from Cloud to Cloud as needed. MODAClouds offers a quality-driven design, development and operation method and features a Decision Support System to enable risk analysis for the selection of Cloud providers and for the evaluation of the Cloud adoption impact on internal business processes. Furthermore, MODAClouds offers a run-time environment for observing the system under execution and for enabling a feedback loop with the design environment. This allows system developers to react to performance fluctuations and to re-deploy applications on differentClouds on the long term.
Cloud computing architecture is used as a guideline to understand the whole process including actor roles inside a cloud computing environment. Currently, there is only a few cloud computing architecture that can be used as a reference for building a cloud computing infrastructure. As cloud computing technology is being used to minimize the usage cost of computing resources, many enterprises gained interest of migrating their old system to the cloud computing system. This paper describes an overview of the new proposed cloud computing reference architecture but focusing on one of the cloud provider components which is cloud service management. It is required for cloud providers to support them managing their cloud services properly from the planning to delivery and operation process.
Cloud computing aims on delivery of fault tolerant, scalable and reliable infrastructure to host Internet based application services. Our work presents the implementation of an efficient Quality of Service (QoS) based smart-scheduler along with Backfill strategy based light weight Virtual Machine Scheduler for dispatching jobs. The user centric smart-scheduler deals with selection of proper resources to execute high level jobs. The system centric Virtual Machine (VM) scheduler optimally dispatches the jobs to processors for better resource utilization. We also present our proposals on scheduling heuristics that can be incorporated at data center level for selecting ideal host for VM creation. Here Pollaczek-Khintchine (M/G/1) queuing model with non - preemptive priority and single server has been used to build an advanced job-scheduling system, assuming that Cloud-users' jobs come to the server following Poisson distribution while the process time to each job by the server has a general distribution. The implementation can be further extended at the host level, using load balancing in cloudenvironment.
This paper presents the various mechanisms for virtual machine image distribution within a large batch farm and between sites that offer cloud computing services. The work is presented within the context of the Large Hadron Collider Computing Grid (LCG), it has two main goals. First it aims at presenting the CERN specific mechanisms that have been put in place to test the pre-staging of virtual machine images within a large cloud infrastructure of several hundred physical hosts. Second it introduces the basis of a policy for trusting and distributing virtual machine images between sites of the LCG. Finally experimental results are shown for the distribution of a 10 GB virtual machine image distributed to over 400 physical nodes using a binary tree and a Bit Torrent algorithm. Results show that images can be pre-staged within 30 minutes.
E-Capital Market industry today, faced with numerous problems those issues in providing new services. Lack of flexibility, scalability, agility and IT cost structure are examples of these problems. Cloudcomputing technology has had a significant impact on improving service delivery e-Capital Market industry and In addition to reducing current problems delivery e-Capital Market industry, reduces costs associated with IT. The goal of this research is to provide an appropriate framework to evaluate the services provided by cloud providers is the use Capital Market, So that the Capital Market can use this framework to evaluate different cloud providers, and the best case to choose. Cloud computing technology is introduced in this paper first and then Capital Market problems in the field of information technology, the advantages and disadvantages of cloud computing has been used in Capital Markets and existing models and frameworks to evaluate the cloud computing provides a framework for evaluating the services provided by the Capital Market and the proposed framework that using the Delphi method is evaluated by professionals.
During recent years cloud service providers have successfully provided reliable and flexible resources to cloud users. For example Amazon Elastic Block Store (Amazon EBS) and Simple Storage Service (Amazon S3) provides users storage in the cloud. Despite the tremendous efforts cloud serviceproviders have devoted to the availability of their services, the interruption is still inevitable. Therefore just as an Internet service provider will not count on a single network provider, a cloud user should not depend on a single cloud service provider either. However, cloud service providers provide different levels of services. A more costly service is usually more reliable. As a result it is an important and challenging problem to choose among a set of service providers to fit one's need, which could be budget, failure probability, or the amount of data that can survive failure. The goal of this paper is to select cloud service providers in order to maximize the benefits with a given budget. The contributions of this paper include a mathematical formulation of the cloud service provider selection problem in which both the object functions and cost measurements are clearly defined, algorithms that selects among cloud storage providers to maximize the data survival probability or the amount of surviving data, subject to a fixed budget, and a series of experiments that demonstrateDuring recent years cloudservice providers have successfully provided reliable and flexible resources to cloud users. For example Amazon Elastic Block Store (Amazon EBS) and Simple Storage Service (Amazon S3) provides users storage in the cloud. Despite the tremendous efforts cloud service providers have devoted to the availability of their services, the interruption is still inevitable. Therefore just as an Internet service provider will not count on a single network provider, a cloud user should not depend on a singlecloud service provider either. However, cloud service providers provide diffe- ent levels of services. A more costly service is usually more reliable. As a result it is an important and challenging problem to choose among a set of service providers to fit one's need, which could be budget, failure probability, or the amount of data that can survive failure. The goal of this paper is to select cloud service providers in order to maximize the benefits with a given budget. The contributions of this paper include a mathematical formulation of the cloud service provider selection problem in which both the object functions and cost measurements are clearly defined, algorithms that selects among cloud storageproviders to maximize the data survival probability or the amount of surviving data, subject to a fixed budget, and a series of experiments that demonstrate that the proposed algorithms are efficient enough to find optimal solutions in reasonable amount of time, using price and fail probability taken from realcloud providers. that the proposed algorithms are efficient enough to find optimal solutions in reasonable amount of time, using price and fail probability taken from real cloud providers.
Cloud Computing (CC) is a new paradigm of utility computing and enormously growing phenomenon in the present IT industry hype. CC leverages low cost investment opportunity for the new business entrepreneur as well as business avenues for cloud service providers. As the number of the new CloudService Customer (CSC) increases, users require a secure, reliable and trustworthy Cloud ServiceProvider (CSP) from the market to store confidential data. However, a number of shortcomings in reliable monitoring and identifying security risks, threats are an immense concern in choosing the highly secure CSP for the wider cloud community. The secure CSP ranking system is currently a challenging aspect to gauge trust, privacy and security. In this paper, a Trusted Third Party (TTP) like credit rating agency is introduced for security ranking by identifying current assessable security risks. We propose an automated software scripting model by penetration testing for TTP to run on CSP side and identify the vulnerability and check security strength and fault tolerance capacity of the CSP. Using the results, several non-measurable metrics are added and provide the ranking system of secured trustworthy CSP ranking systems. Moreover, we propose a conceptual model for monitoring and maintaining such TTPcloud ranking providers worldwide called federated third party approach. Hence the model of federated third party cloud ranking and monitoring system assures and boosts up the confidence to make a feasible secure and trustworthy market of CSPs.
Cloud computing provides computing resources on demand. It is a promising solution for utility computing. Increasing number of cloud service providers having similar functionality poses a problem tocloud users of its selection. To assist the users, for selection of a best service provider as per user's requirement, it is necessary to create a solution. User may provide its QoS expectation and serviceproviders may also express the offers. Experience of existing users may also be beneficial in selection of best cloud service provider. This paper identifies QoS metrics and defines it in such a way that user and provider both can express their expectation and offers respectively into quantified form. A dynamic and flexible framework using Ranked Voting Method is proposed which takes requirement of user as an input and provides a best provider as output.
The applications submitted to cloud middle ware have been distributed to the CSPs based on the available CSPs in the cloud environment to categorize the service CSP providers with this work we are trying to introduce a concept to find the optimal csp based on rough set based approach. IaaS provides a large amount of computational capacities to users in a flexible and efficient way. In the market various CSPs are available example Amazons elastic computing cloud offers virtual machine with 0.1 us dollars per hour similarly another cloud Google compute cloud offers virtual machine with 0.5 us dollars per hour then the cloud users need rating among the various Csps. In this research work we have been proposing an approach to provide the rating of CSPs based on the internal performance of Datacenters and virtual machines. In present situation day-by- day number of cloud service providers have been increasing drastically. In this scenario existing service providers scheduling need a mechanism to find the optimal service providers information to Service request scheduling using this information SRS can allocate the service to the respective optimal service providers. In this paper we studied the problem of dynamic request allocation and scheduling for context aware application deployed in geographically distributed data centers forming a cloud.
The proliferation of cloud computing allows scientists to deploy computation and data intensive applications without infrastructure investment, where large generated datasets can be flexibly stored with multiple cloud service providers. Due to the pay-as-you-go model, the total application cost largely depends on the usage of computation, storage and bandwidth resources, and cutting the cost of cloud-based data storage becomes a big concern for deploying scientific applications in the cloud. In this paper, we propose a novel algorithm that can automatically decide whether a generated dataset should be 1) stored in the current cloud, 2) deleted and re-generated whenever reused or 3) transferred to cheaper cloud service for storage. The algorithm finds the trade-off among computation, storage and bandwidth costs in the cloud, which are three key factors for the cost of storing generated application datasets with multiple cloud service providers. Simulations conducted with popular cloud serviceproviders' pricing models show that the proposed algorithm is highly cost-effective to be utilised in thecloud.
Cloud computing is increasingly becoming a desirable and foundational element in international enterprise computing. There are many companies which design, develop, and offer cloud technologies. However, cloud providers are still like lone islands. While current cloud computing models have provided significant benefits of maximizing the use of resources within a cloud, the current solutions still face many challenges including the lack of cross-leverage of available resources across clouds, the need to move data between clouds in some cases, and the lack of a global efficient cooperation between clouds. In this paper, we address these challenges by providing an approach that enables various cloud providers to cooperate in order to execute, together, common requests. Several enhancements are provided by integrating hardware acceleration with the computation services. We extend the Hadoop framework by adding provisions for hardware acceleration with Field Programmable Gate Arrays (FPGAs) within the cloud, for multi-cloud interaction, and for global cloud management. Hardware acceleration is used to offload computations when needed or as a service within the clouds. It can provide additional sources of revenues, reduced operating costs, and increased resource utilization. We used a k-means clustering application as a case study to demonstrate the effectiveness of hardware acceleration..
Cloud computing is becoming more and more mature, and an IaaS cloud computing model calledCloud Bank [1, 2, 3, 4, 13], which is based on commercial bank model, has been designed. Cloud Bank model can be partly distinguished from other traditional IaaS providers by the sources of infrastructure resources. Compare with traditional IaaS Clouds whose infrastructure resources are almost derived from single provider, infrastructure resources of Cloud Bank are from various types of venders. Hence, there to some extent is certain instability of composition of Cloud Bank resource providers. In order to attract either large, professional IT resources venders or myriad, small personal computer owners intoCloud Bank, it is necessary to establish a resources provider-oriented pricing model. This paper briefly introduces the architecture of Cloud Bank and then describes in detail the pricing mechanism based on dynamic game theory.
Having received significant attention in the industry, the cloud market is nowadays fiercely competitive with many cloud providers. On one hand, cloud providers compete against each other for both existing and new cloud users. To keep existing users and attract newcomers, it is crucial for each provider to offer an optimal price policy which maximizes the final revenue and improves the competitive advantage. The competition among providers leads to the evolution of the market and dynamic resource prices over time. On the other hand, cloud providers may cooperate with each other to improve their final revenue. Based on a Service Level Agreement, a provider can outsource its users’ resource requests to its partner to reduce the operation cost and thereby improve the final revenue. This leads to the problem of determining the cooperating parties in a cooperative environment. This paper tackles these two issues of the current cloud market. First, we solve the problem of competition amongproviders and propose a dynamic price policy. We employ a discrete choice model to describe the user’s choice behavior based on his obtained benefit value. The choice model is used to derive the probability of a user choosing to be served by a certain provider. The competition among providers is formulated as a non-cooperative stochastic game where the players are providers who act by proposing the price policy simultaneously. The game is modelled as a Markov Decision Process whose solution is a Markov Perfect Equilibrium. Then, we address the cooperation among providers by presenting a novel algorithm for determining a cooperation strategy that tells providers whether to satisfy users’ resource requests locally or outsource them to a certain provider. The algorithm yields the optimal cooperation structure from which no provider unilaterally deviates to gain more revenue. Numerical simulations are carried out to evaluate the performance of the proposed models..
Cloud Computing is gaining a considerable attention in the past few years. It changes the way people acquire software and hardware as it provides them as services through internet on-demand following a pay-as-you-go financial model. With the exponential increase of such service, selecting the optimalprovider based on predefined Quality of Service (QoS) requirements becomes crucial. The current techniques are just designed for performance evaluation and cost-benefit analysis; yet optimal serviceprovider selection based on a group of QoS requirements is still uncovered as it should be. In this paper we propose a mathematical model addressing the Cloud service provider selection optimization problem based on QoS guarantees. The proposed model efficiently matches with the characteristics of market-oriented platforms covering a wide range of service provider selection problems. The efficiency of the proposed model is validated through simulation studies.
It is clear that Cloud computing is and will be a sea change for the Information Technology by changing the way in which both software and hardware are designed and purchased. In this work we address the use of this emerging computing paradigm into web hosting providers in order to avoid its resource management limitations. Thanks to the Cloud approach, resources can be provided in a dynamic way according with the needs of providers and end-users. In this paper, we present an elastic web hostingprovider, namely Cloud Hosting Provider (CHP), that makes use of the outsourcing technique in order to take advantage of Cloud computing infrastructures for providing scalability and high availability capabilities to the web applications deployed on it. Furthermore, we pursue the main goal of maximizing the revenue earned by the provider through both the analysis of Service Level Agreements (SLA) and the employment of an economic model. The evaluation exposed demonstrates that the system proposed is able to properly react to the dynamic load received by the web applications and it also achieve the aforesaid revenue maximization of the provider by performing an SLA-aware resource (i.e. web servers) management.
Cloud-service-broker needs a virtual service portal between multiple cloud-service-providers and cloud-service-consumers. The cloud-service-broker portal enables the cloud-service-providers to specify available their services. In addition, the cloud-service-consumers may find the most suitable services by negotiating the agreements on the services. The cloud-service-broker as an emerging technology intermediates heterogeneous multiple cloud services for both the providers and consumers. In this paper, we suggest the web-based user interface design of the cloud-service-broker portal to support different providers and consumers..
Job scheduling system problem is a core and challenging issue in cloud computing. How to use cloudcomputing resources efficiently and gain the maximum profits with job scheduling system is one of thecloud computing service providers' ultimate goals. In this paper, firstly, by analysis the differentiated QoS requirements of cloud computing resources users' jobs, we build the corresponding non-preemptive priority M/G/1 queuing model for the jobs. Then, considering cloud computing serviceproviders' destination which is to gain the maximum profits by offering cloud computing resources, we built the system cost function for this queuing model. After that, based on the queuing model and system cost function, considering the goals of both the cloud computing service users and providers, we gave the corresponding strategy and algorithm to get the approximate optimistic value of service for each job in the corresponding no-preemptive priority M/G/1 queuing model. Finally, we also provide corresponding simulations and numerical results. Analysis and number results show that our approach for job scheduling system can not only guarantee the QoS requirements of the users' jobs, but also can make the maximum profits for the cloud computing service providers.
In cloud computing, multiple cloud providers can cooperate to establish a resource pool to support internal users and to offer services to public cloud users. In this paper, we study the cooperative behavior of multiple cloud providers. The hierarchical cooperative game model is presented. First, given a group (i.e., coalition) of cloud providers, the resource and revenue sharing of a resource pool is presented. To obtain the solution, we develop the stochastic linear programming game model which takes the uncertainty of internal users from each provider into account. We show that the solution of the stochastic linear programming game is the core of cooperation. Second, we analyze the stability of the coalition formation among cloud providers based on coalitional game. The dynamic model of coalition formation is used to obtain stable coalitional structures. The resource and revenue sharing and coalition formation of cloud providers are intertwined in which the proposed hierarchical cooperative game model can be used to obtain the solution. An extensive performance evaluation is performed to investigate the decision making of cloud providers when cooperation can lead to the higher profit..
In order to design, build, and provide cloud based solutions that best meet customers' needs, it is essential to understand the skills, goals, primary tasks, and responsibilities of the people or organizations involved throughout the cloud service lifecycle. At IBM®, we developed a set of user roles that are used to describe the tasks of the people who interact with a cloud based Information Technology system. The three core roles of Cloud Service Creator, Cloud Service Provider, and CloudService Consumer create the base for reflecting the close interaction between developers, providers, and consumers in order to achieve the optimum service flow. The development of a single role as well as the entire taxonomy of roles is guided by a framework of well-defined principles..
Cloud computing is an emerging computing paradigm which allows sharing of massive, heterogeneous, elastic resources among users. Despite of all the hype surrounding the cloud, users are still reluctant to adopt cloud computing because public cloud services process users' data on machines that users do not own hence there is a fear of leakage of users' commercially sensitive data. Due to these reasons, it is very necessary that cloud users' be vigilant while selecting the service providers present in the cloud. To address this problem, selection of trustworthy cloud providers is proposed where users or enterprises employ the services of trustworthy service providers in the cloud. The paper proposes a system based on cooperative model of society where users select trustworthy service providers based on the recommendations given by their trustworthy acquaintances. The uncertainty present in the recommendations is handled through Fuzzy Inference System (FIS). Fuzzy inference system is capable of inferring crisp output even when the inputs are imprecise or uncertain, mimicking the reasoning of human mind. Experiments confirm that selection of trustworthy cloud providers is an effective and feasible way of estimating the trustworthiness of the service providers and thus helping users in protecting their data.
Nowadays Cloud computing is recognized as the most emerging computing paradigm. Because of its promising benefits, every day more and more enterprises are relying on Cloud systems. Furthermore, new Cloud business models are appearing, most of them within the SaaS marketplace, which fully depend on PaaS and IaaS providers. In any case, the expectation from businesses that IT (Cloud) services and infrastructures should bring them closer to the achievement of their Business-Level Objectives (BLOs) is spreading. Due to this fact, the presence in Cloud providers of a self-management of Cloud services and infrastructures driven by business-level aspects is mandatory. In this direction, the Business-Driven IT Management (BDIM) discipline has been evolving as the most promising way in the sense of aligning IT (low-level) management decisions with business-level objectives coming fromproviders themselves, as well as from their users. In this paper, we expose several BDIM challenges on the Cloud computing paradigm. Consequently, we outline key issues for the inclusion of BDIM-related features into the core operation of Cloud providers..
The Service Level Agreement(SLA) of current cloud computing often focuses on performance while seldom emphasizes security; additionally, customers have to select the most suitable one among several Cloud Service Providers (CSPs). Therefore, a cloud-oriented meta-synthesis selection method is proposed as well as a cloud computing security SLA indicators system by using Delphi and Goal-Question-Metric approaches; synthetic weight for each indicator is granted through G1 and coefficient of variation methods; optimum nearness is defined to provide quantitative basis in the CSP selection. Calculation and analysis against the normalized reports from Cloud Security Alliance's Security, Trust & Assurance Registry (CSA STAR) show that the proposed approach has the features of clear process and relatively high distinguishability.
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Secure your servers with the included firewall and backup options.Cloud computing providers are notable entities who have verifiably significant production cloud computing service offerings.A service provider that offers customers storage or software services available via a private (private cloud) or public network (cloud). Usually, it means the storage and software is available for access via the Internet.
Cloud providers are generally organizations that provide some form of IT infrastructure that is commercially distributed and sourced across several subscribers - typically businesses. Cloud providers deliver cloud solutions through on-demand, pay-as-you-go systems as a service to customers and end users. Cloud provider customers access cloud resources through Internet and programmatic access and are only billed for resources and services used according to a subscribed billing method.Depending on the business model, a cloud provider may provide various solutions, such as:Infrastructure as a Service (IaaS): May include virtual servers, virtual storage and virtual desktops/computersSoftware as a Service (SaaS): Delivery of simple to complex software through the InternetPlatform as a Service (PaaS): A combination of IaaS and SaaS delivered as a unified serviceA cloud provider also may be classified as a public cloud provider, private cloud provider, hybrid cloud provider or community cloud provider
A cloud provider is also known as a utility computing provider. This role is typically related to that of a managed service provider (MSP), but usually, the latter provides other managed IT solutions. Specifically, nearly all cloud providers see data center operations as a critical area of focus, as compared to only 23 percent of cloud users. In addition, more than 72 percent of cloud providers see business continuity and disaster recovery as a critical area of focus in comparison to 47 percent of cloud users. With respect to storage operations, 49 percent of cloud providers versus 14 percent of cloud users see this as a critical security priority. As shown in the above bar chart, 50 percent of cloud users in comparison to 40 percent of cloud providers report identity and access management as a critical area of focus.Cloud Hosting Providers List provides information on MSPs and hosting services available worldwide providing Hosting & Cloud Computing solutions to business looking to outsource IT services. Companies listed offer services such as computing power, VPS, Email & Web filtering, storage, backup, Hosted Email, Virtual Data Centers, Managed Security and all sort of managed IT services.
Service providers are delivering data center infrastructure-as-a-service (IaaS) to businesses with more agility through scalable, elastic, multi-tenant cloud platforms. Fortinet’s FortiGate Network Security Platform provides the backbone for cloud service provider’s (CSP) and managed service providers (MSSP) to deliver robust network security to their enterprise tenants, whether in a public or hybrid cloud, or even back to the customer premise.Fortinet’s industry-leading, high capacity Firewall technologies deliver exceptional throughput and ultra-low latency, enabling the security, flexibility, scalability and manageability you demand in an edge or core platform. FortiGate appliances and chassis-based devices combine a high-performance Firewall with the flexibility to enable fully integrated personalities (such as VPN, Intrusion Prevention, or Application Control) that provide extensive protection profiles for in-depth defense. Fortinet built the FortiGate line of Network Security Platforms, and the accompanying management and reporting tools, to exceed the performance and security requirements of even the most demanding data center environments.
High-Speed Interfaces – 40 GbE ports with high density of 10 GbE ports High Capacity Firewall – 100+ Gbps firewall throughput (both IPv4 and IPv6); ultra-low latency, 40M+ concurrent sessions Virtualization and Cloud-Ready – Virtual appliance-ready, support for next-generation data center architectures, multi-tenant support, APIs for rapid orchestration, fast integration with 3rd party ecosystems
Flexible Firewall Personalities: Deploy at the edge or core data center, with physical and virtual network segmentation, and deploy optional integrated security technologies (such as VPN, IPS, NGFW) supported by continuous updates
>FortiGate-VM virtual appliances can be orchestrated to deploy on a per-tenant basis, delivering on-demand security-as-a-service seamlessly to IaaS and PaaS with all the tenant benefits of a dedicated Fortinet appliance.Support for all leading hypervisors including VMware vSphere, Microsoft Hyper-V, KVM, and Xen enables FortiGate-VM virtual appliances work alone or complement FortiGate physical appliances protecting north-south traffic at the network core or data center edge.
To support large-scale multi-tenant cloud infrastructure, network security itself must not only be performant, but also scalable and multi-tenant. Fortinet’s unique virtual domain (VDOM) technology, together with VLAN support, enables high-end FortiGate physical appliances to be divided into hundreds of logical instances for multi-tenant environments, with each instance having fully isolated security policies and management delegation. VDOM technology has long been proven in telco and service provider managed service environments for multi-tenancy.FortiGate-VM also further supports VDOM and VLAN technology, so whether in virtual appliances only or together with FortiGate physical appliances at the data center network core, service providers have the unique agility and flexibility to leverage both scale-up and scale-out technologies together to deliver extremely high network security performance with unlimited elasticity. As an example, all Layer 2/3 firewall traffic could be driven north-south to a physical FortiGate-5000 series chassis for all tenants, while intrusion prevention and other CPU-intensive Layer-7 application security is deployed with optional per-tenant FortiGate-VM virtual appliances.
To support large-scale multi-tenant cloud infrastructure, network security itself must not only be performant, but also scalable and multi-tenant. Fortinet’s unique virtual domain (VDOM) technology, together with VLAN support, enables high-end FortiGate physical appliances to be divided into hundreds of logical instances for multi-tenant environments, with each instance having fully isolated security policies and management delegation. VDOM technology has long been proven in telco and service provider managed service environments for multi-tenancy.
FortiGate-VM also further supports VDOM and VLAN technology, so whether in virtual appliances only or together with FortiGate physical appliances at the data center network core, service providers have the unique agility and flexibility to leverage both scale-up and scale-out technologies together to deliver extremely high network security performance with unlimited elasticity. As an example, all Layer 2/3 firewall traffic could be driven north-south to a physical FortiGate-5000 series chassis for all tenants, while intrusion prevention and other CPU-intensive Layer-7 application security is deployed with optional per-tenant FortiGate-VM virtual appliances.
High performance, high capacity, and ultra-low latency Cloud-ready multi-tenant support and virtual domain support for network segmentationFlexibility to enable the firewall personality you need to match your environment with edge or core deployment, network segmentation, or integrated security technologies Single-pane-of-glass management for unmatched visibility and control Single security platform delivers all needed cloud services Lower TCO, improved projection, increased performanceUnmatched elasticity and flexibility of deployment with appliance, chassis-based, and virtual machine options for provider data centers