Types Of Cloud Services Research Articles

Cloud Security Risk Analysis Method based on Fuzzy Logic

This paper proposes a cloud security risk assessment index system through the study of cloud computing structure and services and quantifies the risk through entropy weight and fuzzy theory. This method can determine the value of risk from the three essential attributes of assets, threats, and vulnerability, and it can be applied to the risk assessment of various types of cloud services.

Model-Based Extraction of Knowledge about the Effect of Cloud Application Context on Application Service Cost and Quality of Service

With the increased usage of cloud computing in production environments, both for scientific workflows and industrial applications, the focus of application providers shifts towards service cost optimisation. One of the ways to achieve minimised service execution cost is to optimise the placement of the service in the resource pool of the cloud data centres. An increasing number of research approaches is focusing on using machine learning algorithms to deal with dynamic cloud workloads by allocating resources to services in an adaptive way. Many of such solutions are intended for cloud infrastructure providers and deal only with specific types of cloud services. In this paper, we present a model-based approach aimed at the providers of applications hosted in the cloud, which is applicable in early phases of the service lifecycle and can be used for any cloud application service. Using several machine learning methods, we create models to predict cloud service cost and response times of two cloud applications. We also explore how to extract knowledge about the effect that the cloud application context has on both service cost and quality of service so that the gained knowledge can be used in the service placement decision process. The experimental results demonstrate the ability of providing relevant information about the impact of cloud application context parameters on service cost and quality of service. The results also indicate the relevance of our approach for applications in preproduction phase since application providers can gain useful insights regarding service placement decision without acquiring extensive training datasets.

A multifaceted framework for adoption of cloud computing in Malaysian SMEs

PurposeThe purpose of this study is to develop a model to understand the relationships among technology, organizational and environmental (TOE) contexts, intention to adopt cloud computing (IACC) and actual usage of cloud computing (AUCC) in small and medium enterprises (SMEs) in Malaysia as a developing country. More specifically, this paper seeks to explore the mediation effect of IACC on the relationship between TOE context and AUCC.Design/methodology/approachA positivist research approach was selected for this study. Drawing largely upon the TOE framework, this study uses survey data from 209 Malaysian SMEs. Structural equation modelling (SEM) based on partial least squares (PLS) was used to assess the structural relations of the research model.FindingsThe results of the structural model show that data security, technology readiness, top management support, competitive pressure and innovativeness are the most significant factors in predicting the adoption of cloud computing in Malaysian SMEs. Further, the results indicate that intention to adopt cloud computing can play a mediating role between TOE factors and the actual usage of cloud computing.Research limitations/implicationsThe focus upon Malaysian SMEs may diminish the generalizability of the findings. This study provides profound insight into the management and foundation of cloud computing, different types of cloud services and deployment models that could facilitate the management of enterprise strategic resources and contribute to the performance improvement. This study also provides another important implication for practitioners regarding the absolute necessity of value drivers’ identification within enterprise and understand the causal relationships, which are vital in driving those values.Practical implicationsThis study provides several practical guidance for practitioners in deploying cloud services which are most suitable option for their specific technology requirement in their enterprise to enjoy the full benefits of their intangible assets. Another significant implication of this study lies in the fact that it may require a different emphasis on nature and adoption design when there is a higher level of stress on technology-related and cloud computing resources.Originality/valueThis study contributes to the extant literature by developing an integrative model to identify how a wide set of contextual factors can determine the intention to adopt cloud computing and, in turn, influence the actual usage of cloud computing in SMEs in Malaysia as a developing country.

A Proposition of Modifications and Extensions of Cloud Computing Standards for Trust Characteristics Measures

In recent years, we have witnessed a marked rise in the number of cloud service providers with each offering a plethora of cloud services with different objectives. Gaining confidence for cloud technology adoption as well as selecting a suitable cloud service provider, both require a proper evaluation of cloud service trust characteristics. Hence, the evaluation of cloud services before used by the customer is of utmost importance. In this article, we adapt the extracted trust characteristics from both system and software quality standards and cloud computing standards, for evaluating cloud services. Moreover, we derive measures for each trust characteristics to evaluate the trustworthiness of different cloud service providers, and generalize these trust measures for any type of cloud services (e.g. Software as a Service, Platform as a Service, and Infrastructure as a Service). Our work thereby demonstrates a way to apply generalized trust measures for cloud services and therefore contributes to a better understanding of cloud services to evaluate their quality characteristics. As part of our ongoing research, the results of this study will be used to develop a comprehensive cloud trust model.

Бізнес-моделі хмарного надання ІТ-послуг

Бізнес-моделі хмарного надання ІТ-послуг

Transactional Behavior Verification in Business Process as a Service Configuration

Business Process as a Service (BPaaS) is an emerging type of cloud service that offers configurable and executable business processes to clients over the Internet. As BPaaS is still in early years of research, many open issues remain. Managing the configuration of BPaaS builds on areas such as software product lines and configurable business processes. The problem has concerns to consider from several perspectives, such as the different types of variable features, constraints between configuration options, and satisfying the requirements provided by the client. In our approach, we use temporal logic templates to elicit transactional requirements from clients that the configured service must adhere to. For formalizing constraints over configuration, feature models are used. To manage all these concerns during BPaaS configuration, we develop a structured process that applies formal methods while directing clients through specifying transactional requirements and selecting configurable features. The Binary Decision Diagram (BDD) analysis is then used to verify that the selected configurable features do not violate any constraints. Finally, model checking is applied to verify the configured service against the transactional requirement set. We demonstrate the feasibility of our approach with several validation scenarios and performance evaluations.

TSLAM

With the rapid development of cloud computing, various types of cloud services are available in the marketplace. However, it remains a significant challenge for cloud users to find suitable services for two major reasons: (1) Providers are unable to offer services in complete accordance with their declared Service Level Agreements, and (2) it is difficult for customers to describe their requirements accurately. To help users select cloud services efficiently, this article presents a Trust enabled Self-Learning Agent Model for service Matching (TSLAM). TSLAM is a multi-agent-based three-layered cloud service market model, in which different categories of agents represent the corresponding cloud entities to perform market behaviors. The unique feature of brokers is that they are not only the service recommenders but also the participants of market competition. We equip brokers with a learning module enabling them to capture implicit service demands and find user preferences. Moreover, a distributed and lightweight trust model is designed to help cloud entities make service decisions. Extensive experiments prove that TSLAM is able to optimize the cloud service matching process and compared to the state-of-the-art studies, TSLAM improves user satisfaction and the transaction success rate by at least 10%.

Ranking cloud render farm services for a multi criteria recommender system

Recommender systems that recommend ideal services or items to the online users are a very useful tool for both the users and the businesses. Usually for recommending services, multiple attributes of the services are evaluated and these types of recommender systems that evaluate multiple attributes are called multi criteria recommender systems. In these types of multi criteria recommender systems the ranking of services plays a major role. This work is focused on ranking the cloud render farm services which are of the PaaS (Platform-as-a-Service) type of cloud services that provide the entire platform for the animators to render the files using the cloud resources. This work identifies the Quality of Service (QoS) attributes that are important for the animators for selecting a cloud render farm service. The QoS values of four different real time cloud render farm services were collected by conducting real time experiments using the files of the “Big Buck Bunny”, an open-source animated film project and were ranked using three Multi-Criteria Decision Making (MCDM) methods, namely the AHP (Analytical Hierarchical Process), TOPSIS (Technique for Order Preference by Similarity to the Ideal Solution) and SAW (Simple Additive Weighting). The analysis of the ranks obtained using the three different MCDM methods provide many useful insights and conclusions.

Cloud providers viability

A major part of the commercial Internet is moving toward the cloud paradigm. This phenomenon has a drastic impact on the organizational structures of enterprizes and introduces new challenges that must be properly addressed to avoid major setbacks. One such challenge is that of cloud provider viability, that is, the reasonable certainty that the Cloud Service Provider (CSP) will not go out of business, either by filing for bankruptcy or by simply shutting down operations, thus leaving its customers stranded without an infrastructure and, depending on the type of cloud service used, even without their applications or data. This article attempts to address the issue of cloud provider viability, defining a possible way of modeling viability as a non-functional requirement and proposing some approaches that can be used to mitigate the problem, both from a technical and from a legal perspective. By introducing a structured perspective into the topic of cloud viability, describing the risks, factors and possible mitigators, the contribution of this work is twofold: it gives the customer a better understanding to determine when it can rely on the cloud infrastructure on the long term and what precautions it should take in any case, and provides the CSP with means to address some of the viability issues and thus increase its customers’ trust.

A Three-Dimensional Performance Measurement Model for Cloud Computing

New paradigms for processing and storing data such as cloud computing require new approaches for the measurement of cloud service performance. To establish a Service Level Agreement (SLA) between a cloud service provider and its customers, the cloud services and their service level objectives need to be identified. An additional challenge in the performance measurement of cloud services is the lack of models that integrate the different perspectives of providers, maintainers and customers within the same model in order to define the concepts commonly used in cloud SLA contracts. This work proposes a three-dimensional Performance Measurement Model for Cloud Computing (P2M2C-3D) which consolidates performance measurement from the perspectives of providers, maintainers and customers for the different types of cloud services.

Secure migration to compliant cloud services: A case study

Adoption of cloud computing technology in the financial sector is increasing to improve the efficiency of payment transactions, risk management, and business processes. This is occurring more rapidly in developed countries such as USA, Canada, and the UK while cloud implementation in less developed countries such as Saudi Arabia is still emerging. Implementation of cloud technologies in the financial sector requires diligent decisions such as selecting the most suitable secure cloud deployment model, service level agreement, and cloud vendor. In this paper, cloud migration using an information security, privacy, and compliance (ISPC) readiness model is presented. Several types of cloud services are available, therefore evaluating migration readiness and selecting an appropriate vendor is critical, as this will have an impact on the requirements of stakeholders such as local banks. Cloud migration decisions are obtained by analyzing ISPC requirements considering the strategic initiatives of the organization. A case study involving the Saudi Arabian central bank is presented to demonstrate the implementation of the ISPC readiness model.

PI3.Performance Model of Software as a Service (SaaS) Cloud Environment

Cloud computing is a vibrant and dynamic technology. Cloud users can subscribe to various types of cloud services like Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) etc. offered to clients by various cloud service providers like Amazon, Microsoft, Google, IBM, Facebook, Twitter, and WhatsApp etc. SaaS service model is the most popular service model of the cloud. In this service model, cloud user downloads the Application (App) of the cloud service provider (CSP) and interacts with the resources of the CSP by using the App. The App execution engine is placed at various data centers located at different locations by the CSP to optimize the performance of the App. The placement of Cloud App execution engine at various data centers by the CSP plays a vital role in overall performance of SaaS cloud environment. In this paper, we address this issue and propose a performance model of SaaS cloud environment to aid the CSP to optimally place the App execution engine at various locations to improve the overall performance of the Cloud App. The proposed performance model is named as PI3(π3) Cloud performance model, SaaS, Performance model of SaaS cloud, Performance parameters of the cloud. (Prodigal, Ideal, Impoverished, and Inefficient) uses two important performance metrics response time of user request and cost of providing services and it classifies the performance of the SaaS cloud environment into four types: Prodigal, Ideal, Impoverished and Inefficient. Finally, we use the proposed model to analyze and optimize the performance of a SaaS cloud environment.

Forensics Analysis from Cloud Storage Client Application on Proprietary Operating System

Increased use of cloud storage services have become a necessity alternative that complements the main storage media in everyday activities because it offers ease of doing automatic backups, sharing files and photos and so forth on a variety of computing devices and smartphones. It is very possible loopholes for criminals to store illegal files or matters relating to such activities. There are various types of cloud services with each type having a different potential use in criminal activities. One area of difficulty is the identification and acquisition of potential data when different services can be exploited by criminals. Because geographically cloud servers scattered in various regions. This causes difficulties for digital forensic investigators will add time and expense, to contact all potential service providers to determine whether the data stored in the server cloud services. This paper presented at a target on the client side user application to help find the data renmant on the use of cloud storage applications of various service provider on the proprietary operating system focuses on the Windows 10 platform. Results from this research include a variety of state after the install, deleted and uninstall web browser and memory, in order to find digital evidence. Based on the test results the success index average was 82.63% and the remaining can not be analyzed, the results depend on various state, procedures and tools that are used, the research can be carried out smoothly. General Terms Digital investigation, Cloud storage, Application Forensics.

Virtual cloud bank: consumer-centric service recommendation process and architectural perspective for cloud service brokers

A paradigm shift from a PC-centric to a cloud computing environment has occurred because of rapid and continuous improvements in the IT environments. With the expansion of cloud computing, various types of cloud services are emerging, collectively known as XaaS (that is, "everything as a service"), including Infrastructure as a Service, Platform as a Service, and Software as a Service. Therefore, an intermediation entity known as a CSB (cloud service broker) is required that interrelates cloud service providers and cloud consumers. However, CSBs remain an active research area in industry and academia. With the diversification of cloud services and the emergence of services with similar functions, the role of the CSB to recommend cloud services that meet the requirements of various consumers has become increasingly important. In this paper, to allow CSBs to provide appropriate cloud services from consumer-centric perspectives, we propose a CSB named the virtual cloud bank that includes a process for recommending cloud services and architectural aspects. Our proposed approach can be utilized as a reference model for a consumer-centric CBS for provisioning cloud services. Therefore, if CSB developers apply and extend the proposed well-defined architectural elements and recommendation approach, this is expected to help accelerate the growth of the cloud computing market.

Incorporating service and user information and latent features to predict QoS for selecting and recommending cloud service compositions

The rapid growth of published cloud services in the Internet makes the service selection and recommendation a challenging task for both users and service providers. In cloud environments, software re services collaborate with other complementary services to provide complete solutions to end users. The service selection is performed based on QoS requirements submitted by end users. Software providers alone cannot guarantee users' QoS requirements. These requirements must be end-to-end, representing all collaborating services in a cloud solution. In this paper, we propose a prediction model to compute end-to-end QoS values for vertically composed services which are composed of three types of cloud services: software (SaaS), infrastructure (IaaS) and data (DaaS) services. These values can be used during the service selection and recommendation process. Our model exploits historical QoS values and cloud service and user information to predict unknown end-to-end QoS values of composite services. The experiments demonstrate that our proposed model outperforms other prediction models in terms of the prediction accuracy. We also study the impact of different parameters on the prediction results. In the experiments, we used real cloud services' QoS data collected using our developed QoS monitoring and collecting system.

Cross-cutting 기반의 클라우드 서비스 품질 메트릭 및 SLA 명세 기법

클라우드 서비스가 증가하고 다양해짐에 따라 클라우드 서비스 사용자들의 요구사항을 만족하는 가장 적절한 서비스를 찾아주는 클라우드 서비스 브로커(CSB) 기술이 나타났다. CSB를 통해 클라우드 서비스가 사용되는 것을 촉진시키기 위해서는 서비스 수준 협약(SLA) 기반의 협상 과정을 통해 사용자들의 요구사항에 맞는 품질 수준을 보장하는 것이 중요하다. 그러나 클라우드 서비스 유형 별로 품질수준을 표현하는 측정 기준과 척도, 계산 방식이 서로 상이하다. 따라서 클라우드 서비스의 품질에 대한 가변성을 분석하고, 분석된 품질 수준을 보장 및 개선하기 위한 SLA 모델이 필요하다. 본 논문에서는 cross-cutting 개념을 적용하여 클라우드 서비스의 유형 별 품질 메트릭을 분석하고 사용자와 제공자 간의 품질 수준에 대한 협상을 담당하는 VSLA(Variable SLA) 메타모델을 제안한다.

Leveraging Slack Capacity in IaaS Contract Cloud Services

This paper develops pricing and capacity planning models for a cloud provider taking into account the trade-off between service reliability and capacity utilization. The provider's objectives are to optimally allocate resources, price different types of cloud services, and ultimately extract the maximum revenue from the market. We first analyze two basic types of cloud services: contract and on-demand. We then propose hybrid models in which the two basic services simultaneously exist. For each hybrid model, we determine an optimal capacity planning strategy, optimal reservation fee, optimal per-usage fee, and corresponding service reliability. We conduct experiments to study how optimal solutions change with respect to critical system parameters such as service rate, market size, and service reliability. Our work provides a framework for resource allocation, service provision, and strategic planning in cloud computing practice.

A Petri net-based decision-making framework for assessing cloud services adoption: The use of spot instances for cost reduction

Cloud services are widely used nowadays, especially in Infrastructure as a service (IaaS), with vendors offering several purchasing options and expanding the range of services offered on almost a daily basis. Cost reduction is a major factor promoting the adoption of cloud services among enterprises. However, qualitative factors need to be evaluated as well, thus rendering the decision regarding the adoption of cloud services among enterprises a non-trivial task for Information Technology (IT) managers. In this paper, we propose a place/transition or Petri net-based multi-criteria decision-making (MCDM) framework to assess a cloud service in comparison with a similar on-premises service. The framework helps IT managers choose between two such options, and can be used for any type of cloud service: Infrastructure as a Service (IaaS), Platform as a service (PaaS), Software as a service (SaaS), etc. Because its low cost is among the most important reasons for adopting cloud services, we also propose a Petri net to model cost savings using the spot instances purchasing option in public clouds. Through simulation of several scenarios, we conclude that spot instances present a very interesting cost-saving option in the auto-scaling process, even for simple business applications using few servers.

테넌트 요구사항 기반의 클라우드 서비스 추천 방법

It is difficult to provide proper cloud services for cloud users, because the number of cloud services are increasing and the type of cloud services are diversifying. To overcome this problem, the concept of cloud service broker is presented to mediate cloud services between cloud providers and tenant. The most important role of cloud service broker is to finding cloud services that fulfill requirements of tenant. However, current existing cloud service broker conduct passive requirements analysis process with cloud service expert`s assistance. In addition, the systematic functional and non-functional requirement analysis is insufficient. Therefore, we need the new methods for requirement analysis to find nearest service that matches with requirement of tenant. In this paper, we apply pairwise comparison from AHP method to analyze requirement automatically and systematically. It calculates score of service by comparing requirement with service specification, calculating importance rate, and so on.

Application of cloud computing services in business

Dynamism of all business processes and a huge amount of information of different nature are the main characteristics of today's business environment. They require the use of information technologies as an integral and essential part of the management strategy of companies. One modern and alternative approach to business management is the use of services based on cloud computing. The movement of the business to the cloud empowers companies to achieve significant economic benefits without investments in building their own IT infrastructure. The purpose of the current work is to present the nature and advantages of different types of cloud services. Popular cloud services for business are