Cloud Computing Services Research Articles

CURRENT STATE, TRENDS AND CHALLENGES OF CHINA’S DIGITAL TRADE

The digitalization of economy has a significant impact on the economic sector and on other activities. In recent years, there has been a sharp increase in the digitalization of the economy in China, primarily in such an area as digital trade. China's digital trade has grown steadily in recent years, and its share in China's trade has also increased. This article proposes the term “digital trade” and presents its characteristics. Analyze the state of the China’s digital trade, the features and main trends in the development of digital trade in goods and services. In addition, put forward current problems in the development of digital trade in China. It is concluded that digital trade in China as a whole has a positive trend, but in the future, instead of digital trade in goods, digital trade in services will become a major driving force of China's digital trade. With the development of cloud computing, cloud outsourcing and offshore services will become a new sector of digital services trade in the coming years. It was noted that China's digital trade is a driver for innovative trade growth and has an active impact on China's trade and economic activity.

Riscos da computação em nuvem: estudo na ótica dos gestores de órgãos públicos federais no Brasil

This work aimed to evaluate the risks when deploying Cloud Computing services from the perspective of managers of federal public agencies in Brazil. To achieve the proposed objective, semi-structured interviews were conducted with tactical level servers, involved with the management of information technology of ten Federal Public Administration agencies. The data were analyzed based on the recommendations of international entities to face risks of this nature, based on nine dimensions: governance; legislation and regulations; compliance and auditing; business continuity; security; isolation; identity and access management; data protection; and incident response. The results showed that there is still a way to go to implement these services in Public Administration, especially when it comes to questions about the risks that are linked to their use, with attention to the treatment of sensitive data. In addition, to implement the cloud computing service as proposed by the Digital Transformation Strategy, the findings suggest the need to face risks of complex transposition, a fact that works as an incentive to delay the implementation of this technology by Brazilian government entities.

Resource Management and Pricing for Cloud Computing Based Mobile Blockchain With Pooling

In a public blockchain system applying Proof of Work (PoW), the participants need to compete with their computing resources for reward, which is challenging for resource-limited devices. Mobile blockchain is proposed to facilitate the application of blockchain for mobile service, in which the lightweight devices can participate mining by renting resources from the Cloud Computing Service Provider (CCSP), but CCSP usually does not have the information about the demand preference of users. In this paper, a contract model is adopted to address the cloud computing resource allocation and pricing problem in the mobile blockchain. In particular, an adverse selection contract solution is proposed to overcome the information asymmetry problem, and resource pooling is introduced to improve the stability of users rewards. Simulation results show that the information asymmetry problem is well overcome by adverse selection contract so that CCSP can obtain more utility than linear pricing contracts. Furthermore, the resource pooling could effectively improve the users and CCSPs utilities. When the size of the mining pool is large enough, it can achieve an improvement effect of more than 10 times. The effect of pool size and user type distribution on CCSPs utility is also studied.

A comparison of Machine Learning Methods to predict Hospital Readmission of Diabetic Patient

Diabetes is a chronic disease whereby blood glucose is not metabolized in the body. Electronic health records (EHRs) for each individual or a population have become important to standing developing trends of diseases. Machine/Deep Learning helps provide accurate predictions higher than actual assessments. The main problem that we are trying to apply Machine/Deep learning model and using EHRs that combines the strength of a machine learning model with various features and Hyper-parameter optimization or tuning. The Hyper-parameter optimization uses the random search optimization which minimizes a predefined loss function on given independent data. The evaluation on the method comparisons indicated that Machine/Deep Learning models (Logistic Regression, Artificial Neural Network, Naïve Bayesian Classifier, Support Vector Machine and XGBoost) has improved results compared to the majority of previous models increasing the ratio of metrics (Accuracy, Recall, F1 and AUC score) on the same public dataset that is reprocessed. This shows that the proposed XGBoost model implemented in Amazon SageMaker (Amazon SageMaker was a Cloud Computing service) has the best performance evaluation results. This work is also one of the contributions to the global economic recovery in general and the reduction of medical equipment supply for the care and treatment of diabetics in particular during the Covid-19 pandemic.

Development of Multisource Cloud Logs Forensic with encase Tool for performing Lock Technique using Deep Analysis and Reporting

Encase and FTK tool will be utilised too much in Cyber security. In view of this Cloud forensic is an research which would be binded together by cloud computing and cyber security. Cyber forensic is connected to cloud computing and different services of CC such as Infrastructure-As-A-Service (IaaS), Platform-As-A-Service (PaaS),Software-As-A-Service(SaaS) ,Data-StorageAs-A-Service (DSaaS) will be applied in different domains.. cloud forensic techniques will be used if any attacks on software, platforms, infrastructure, and storage must be investigate, report and recovered data . Many cloud forensic techniques has been innovated and proposed in literature and tools have been using in IT industries to provide secure cloud services. With this evaluation of techniques and tools, attackers evolve their anti-forensic techniques as well to break the security measures. Hence the continuous monitoring and research care is indeed required in cyber security and forensic fields.. Hence log recovery and forensic have been given highest priority on cloud resources and functioning towards improving the cloud security and cloud forensic systems.

A Privacy-Preserving Outsourcing Data Storage Scheme with Oruta Data Auditing

Cloud Computing has been envisioned as the next generation architecture of IT Enterprise. In contrast to traditional solutions, where the IT services are under proper physical, logical and personnel controls, Cloud Computing moves the application software and databases to the large data centers, where the management of the data and services may not be fully trustworthy. With cloud computing and storage, users are able to access and to share resources offered by cloud service providers at a lower marginal cost. With cloud computing and storage services, data is not only stored in the cloud, but routinely shared among a large number of users in a group. In this project, we propose Oruta, a privacy-preserving auditing scheme for shared data with large groups in the cloud. We utilize ring signatures to compute verification information on shared data, so that the TPA is able to audit the correctness of shared data, but cannot reveal the identity of the signer on each block. We can implement the batch auditing scheme to perform efficient public auditing to protect both identity and data privacy in cloud environments.

Dual Encryption based secured data maintenance using Fog Computing

Many people and organizations are accessing data in the cloud due to the rapid growth of cloud computing .Fog computing interface used between cloud and the end devices to reduce the overhead of the cloud computing and better network services, with secure data transmission requirement. In this paper, Identity Based Broadcast Encryption with Decrypting Time Interval (IBBE-DTI) scheme is proposed for protecting the data securely. This facilitates the data to be encrypted with authentication token which is the combination of private key and identities of users who wants the data. To increasing the security, data owner additionally set decrypting time interval along with the data to be encrypted which leads to additional key namely Time Secret Key (TSK) for decryption. This paper proposed a dual verification process for efficient user authentication based on authorization token, which will be defined by the data owner, and a Unique Signature, which will generate by the fog processor at the time of encryption. This proposed work supports both security of data and verifies the user authentication for efficient data transmission with low computation overhead.

A Study on the Relationship between Cloud Computing Service and the Subcontracting Act

A Study on the Relationship between Cloud Computing Service and the Subcontracting Act

On-the-Fly Fusion of Remotely-Sensed Big Data Using an Elastic Computing Paradigm with a Containerized Spark Engine on Kubernetes.

Remotely-sensed satellite image fusion is indispensable for the generation of long-term gap-free Earth observation data. While cloud computing (CC) provides the big picture for RS big data (RSBD), the fundamental question of the efficient fusion of RSBD on CC platforms has not yet been settled. To this end, we propose a lightweight cloud-native framework for the elastic processing of RSBD in this study. With the scaling mechanisms provided by both the Infrastructure as a Service (IaaS) and Platform as a Services (PaaS) of CC, the Spark-on-Kubernetes operator model running in the framework can enhance the efficiency of Spark-based algorithms without considering bottlenecks such as task latency caused by an unbalanced workload, and can ease the burden to tune the performance parameters for their parallel algorithms. Internally, we propose a task scheduling mechanism (TSM) to dynamically change the Spark executor pods’ affinities to the computing hosts. The TSM learns the workload of a computing host. Learning from the ratio between the number of completed and failed tasks on a computing host, the TSM dispatches Spark executor pods to newer and less-overwhelmed computing hosts. In order to illustrate the advantage, we implement a parallel enhanced spatial and temporal adaptive reflectance fusion model (PESTARFM) to enable the efficient fusion of big RS images with a Spark aggregation function. We construct an OpenStack cloud computing environment to test the usability of the framework. According to the experiments, TSM can improve the performance of the PESTARFM using only PaaS scaling to about 11.7%. When using both the IaaS and PaaS scaling, the maximum performance gain with the TSM can be even greater than 13.6%. The fusion of such big Sentinel and PlanetScope images requires less than 4 min in the experimental environment.

Analyzing Continuance of Cloud Computing in Higher Education Institutions: Should We Stay, or Should We Go?

Higher Education Institutions (HEIs) consider resource optimization as an essential concern. Cloud computing (CC) in the fourth industrial revolution became the de-facto standard for delivering IT resources and services. CC is now a mainstream technology, andHEIs across the globe are rapidly transitioning to this model; hence, maintaining the retention of the customers of such technologies is challenging for cloud service providers. Current research concerning CC focused on adoption and acceptance. However, there is still a scarcity of research concerning such technology’s continued use in an organizational setting. Drawing on the prior literature in organizational-level continuance, this paper established a positivist quantitative-empirical study to bridge the research gap and assess the precursors for a continuance of cloud technology in HEIs. Subsequently, this study developed a conceptual framework by integrating the IS success model and the IS discontinuance model through the lens of the TOE framework. The data were collected from the decision-makers of Malaysian HEIs that have adopted CC services, and analyzed using Structural equation Modelling (SEM) based on Partial Least Squares (PLS). The results indicate that the continuance intention can be predicted by technology, organizational, environmental, and other contextualized factors, explaining 85.2% of the dependent variables’ variance. The paper closes with a discussion of the research limitations, contribution, and future directions.

An Algorithm to Minimize Energy Consumption and Elapsed Time for IoT Workloads in a Hybrid Architecture.

Advances in communication technologies have made the interaction of small devices, such as smartphones, wearables, and sensors, scattered on the Internet, bringing a whole new set of complex applications with ever greater task processing needs. These Internet of things (IoT) devices run on batteries with strict energy restrictions. They tend to offload task processing to remote servers, usually to cloud computing (CC) in datacenters geographically located away from the IoT device. In such a context, this work proposes a dynamic cost model to minimize energy consumption and task processing time for IoT scenarios in mobile edge computing environments. Our approach allows for a detailed cost model, with an algorithm called TEMS that considers energy, time consumed during processing, the cost of data transmission, and energy in idle devices. The task scheduling chooses among cloud or mobile edge computing (MEC) server or local IoT devices to achieve better execution time with lower cost. The simulated environment evaluation saved up to 51.6% energy consumption and improved task completion time up to 86.6%.

Lightweight fog computing-based authentication protocols using physically unclonable functions for internet of medical things

The Internet of Medical Things (IoMT) is a network of connections between a medical information system and medical equipment. Fog computing for IoMT is a model for extending cloud computing and medical services to the edge of the network, but the conventional fog computing model does not support some necessary features, such as device-to-device (D2D) communications for the effective exchange of data and processing thereof between devices in the IoMT. This investigation develops a secure authentication scheme for the fog computing model with cooperative D2D communication support. Since the power and resources of the medical sensors are limited, the proposed protocols use lightweight cryptographic operations, including a one-way cryptographic hash function, the Barrel Shifter Physically Unclonable Function (BS-PUF), to ensure the security of the sensors and fog nodes and to avoid a computational burden on devices. The proposed protocols not only resist possible attacks and provide more security than related schemes, but also are more efficient.

A State of Art for Smart Gateways Issues and Modification

The Internet of Things (IoT) is a collection of objects such as sensors, actuators, and processors, which interconnected within a specific network to perform a task collaboratively. The IoT is one of the prevalent technologies, which has developed dramatically in recent years. Its reputation derives from its relevance and role in employing things in the best way, starting with smartphones that opened new horizons in control technologies and later developing new ideas regarding cloud-computing services. A smart gateway plays an essential role in the IoT applications that responsible for enabling communication between the network layer and the ubiquitous sensors network layer. IoT gateways are methods that operate with influential data centers as a point of communication between lower-end users. IoT gateways connect the heterogeneous devices in use and carry out many tasks to accomplish the computing mission. This work searches how IoT gateway's function and how they interact. In particular, it lists interface issues related to IoT gateways. In this paper, we research IoT and Smart Gateways and address Smart Gateways problems and computing techniques to promote IoT programs' stable transition to the Smart Gateway.

3D Simulation-Based Acoustic Wave Resonator Analysis and Validation Using Novel Finite Element Method Software.

This work illustrates the analysis of Film Bulk Acoustic Resonators (FBAR) using 3D Finite Element (FEM) simulations with the software OnScale in order to predict and improve resonator performance and quality before manufacturing. This kind of analysis minimizes manufacturing cycles by reducing design time with 3D simulations running on High-Performance Computing (HPC) cloud services. It also enables the identification of manufacturing effects on device performance. The simulation results are compared and validated with a manufactured FBAR device, previously reported, to further highlight the usefulness and advantages of the 3D simulations-based design process. In the 3D simulation results, some analysis challenges, like boundary condition definitions, mesh tuning, loss source tracing, and device quality estimations, were studied. Hence, it is possible to highlight that modern FEM solvers, like OnScale enable unprecedented FBAR analysis and design optimization.

Data Center Enhancement by Server Resources Utilization

Data centers are the main nerve of the Internet because of its hosting, storage, cloud computing and other services. All these services require a lot of work and resources, such as energy and cooling. The main problem is how to improve the work of data centers through increased resource utilization by using virtual host simulations and exploiting all server resources. In this paper, we have considered memory resources, where Virtual machines were distributed to hosts after comparing the virtual machines with the host from where the memory and putting the virtual machine on the appropriate host, this will reduce the host machines in the data centers and this will improve the performance of the data centers, in terms of power consumption and the number of servers used and cost.

Providing Predictable Quality of Service in a Cloud-Based Web System

Cloud-computing web systems and services revolutionized the web. Nowadays, they are the most important part of the Internet. Cloud-computing systems provide the opportunity for businesses to undergo digital transformation in order to improve efficiency and reduce costs. The sudden shutdown of schools and offices during the pandemic of Covid 19 significantly increased the demand for cloud solutions. Load balancing and sharing mechanisms are implemented in order to reduce the costs and increase the quality of web service. The usage of those methods with adaptive intelligent algorithms can deliver the highest and a predictable quality of service. In this article, a new HTTP request-distribution method in a two-layer architecture of a cluster-based web system is presented. This method allows for the provision of efficient processing and predictable quality by servicing requests in adopted time constraints. The proposed decision algorithms utilize fuzzy-neural models allowing service times to be estimated. This article provides a description of this new solution. It also contains the results of experiments in which the proposed method is compared with other intelligent approaches such as Fuzzy-Neural Request Distribution, and distribution methods often used in production systems.

Design of Military Service Framework for Enabling Migration to Military SaaS Cloud Environment

The military of the Republic of South Korea applies infrastructure as a service (IaaS) cloud-computing technology and applications distributed nationwide are transferred to two defense-integrated data centers (DIDCs). However, to improve the quality of the military information service provided by the DIDCs, it is crucial to expand the cloud-computing service from IaaS to the software as a service (SaaS) level. Owing to the in-house planning, development and operation of military applications by the Ministry of National Defense and each military force, these organizations operate several applications that are similar and redundant. Accordingly, SaaS can reduce the costs of IT services and management overhead by eliminating similar and redundant applications and integrating them into common services. In this study, a military service framework (MSF) was designed based on the criteria of business functions and service targets. The MSF was applied to applications currently in operation to create a current military SaaS portfolio, whereas the future military SaaS portfolio was restructured by identifying common services within and between organizations and throughout the military. Consequently, 369 future military SaaS portfolios were created, representing a 36% decrease realized by integrating similar and redundant systems out of 580 applications.

Cloud Computing in Solving Problems of COVID-19 Pandemic

Cloud computing facilitates collaboration, communication, and essential online services during the COVID-19 crisis. The current situation of the COVID-19 pandemic has compelled people to work from their homes, but they have to communicate, collaborate online. Thus, we see an essential role of cloud computing in taking up this challenge of working from home and delivering efficiently. A brief review of Cloud Computing service in the context of COVID-19 pandemic is done using recent papers’ by searching keywords such as “Cloud Computing” and “COVID-19” from PubMed’s database SCOPUS and Google Scholar. During the lockdown situation, cloud computing technology helps provide commendable service in the healthcare domain. It provides an advanced infrastructure for facilitating digital transformation. A brief discussion has been made on how cloud computing components are vital for overcoming the ongoing situation. This paper also studies the remote working of cloud computing for the COVID-19 pandemic and finally identified significant cloud computing applications for the COVID-19 pandemic. All countries focus on reducing this virus’s spread, so this technology helps minimize the spread of this virus by providing online services. It provides an innovative environment that enhances the creativity and productivity of healthcare workers. This technology is efficient in detecting, tracking, and monitoring newly infected patients. In the future, this technology will insight and provide control over this infection to save millions of lives worldwide. This technology is also quite helpful to forecast the future impact of the SARS-Co-2 virus.

Experience of FRC CSC RAS in providing high-performance computing cloud services for materials science problems

To solve the problems of materials science, including multiscale modeling for the synthesis of materials with specified properties, a modern digital platform for scientific research has been created at the FRC CSC RAS. The digital platform is a combination of a competence center, a high-performance computing complex and a set of scientific services that are provided to researchers in the form of traditional cloud services in software (SaaS), platform (PaaS) and infrastructure (IaaS) services, as well as using specific technologies for providing researchers scientific service as a service (RaaS, Research as a Service).Other examples of scientific fields for which scientific services are used in conjunction with high-performance computing services are: biomedical chemistry, crystallography, computational linguistics, artificial intelligence.The article describes the information and computing environment of the sharing research facilities Center for Collective Use “Informatics”, which forms the basis of the instrumental and technological infrastructure for prototyping, as well as the layout of the control system for deterministic scientific services of the digital platform.The article presents the results of experimental studies carried out in relation to algorithms for the transfer and intermediate storage of initial data, data exchange services when interacting with a platform user, cloud scientific high-performance computing services, algorithms for the interaction of data exchange adapters when ensuring interaction between the platform, which are relevant in solving problems of multiscale modeling for the synthesis of materials with desired properties.The results obtained allow us to evaluate the practical aspects of the functioning of a digital platform for scientific research, designed for the effective organization of scientific research and management of the scientific instrument base in the interests of a wide range of research teams and industrial consumers.

Liability within the scope of Cloud Computing services

The issue of acquiring large amounts of data and creating large sets of digital data, and then processing and analyzing them (Big Data) for the needs of generating artificial intelligence (AI) solutions is one of the key challenges to the development of economy and national security. Data have become a resource that will determine the power and geopolitical and geoeconomic position of countries and regions in the 21st century.The layout of data storage and processing in distributed databases has changed in recent years. Since the appearance of hosting services in the range of ICT services, we are talking about a new type of ASP (Applications Service Providers) – provision of the ICT networks as part of an application). Cloud Computing is therefore one of the versions of the ASP services. The ASP guarantees the customer access to a dedicated application running on a server. Cloud Computing, on the other hand, gives the opportunity to use theresources of a shared infrastructure for many users simultaneously (Murphy n.d.). The use of the CC model is more effective in many aspects. Cloud Computing offers the opportunity to use three basic services: data storage in the cloud (cloud storage), applications in the cloud (cloud applications) and computing in the cloud (compute cloud). Website hosting and electronic mail are still the most frequently chosen services in Cloud Computing. The article attempts to explain the responsibility for content stored in the Cloud Computing.