Adoption Of Cloud Services Research Articles

Contextual Analysis of Educational Monitoring and Progression as a Service (EMPaaS) System in Higher Education

The arrival of new technologies has opened a window of opportunity for UK higher education institutions. Although UK Higher education (HE) has recently become a huge phenomenon owing to an increase in students attending University, many UK universities are not investing enough in technology to facilitate teaching, management and research practices that aim to improve the student experience. This paper discusses the potential for an information system solution, which can facilitate the institutional practices in UK HEIs from multiple stakeholder perspectives. An existing system employed at a UK University known as “MyPGR” was evaluated in order to shed some light on the existing technical problems UK Universities are currently facing, with the support of a soft systems approach (CATWOE). The proposed solution is the Educational-Monitoring-and-Progression-as-a-Service (EMPaaS), which is based on the Cloud Computing model. EMPaaS has the potential to monitor student progression and key milestones relating to their PGR programme, in addition to enabling students to use free cloud applications to keep track of milestones and progressions. The highly accessible and flexible nature of cloud applications adds to the cost-effectiveness of adopting cloud services, which in turn frees up additional funds for UK Universities to pursue other important investments.

A hybrid fault tolerance framework for SaaS services based on hidden Markov model

With the booming of cloud computing, more and more applications adopt cloud services to implement their critical business. However, failures causing either service downtime or producing invalid res...

Selection of Cloud Delivery and Deployment Models

Research interests on cloud computing adoption and its effectiveness in terms of cost and time has been increasing. However, one of the challenging decisions facing management in adopting cloud services is taking on the right combinations of cloud service delivery and deployment models. A comprehensive review of literature revealed a lack of research addressing this selection decision problem. To fill this research gap, this article proposes an expert system approach for managers to decide on the right combination of service delivery and deployment model selection. The article first proposes a rule-based expert system prototype, which provides advice based on a set of factors that represent the organizational conditions and requirements pertaining to cloud computing adoption. Next, the authors evaluate the system prototype. Lastly, the article concludes with a discussion of the results, its practical implications, limitations, and further research directions.

An Analysis of Issues for Adoption of Cloud Computing in Telecom Industries

In the modern era companies seek the use of modern technologies in order to upgrade their infrastructure and enhance their business growth. The use of business intelligence, data science and cloud computing (CC) has become an integral part of business. Different factors play important role in the adoption of cloud services. An organization willing to adopt cloud services should consider them. This paper explores the factors and addresses the issues in implementing and deploying CC in telecom companies. In addition, this study also shares the benefits of utilizing CC which is a novel technical pattern which can change the use of different associations of information technology as a service. CC concentrates on the idea of definition, security problems, service models and infrastructures of its development. The important point is to analyze how this paradigm should be adopted in telecom industries and its results. This research study presents a comparative analysis of adaptation of CC by various telecom industries. The results identify certain limitations which also play their role for adaptation of CC in telecom companies.

A STEP FORWARD IN INTEGRATING HEALTHCARE AND VOICE-ENABLED TECHNOLOGY: CONCEPT DEMONSTRATION WITH DEPLOYMENT OF AUTOMATIC MEDICAL CODING MODEL AS AN AMAZON “ALEXA” SKILL

Digital technology is fast improving and being adopted by many fields of research. Although the adoption is slow in clinical research, the change is inevitable. Amazon, Google and Microsoft are accelerating the progress and implementation by providing cloud-based web services. HIPAA compliance of such platforms has provided confidence to the medical community to adopt cloud services at a quicker pace. With deep learning making a paradigm shift in every field it touches, all the above-mentioned tech giants provide Artificial Intelligence tools and architectures to rapidly create and deploy applications. These services act as bricks which when put together creates applications that can significantly improve user experience and quality control measures. Using an in-house developed model in conjunction with Amazon Web Services, we have developed a voice-interactive virtual assistant that answers users’ requests to obtain MedDRA coding results by understanding the user's question (Alexa skill with interaction model), executing the model in a server-less function (model deployed in AWS Lambda), querying the obtained code in a server-less interactive query service (AWS Athena) to obtain the corresponding meaningful description, and finally based on the result, communicates to them appropriately in a human-like voice. We had previously reported machine learning based models for medical coding that predict proper adverse event (AE) coding with an accuracy of 75 - 82% (Ravindranath et. al, AAIC 2017, 2018). Here, we demonstrate deployment of a custom built medical-coding model within services offered by Amazon to render a voice-based User Interface that can communicate and provide AE coding results seamlessly. We expect this method to act like a quick-lookup solution for the medical coders while coding, or training coders to find and validate their coding results.

Dynamic Workload Migration Over Backbone Network to Minimize Data Center Electricity Cost

As more organizations adopt cloud services, energy consumption in data centers (DCs) keeps increasing. Today, information and communication technology (ICT) has become a major consumer of energy worldwide. A large portion of ICT energy consumption is used to power servers running in DCs and the network they use to communicate. In this paper, we consider that energy cost at a particular DC is often related to the electricity price regulated by independent system operators/regional transmission organizations. As these prices vary in time and depend on the geographical locations of the DCs, recent studies have shown that the spatio-temporal variations of electricity price can be exploited to reduce electricity cost. In particular, as workloads tend to change, often unpredictably, adaptive workload placement and migration can help to serve the workloads in regions with lower electricity costs. While most prior works consider a quasi-static scenario with known workload patterns, this paper proposes dynamic workload-aware algorithms which exploit the spatio-temporal variations of electricity costs to minimize the energy cost in ICT. Although prior studies focused on power consumption from power consumers such as servers, cooling systems, etc., recent studies have shown that the network elements consume a significant portion of the energy. Hence, while reducing DC energy cost, this paper also considers electricity cost of the backbone network. Algorithms introduced in this paper use dynamic request re-routing and live virtual machine (VM) migration to move workloads to DCs with lower electricity cost. We consider VM migration cost (including electricity cost at backbone network nodes), bandwidth constraints for migration, VM consolidation, constraints from service level agreement, and administrative overhead of VM migration. Our simulation studies show that the proposed algorithms reduce operational cost of DCs significantly.

Speedy Cloud-RSA homomorphic scheme for preserving data confidentiality in cloud computing

Homomorphic encryption (HE) technique provides a third party with the ability to execute operations on ciphertexts. This property can be considered as a good solution to overcome some barriers limiting the widespread adoption of cloud services. However, since cloud environments are more threatened by security attacks and since cloud consumers often access to cloud services using resource-constrained devices, the HE schemes have to be promoted at security level and at running time to work efficiently. In El Makkaoui et al. (Cloud-RSA: an enhanced homomorphic encryption scheme. In: Rocha A, Serrhini M, Felgueiras C (eds) Europe and MENA cooperation advances in information and communication technologies. Advances in intelligent systems and computing, vol 520. Springer, Cham, pp 471–480, 2017b), we boosted RSA scheme at security level, Cloud-RSA. In this paper, we suggest two variants of Cloud-RSA scheme in order to speed up its decryption process. The variants are based on modifying the form of Cloud-RSA modulus and exponents. The first variant uses a modulus formed of two or more distinct primes and employs the Chinese remainder theorem (CRT) to encrypt and decrypt. Whereas, the second variant uses a modulus of the form $$n=p^rq^s$$ for $$r\ge 2$$ and $$s \ge 1$$ , and applies the Hensel lifting and the CRT to decrypt. Theoretical and simulation results show that the proposed variants provide a large decryption speedup over Cloud-RSA.

A novel TOPSIS evaluation scheme for cloud service trustworthiness combining objective and subjective aspects

Cloud computing has been paid more attention due to its outstanding advantages. However, trust issue greatly affects the adoption of cloud services. Selecting trustworthy cloud service from those with same functionality but different qualities has become a significant challenge. Since trustworthiness evaluation is multi-dimensional, how to assign weight for each influence factor is a non-trivial problem. In this paper, we put forward a novel TOPSIS evaluation scheme for cloud service trustworthiness combining objective and subjective aspects. First, we consider the objectivity of cloud services from two facets. For one thing, we concern the reliability of QoS information source and utilize monitored values of QoS attributes rather than feedback ratings from consumers. For another, we employ objective entropy weight for different QoS attributes to decrease the effect of false or artificial parameter information. Second, we introduce trust preference that reflects the subjectivity of trust. Most important of all, we propose the combined weight integrating the two aspects and apply it to TOPSIS method to develop a novel evaluation scheme. The results of two experiments based on the existing QWS dataset from real Web services demonstrate its feasibility, effectiveness, and better Satisfaction Degree from the perspective of consumers.

The Benefits of Cloud Computing

Cloud computing is gaining ground in the global ICT market and day by day a significant number of Small and Medium Enterprises (SMEs) are adopting cloud services with sole purpose to improve their business environment and become more efficient, competitive and productive. Migrating a business IT infrastructure to the cloud offers reduction on server and storage costs, software maintenance expenditures, network and energy expenses as well as costs associated with disaster recovery. Since the cloud computing model works on a “pay-as-you-go” basis, it provides the option to pay for what is used. Thus, its adoption can offer slow start-up or expansion costs, creating an environment for rapid innovation and development. Into that context, this article presents the Greek side of cloud evolution through two representative case studies, the migration of an IT system of a Greek industry, from an in-house data center to Google Cloud and a study of the “in-house” IT infrastructure of the National Confederation of Hellenic Commerce. Findings from the Greek industry, indicate that the cloud proposal could cost 50%, or 24% less per month (depending on the solution). As far as the National Confederation of Hellenic Commerce is concerned, the article proposes only a new measure of security using Cloud services for reasons that will be discussed at the case study. Both case studies take into account the present costs of the IT system (energy consumption, third party contracts and maintenance) and propose alternatives through cloud migration. Results indicate that cloud computing offers benefits and significant cost savings for both studied cases, showing promising ways for the successful adoption of the cloud.

Current cloud challenges in Germany: the perspective of cloud service providers

Cloud computing has a significant impact on information and communication technology (ICT) and is one of the most important technological drivers of the digitalization of enterprises. However, due to the increasing dissemination of cloud services and the growing number of cloud service providers (CSPs), the uncertainty and risks for user companies in adopting cloud services have also increased. In this paper, we address those aspects from the perspective of the CSPs. We identified relevant literature and studies and conducted interviews with business experts from 16 German CSPs. In our results, we present current customer requirements and barriers to using cloud services from a provider’s viewpoint and identify the actions of and obstacles for CSPs in meeting the needs and constraints of the customers. Finally, we identify current and future challenges for CSPs in dealing with customer requirements and barriers by addressing their root causes. One of the main challenges from the CSPs’ perspective is addressing customers appropriately and building relationships of trust. This also “forces” changes in the sales processes. In this process, the essential challenges can be identified as an increase in complexity and a simultaneous simplification of specific sales activities. Therefore, the necessity arises for the continuous support of business relationships through value-adding and additional services. However, this results in another challenge for the CSPs – Namely, to find the right balance between standardization and meeting customer-specific requirements. In our paper, we show that the perspective of the CSPs is rarely discussed in the literature. Nevertheless, understanding the perceptions of the providers and their actions and measures is essential for future research activities in the field of cloud service selection. Comparing the customers’ perspectives and viewpoints with the CSPs’ actions will enhance the development of a holistic selection approach for future cloud projects. Therefore, our paper’s contribution to research is also the identification of this missing integration.

Space-Division Multiplexing in Data Center Networks: On Multi-Core Fiber Solutions and Crosstalk-Suppressed Resource Allocation

The rapid growth of traffic inside data centers caused by the increasing adoption of cloud services necessitates a scalable and cost-efficient networking infrastructure. Space-division multiplexing (SDM) is considered as a promising solution to overcome the optical network capacity crunch and support cost-effective network capacity scaling. Multi-core fiber (MCF) is regarded as the most feasible and efficient way to realize SDM networks, and its deployment inside data centers seems very likely as the issue of inter-core crosstalk (XT) is not severe over short link spans (<1 km) compared to that in long-haul transmission. However, XT can still have a considerable effect in MCF over short distances,which can limit the transmission reach and in turn the data center’s size. XT can be further reduced by bi-directional transmission of optical signals in adjacent MCF cores. This paper evaluates the benefits of MCF-based SDM solutions in terms of maximizing the capacity and spatial efficiency of data center networks. To this end, we present an analytical model for XT in bi-directional normal step-index and trench-assisted MCFs and propose corresponding XT-aware core prioritization schemes. We further develop XT-aware spectrum resource allocation strategies aimed at relieving the complexity of online XT computation. These strategies divide the available spectrum into disjoint bands and incrementally add them to the pool of accessible resources based on the network conditions. Several combinations of core mapping and spectrum resource allocation algorithms are investigated for eight types of homogeneous MCFs comprising 7–61 cores, three different multiplexing schemes, and three data center network topologies with two traffic scenarios. Extensive simulation results showthat combining bi-directional transmission in dense core fibers with tailored resource allocation schemes significantly increases the network capacity. Moreover, a multiplexing scheme that combines SDM and WDM can achieve up to 33 times higher link spatial efficiency and up to 300 times greater capacity compared to a WDM solution.

A Comparison of Competing Models for Understanding Industrial Organization’s Acceptance of Cloud Services

Cloud computing is the next generation in computing, and the next natural step in the evolution of on-demand information technology services and products. However, only a few studies have addressed the adoption of cloud computing from an organizational perspective, which have not proven whether the research model is the best-fitting model. The purpose of this paper is to construct research competing models (RCMs) and determine the best-fitting model for understanding industrial organization’s acceptance of cloud services. This research integrated the technology acceptance model and the principle of model parsimony to develop four cloud service adoption RCMs with enterprise usage intention being used as a proxy for actual behavior, and then compared the RCMs using structural equation modeling (SEM). Data derived from a questionnaire-based survey of 227 firms in Taiwan were tested against the relationships through SEM. Based on the empirical study, the results indicated that, although all four RCMs had a high goodness of fit, in both nested and non-nested structure comparisons, research competing model A (Model A) demonstrated superior performance and was the best-fitting model. This study introduced a model development strategy that can most accurately explain and predict the behavioral intention of organizations to adopt cloud services.

Status of Cloud Service Adoption in Climate Risk Country

Ghana has attained cloud readiness indices facilitating services adoption by local enterprises through brokerage firms. Accordingto Gartner group by 2015, at least 20% of all cloud services will be consumed via internal or external cloud service brokerages,rather than directly with service providers. It means enterprises must identify local cloud brokerage firms to intermediate for cloudclients and service providers. We aimed at surveying cloud service awareness among enterprises in Ghana. We performed fieldstudy using statistical tool to analyze data collected among 45-participants spread across 20 local enterprises, using purposivesampling in the selection of strategic enterprise managers located in the second largest city, Kumasi, Ghana. We employedDelphi technique involving three Information Technology experts to validate responses in reducing margin of error in the analysis.We found that 67% respondents are unaware of local cloud service brokerage firms. Alternatively, 33% respondents mentioned atleast one local cloud brokerage firm; although experts believed some did a chess guessing to have it correct. Our Delphi expertsattributed this alarming percentile to lack of policy stakeholders involvement in ensuring cloud adoption readiness. We concludedon effective sensitization of cloud computing service adoption in optimizing data center proliferation by enterprises in Ghana.Adopting cloud computing over data center helps in reducing global warming contributed by heat emissions from computingservers.

Antecedents and optimal industrial customers on cloud services adoption

ABSTRACT The rapid flourishing of the cloud service market necessitates investigating the underlying determinants of cloud services adoption and identifying optimal industrial customers for business-to-business (B2B) service encounters. Many studies have addressed technical and operational concerns related to cloud services. However, only a few studies have addressed the adoption of cloud computing from an organizational perspective, and none of them have considered the practical application of cloud computing in society. Therefore, in this paper, a research model is constructed to understand an industrial organization’s acceptance of cloud services and apply the results in order to explore optimal industrial customers. A questionnaire-based survey was used to collect data from the population, 227 firms in the manufacturing and services industries in Taiwan. Causal relationships were tested through structural equation modeling and the ordering of optimal industrial customers was evaluated by using the Technique for Order of Preference by Similarity to Ideal Solution method.

Određivanje faktora koji utiču na prihvatanje 'cloud' usluga u Indiji

This study identifies the factors influencing cloud services adoption in India using Unified Theory of Acceptance and Use of Technology (UTAUT) model. Role of perceived risk as a moderator in adoption of cloud services, too, has been examined along with other moderators such as gender, age, experience and voluntaries of use as stated in UTAUT model. Following a descriptive research design, a survey was conducted and a structured questionnaire was administered randomly to a sample of 379 respondents in Dehradun region. Most of the relationships confirmed to UTAUT model. Performance expectancy and effort expectancy emerged as the two most significant factors influencing cloud services adoption. Perceived risk, too, played a significant moderating role in adoption of cloud services. Cloud based services are relatively new to consumers in India. The benefits of these cloud technology can only be reaped fully if more and more customers adopt it. Also, various types of risks, such as financial loss, data loss, privacy etc., are associated with using cloud services. Therefore, this study may have immediate implications for cloud service providers.

Cost benefit analysis of cloud computing in education

Application of cloud computing in education not only relieves the educational institutions from the burden of handling the complex IT infrastructure management as well as maintenance activities, but also leads to huge cost savings. Along with many industry sectors, education sector would be largely benefited by adopting cloud services. Cloud promises to deliver affordable, reliable and flexible computing solutions to the education sector and enable it to compete more effectively with bigger organisations. The motive of this paper is to analyse the approach that has been followed to identify the benefits and limitations of cloud computing. Specific case of a lab setup has been taken to illustrate the financial aspects. A comparative analysis of cloud-based hosting versus conventional (on-premise) application deployment has also been presented.

Cost benefit analysis of cloud computing in education

Application of cloud computing in education not only relieves the educational institutions from the burden of handling the complex IT infrastructure management as well as maintenance activities, but also leads to huge cost savings. Along with many industry sectors, education sector would be largely benefited by adopting cloud services. Cloud promises to deliver affordable, reliable and flexible computing solutions to the education sector and enable it to compete more effectively with bigger organisations. The motive of this paper is to analyse the approach that has been followed to identify the benefits and limitations of cloud computing. Specific case of a lab setup has been taken to illustrate the financial aspects. A comparative analysis of cloud-based hosting versus conventional (on-premise) application deployment has also been presented.

An ontology-based cloud infrastructure service discovery and selection system

In recent years, due to global economic downfall, many of the organisations have resorted to downsizing their Information Technology (IT) expenses by adopting innovative computing models like cloud computing, which allows business houses to reduce their fixed IT costs by promising a greener, scalable, cost-effective alternative to utilise the IT resources. A growing number of pay-per-use cloud services are now available on the web in the form of Software as a Service (SaaS), Infrastructure as a Service (IaaS) and Platform as a Service (PaaS). With the increase in the number of services, there has also been an increase in demand and adoption of cloud services making cloud service identification and discovery a challenging task. This is due to varied service, descriptions, non-standardised naming conventions, heterogeneity in type and features of cloud services. Thus, selecting an appropriate cloud service according to consumer requirements is a daunting task, especially for applications that use a composition of different cloud services. In this paper, we have designed an ontology-based cloud infrastructure service discovery and selection system that defines functional and non-functional concepts, attributes and relations of infrastructure services. We have shown how the system enables one to discover appropriate services optimally as requested by consumers.

From business process models to the cloud: a semantic approach

The fast evolution of IT services and the shift from server-centred applications to widely distributed frameworks and platforms, of which cloud computing is the best representative, have highly conditioned the way enterprise managers deal with their businesses. Several tools for the design and execution of business processes have been proposed, together with standards for their formal representation, such as BPMN. Despite the expressivity of such tools and representations, there is still a lack of integration with cloud services, mostly due to the high variety of currently available offers, which creates confusion among customers. Moreover, portability and interoperability issues tend to hinder the adoption of cloud solutions for the immediate deployment of business processes. In order to overcome such issues and support the adoption of cloud services for the deployment of business processes, in this paper, a semantic approach is proposed. The presented representation aims at easing the mapping process and to suggest users the best suitable cloud services to compose. A case study which demonstrates the applicability and efficacy of the approach is also described.

An ontology-based cloud infrastructure service discovery and selection system

In recent years, due to global economic downfall, many of the organisations have resorted to downsizing their Information Technology (IT) expenses by adopting innovative computing models like cloud computing, which allows business houses to reduce their fixed IT costs by promising a greener, scalable, cost-effective alternative to utilise the IT resources. A growing number of pay-per-use cloud services are now available on the web in the form of Software as a Service (SaaS), Infrastructure as a Service (IaaS) and Platform as a Service (PaaS). With the increase in the number of services, there has also been an increase in demand and adoption of cloud services making cloud service identification and discovery a challenging task. This is due to varied service, descriptions, non-standardised naming conventions, heterogeneity in type and features of cloud services. Thus, selecting an appropriate cloud service according to consumer requirements is a daunting task, especially for applications that use a composition of different cloud services. In this paper, we have designed an ontology-based cloud infrastructure service discovery and selection system that defines functional and non-functional concepts, attributes and relations of infrastructure services. We have shown how the system enables one to discover appropriate services optimally as requested by consumers.