Cloud Business Research Articles

Development of the information and analytical system of the university

Today, the introduction of analytical systems into the university management circuit has become a necessary and priority task of higher educational institutions. It was led by the desire of the university management to understand the nature of data to improve the quality of educational services and decision-making. This article discusses the analysis of information systems, comparison of business intelligence platforms, and approaches to designing information and analytical system within the university as one of the key elements of the university’s information infrastructure. The presented work describes the data architecture of the corporate information systems of al-Farabi Kazakh National University, designing and implementing an information and analytical system at the university and on the Microsoft Power BI cloud business analysis platform. This system integrates all the disparate data of the university’s corporate information systems and transactional data sources. Furthermore, the logic of data extraction, transformation, implementation of visual reporting in Power BI, and the model of role-based access to them are also described.

A model of business intelligence on cloud for managing SMEs in COVID-19 pandemic (Case: Iranian SMEs)

A model of business intelligence on cloud for managing SMEs in COVID-19 pandemic (Case: Iranian SMEs)

Rural smart tourism under the background of internet plus

Rural tourism under the background of internet plus needs to improve the tourism model and improve the modernization process of rural tourism. In order to improve the efficiency of rural tourism, this paper constructs a rural smart tourism system under the background of internet plus, combines the actual situation of rural tourism to improve the traditional rural tourism model, and analyzes the application of internet plus technology in the architecture of smart tourism system. Moreover, this paper builds a cloud service-based rural tourism cloud data system architecture, and discusses how to build related systems, including the introduction of the cloud data center architecture and functions, the introduction of the architecture, composition and functions of the cloud business management platform, the introduction of the architecture and functions of the tourist behavior intelligent analysis system, etc. finally, this paper analyzes the performance of the rural smart tourism system through experiments. From the experimental research results, we can know that the rural smart tourism system constructed in this paper has certain effects.

Minimized False Alarm Predictive Threshold for Cloud Service Providers

Background: Cloud Security is a strong hindrance which discourages organisations to move toward cloud despite huge benefits. Distributed denial of service attacks operated via distributed systems compromise availability of cloud services which cause limited resources for authentic users and high expense for cloud service users and business owners. Objective: Techniques to identify distributed denial of service attacks with minimized false positives are highly required to ensure availability of cloud services to genuine users. Scarcity of solution which can detect denial of service attacks with minimum false positives and reduced detection delay has motivated us to compare classification algorithms for detection of distributed denial of service attacks with minimum false positive rate. Methods: Classification of incoming requests and outgoing responses using machine learning algorithms is a quite effective way of detection and prevention. We designed a performance tuned support vector machine algorithm with features of F-hold cross validation strategy. Results: F-hold crosses validation strategy, which can detect denial of service packets with 99.89% accuracy. Conclusion: This system ensures economic sustainability for business owners and limited resources mitigation for authenticated and valid cloud users.

Collaboration of Business Intelligence and Cloud Computing and Selecting the Best Cloud Business Intelligence Solution

In this study, business intelligence concept and architecture were explained from data sources to reporting with many advantages provided to institutions in the first part. Then, both cloud computing technology with its service and deployment models and the characteristics of cloud computing experienced clarified in the second part of the study. The relationship between cloud computing and business intelligence and the concept arisen from this collaboration, cloud business intelligence, were represented with its benefits and obstacles experienced by companies using this technology in the third part. Four service providers as alternatives serving cloud business intelligence solutions were selected and the criteria were determined according to the needs of the company, that would like to use a cloud business intelligence software. After all the criteria are prioritized and the alternatives are determined, the best software was chosen by using the Analytic Hierarchical Process software, called Expert Choice.

The use of cloud computing technology in professional training of future programmers

The article provides a brief analysis of the current state of the study of cloud technologies by future software engineers at foreign and Ukrainian universities. The author experience in the application of cloud technologies in the training of future software engineers in Ukraine is presented. The application of cloud business automation systems, online services to monitor the implementation of the software projects, Google services for collaboration, planning and productivity while studying professional disciplines and carrying out diploma projects is described. Based on the survey conducted at Stackoverflow, the state of application of cloud technologies by software engineers around the world has been analyzed. The cloud technologies that are not studied at the analyzed universities of Ukraine and those that are not popular with software developers in the world, but studied at Ukrainian universities by future software engineers are outlined. Conclusions are made on the modernization of training programs for future software engineers. Topics for the study of cloud technologies by future software engineers in the content of professional disciplines are proposed.

Conceptualising a Cloud Business Intelligence Security Evaluation Framework for Small and Medium Enterprises in Small Towns of the Limpopo Province, South Africa

The purpose of this study was to investigate security evaluation practices among small and medium enterprises (SMEs) in small South African towns when adopting cloud business intelligence (Cloud BI). The study employed a quantitative design in which 57 SMEs from the Limpopo Province were surveyed using an online questionnaire. The study found that: (1) the level of cybersecurity threats awareness among decision-makers was high; (2) decision-makers preferred simple checklists and guidelines over conventional security policies, standards, and frameworks; and (3) decision-makers considered financial risks, data and application security, and cloud service provider reliability as the main aspects to consider when evaluating Cloud BI applications. The study conceptualised a five-component security framework for evaluating Cloud BI applications, integrating key aspects of conventional security frameworks and methodologies. The framework was validated for relevance by IT specialists and acceptance by SME owners. The Spearman correlational test for relevance and acceptance of the proposed framework was found to be highly significant at p < 0.05. The study concluded that SMEs require user-friendly frameworks for evaluating Cloud BI applications. The major contribution of this study is the security evaluation framework conceptualised from the best practices of existing security standards and frameworks for use by decision-makers from small towns in Limpopo. The study recommends that future research consider end-user needs when customising or proposing new solutions for SMEs in small towns.

SecAuth-SaaS: a hierarchical certificateless aggregate signature for secure collaborative SaaS authentication in cloud computing

Collaborative cloud business models enable a new dimension of business by giving option to the third party software vendors to deploy their software in the cloud for offering software as a service (SaaS) to the users. However, the secure provisioning of resources requires scalable architecture with efficient authentication for configuring the collaborative software services in the cloud. In this paper, we propose a novel hierarchical certificateless aggregate signature to provide a scalable authentication model for SaaS in cloud computing. Our proposed scheme is secure under the adaptive chosen-message attack in the random oracle model with the hardness assumption of Computational Diffie–Hellman (CDH) problem and Decisional Diffie–Hellman (DDH) problem. Furthermore, our proposed scheme is highly efficient regarding low overhead on computation and communication cost.

Aspect of join ingress authority for civic directory

T Nowadays, Cloud computing is a major and emerging platform that provides various IT related services. The two major factors which inhibit the growth of cloud computing are privacy and security. Hackers can break into public or private cloud environment and steal the data. They can use it with malicious intent such as either use or sell the sensitive information obtained from the business cloud environment. Hence, user’s safety depends upon security level in cloud service providers. For an enterprise, there are enormous amount of data is stored and most of them are sensitive information which can affect huge number of people or an entire business organization. Networks are the medium through which all tasks are performed. For access control, being one of the classic research topics, various schemes have been proposed and implemented. In existing key policy, when the key which provides access to the data falls into the wrong hands, they can use it with malicious intent such as steal or alter the data or sell the sensitive information obtained from the business cloud environment. Using our proposed algorithm, we can able to provide a collaborative access control scheme for public cloud storage. This system is implemented using encryption method called Attribute Based Encryption. Encrypting data ensures that even if the data falls into the wrong hands, it is useless as long as its keys remain secure. Even when the hacker gets access to the key, he cannot access the data as only the assigned users can access the data using the key.

A multi-objective privacy preservation model for cloud security using hybrid Jaya-based shark smell optimization

The rising volume of sensitive and personal data being harvested by data controllers has increased the security essentials in the cloud system. The cloud module is not used just to store the data, but also to process them on cloud premises. Security for the cloud premises is essential as the cloud has lot of outsourced, unprotected sensitive data for the public access. This has resulted repeated data violations, and thus there is a need for the advanced legal data protection constraints. Various studies were conducted to adopt the privacy preservation in the cloud, and most of the state-of-the-art techniques fail to handle the optimal privacy when dealing with sensitive data, as it requires separate data sanitization and restoration models. To overcome this challenge, this paper tempts to develop the privacy preservation model in the cloud environment using the advancements of artificial intelligent techniques. Artificial Intelligent capabilities are working in the business cloud computing environment to make organizations more efficient, strategic, and insight-driven. However, by hosting the data, cloud computing offers businesses high flexibility, agility, and cost savings. The two main phases of the proposed privacy preservation system are the data sanitization and restoration. Moreover, the proposed sanitization process depends on the optimal key generation, which is performed by the hybrid meta-heuristic algorithm. This hybrid algorithm merges two well-performed algorithms, such as Shark Smell Optimization (SSO) and Jaya Algorithm (JA), and thus termed as Jaya-based Shark Smell Optimization (J-SSO). The optimal key generation is accomplished by deriving a multi-objective function that involves the parameters, such as the degree of modification, hiding ratio, and information preservation ratio. Finally, the performance analysis has proved the efficiency of the proposed model over the state-of-the-art models in enhancing cloud security.

A cloud dynamic online double auction mechanism (DODAM) for sustainable pricing

The Cloud is a new computing paradigm that has experienced exponential growth in recent years. Therefore, success in the cloud services industry can be a challenge, as satisfying both cloud service users and providers is challenging. Cloud users expect to receive a higher service quality with the lowest possible prices. On the other hand, cloud service providers need to maximize their revenues by utilizing energy-efficient resources while adopting prices that attract the most customers. As such, the success of a business in cloud computing depends on the equal consideration of cloud service providers’ and users’ needs. This paper proposes a long-term organic solution based on a double auction model that encompasses the varying natures of both strategic players and cloud resources. We develop the dynamic online double auction mechanism (DODAM) and coin the concept of sustainable pricing for cloud computing services. A dynamic online platform that is capable of realistically modelling cloud ecosystems distinguishes the DODAM model from other studies using a double auction mechanism. Based on experimental results, we prove that the proposed model outweighs other double auction models in terms of the social welfare and truthfulness pillars.

Low-latency cloud-fog network architecture and its load balancing strategy for medical big data

In order to apply fog computing to the field of medical big data, this paper proposes a low-latency hybrid cloud-fog network architecture for medical big data, which can solve the processing delay of business in cloud computing center architecture. In this architecture, edge network equipment such as routers and switches in the hospital are used to build a “fog computing” layer between the cloud server and terminals. Then, the computing service for medical data on the cloud is moved to fog equipment for processing, which reduces the processing delay of medical businesses. Besides, it reduces the computing load on cloud servers and improves the overall robustness of network. For further optimizing the processing delay of business in the above network architecture, we study the load balancing strategy in fog computing network. Due to the global search ability of bat algorithm is strong, the convergence speed is fast and it is easy to implement. Therefore, this paper uses bat algorithm to solve the optimization problem in medical big data scenario. Bat algorithm is better than genetic algorithm and particle swarm optimization on the unconstrained optimization problems. However, it also suffers from problems such as local optimization and slow convergence. To solve this problem, we utilize load balancing to initialize bat population data that improves the quality of solution for initial samples. After getting the best bats, a Powell local search is performed on them, which speeds up the convergence of our algorithm. Finally, simulation results show that the proposed hybrid cloud-fog network architecture can reduce the processing delay of medical big data and improve user experience effectively.

Cloud computing ecosystem model: evaluation and role clusters

Several significantly different attempts have been undertaken to visualize the complex and opaque cloud computing ecosystem by a descriptive model. Recently, scholars have developed a new role-based cloud ecosystem model (Passau Cloud Computing Ecosystem Model (PaCE model)) based on a systematic analysis and synthesis of the previous models. However, its scientific evaluation is still outstanding. The main goal is therefore to conduct an evaluation regarding its structural equivalence and completeness compared to the real cloud business according to the design science research paradigm. The second goal is to demonstrate the model’s usefulness by using it as an instrument for the identification of role clusters, which are frequently covered by organizations. To this end, a cross-sectional analysis is conducted, in which 758 organizations are manually analysed and matched with the model’s current roles. As a result, roles have been newly added, removed, broken down into sub-roles, abstracted to a meta-role and renamed. The cluster analysis unveiled five role clusters. Whereas some roles were predominantly found as single role, further roles were exclusively or very frequently found in combination with others. Overall, the revised model creates, compared to the common rather technically orientated market overviews by market research institutes, a detailed categorization schema helping to understand and investigate the organizations belonging to the cloud ecosystem.

Runtime Verification of Business Cloud Workflow Temporal Conformance

Business cloud workflows are often designed with multiple time constraints for timely response to business requests. To ensure on-time completion of workflow instances, workflow temporal conformance state needs to be constantly monitored and verified at runtime. Considering the fact that there are a large number of workflow instances running in a parallel fashion in many business scenarios, conventional verification approaches for time-related properties using such as temporal logic or timed Petri nets are not feasible due to the limitation of low efficiency at runtime. To address this issue, we propose a new approach to automated runtime verification of temporal conformance for parallel workflow instances in a cloud environment. Instead of using response time to verify temporal conformance of every single workflow as in conventional strategies, workflow throughput is employed as the performance measurement to efficiently monitor a large number of parallel workflow instances. On this basis we present a novel conformance verification strategy. This strategy considers the effect of time delay propagation in the cloud workflow systems to accurately verify workflow runtime temporal conformance. Our verification strategy is implemented in a prototype cloud workflow system and the evaluation results show that it outperforms the state-of-the-art workflow temporal verification strategy.

The Construction Scheme of D-Iot Cloud Master Station

With the development of the Energy Internet, specific requirements are put forward for the Distribution Internet of Things technology. How to control the panoramic equipment and data through a horizontalization of all links and a secondary level of operation on the entire business cloud. And provide external platforms and applications. This article first proposes the architecture of the IoT cloud platform for distribution IoT, and discusses open cloud platform, Internet of Things access and equipment management, data storage and management technology, cloud edge collaboration, and other key technologies. Finally, it discusses application scenarios based on IoT technology, such as panoramic condition monitoring based on multi-dimensional information perception, tiered line loss hierarchical layered management, low voltage fault location. To provide technical support for the ubiquitous electric power Internet of Things in order to realize the interconnection of all things and human-computer interaction in all aspects of the power system, create a comprehensive status perception, efficient information processing, and convenient and flexible application.

Analysis of Using Cloud Business in Bosnia and Herzegovina and the Region

Cloud business is the basic support to operations of modern companies. It enables companies to be more agile and innovative. Such form of digital transformation improves business and company productivity and solves business problems in innovative ways. On one hand, Cloud business makes possible for users to get the best expertise possible which they cannot develop independently. On the other hand, it offers possibilities to reduce the costs related to hardware and software to a reasonable level. The time value of money present in Cloud business is also significant. Namely, companies no longer need to invest large sums of money in equipment or software solutions; it is sufficient to rent those and use revenues for future business investments. Cloud solutions mean that users, using modern technology, access their business software solution through a web browser (web application) thus completing their business processes and accessing the database. Expansion of business leads to a new phenomenon – users are no longer tied to a physical location. In this way, users more frequently work from home or on the move by using different mobile devices. We all use a number of applications (Gmail, outlook.com, Facebook, LinkedIn, Twitter etc.) and take advantage of the Cloud business without being aware of it. We do not install any of the mentioned applications on our devices but access those using an internet browser. Given the lack of IT experts due to economic migrations, as is the situation here, insufficient supply and enormous demand for IT professionals, the traditional model of using business information systems will become practically unsustainable. In this paper, following introductory and general remarks on Cloud business, an analysis was made of using Cloud business IT systems in RS/BH, Serbia and the EU.

Intelligent CRM systems of transport companies

High technological efficiency and the use of intelligent systems are the main internal factors in the evolution of the transport company. Transportation companies are introducing digital infrastructure, trying to achieve practical results by focusing on customer demand, such as actively using Customer Relationship Management and holding on to the customer, increasing their loyalty. But there are problems in activating such systems because of their heterogeneity and non-systemic approach to their use. A system analysis is needed, which is the main purpose of this article. This problem is discussed in this article for highly competitive transport (logistics) business. The capabilities and impact of the transport company 's customer relationship management systems in the cloud are analyzed. The method of organization and regulation of business processes oriented to relations with clients, creation and development of cloud business infrastructure is proposed. The evolutionary cycle of the transport system in cloud infrastructure is described. A comprehensive multiplicative transportation efficiency model similar to the Allen model has been built and described how to use it to evaluate system self-regulation. The results of the work can become a methodological basis for solving practical problems of business processes of transport systems and their transfer to cloud infrastructure.

Efficient Secure and Novel Access Control Model for XML-Based EHRS

Millions of private pictures are created in precise virtual gadgets each day. The resulting large computational workload makes humans hotel to shadow computing systems for his or her value-effective calculation assets. Meanwhile, the privateers troubles over the sensitive facts blanketed in outsourced photo records emerge in public. In truth, whilst published to shadow, the safety similarly to privateers of the photograph fabric can handiest presume upon the integrity of the cloud business enterprise. Absence of making sure protection and security and moreover privateers ensures becomes the critical impediment to in addition launch of cloud-based picture handling systems. This paper studies the format targets and also technical boundaries hinge on building cloud-based totally absolutely privacy-preserving photograph processing machine. We find out specific image processing duties, which include image characteristic discovery, virtual watermarking, and content fabric-based image searching for. The superior strategies, which include secure multiparty computation and homomorphism safety are investigated. An in-depth taxonomy of the problem declaration and additionally the corresponding alternatives is provided.

Modeling cloud business customers’ utility functions

Modeling a utility function for cloud business customers is one of the critical challenges facing many cloud service providers (CSPs) for their pricing strategy. It concerns how to measure various subjective experiences of the business customers and how to translate their cloud service experiences into a quantifiable unit, which can be determined by a utility function that reflects cloud resource consumption. The aim of this modeling process is to set up a pricing foundation so that CSPs can target a broader range of customers from various market segments and identify the optimal price point of their various pricing models. Previous studies have either focused on simple theoretical proof or drifted the meaning of utility between demand and supply or proposed a solution based on a uniform cloud market assumption. This paper proposes a novel and practical solution to define multiple utility functions based on a scenario of six cloud market segments, which are analyzed by three analytic approaches that are known as Markov chains analysis, queueing theory, and risk assessment. The entire pricing strategy emphasizes value co-creation between CSP and cloud business customers. In comparison with other methods, such as calibrated, price-quality, resource-based, simple linear, and capacity-aware, this method provides both internal and external rationalities for CSP to capture the subjective value of cloud business customers. Consequently, our experiment results show that this modeling method can increase a profit margin by 51% and decrease a unit cost by 22% for a CSP.

Optimising infrastructure as a service provider revenue through customer satisfaction and efficient resource provisioning in cloud computing

With limited resources, it is quite challenging for cloud providers to meet dynamic and massive customers' demands. Higher utilisation or refusing any service level agreement (SLA) may lead to penalties which play a crucial role in the cloud business. Overutilisation of resources, instead of maximizing the revenue, may lead to a decrease in revenue due to the SLA violations. Various studies have been conducted to investigate these issues; however, there is still room for improvement. In this study, the authors proposed a model to address the resource scalability and SLA violation issues by hiring external resources at low prices. However, in contrast to a federated cloud, the proposed model allows a provider to hire resources from any external provider with flexible terms and price. They designed algorithms to optimise providers' revenue by taking into account different parameters, including resource utilization, customer satisfaction, SLA violation, and prices. Simulation result shows that the proposed model is efficient in handling massive demands, and improves revenue generation and customer satisfaction. Offering joint pricing on customers' choice and outsourcing the extra workload to external resources leads to revenue maximization. Hiring external resources earns external revenue as well as it maximizes the total revenue.