Open Cloud Research Articles

RITI solución híbrida de PBX virtuales con aprovisionamiento automático en la nube

Although telephony over IP protocol has more than a decade among us, the ubiquity of the Internet, new open hardware technologies, free software and cloud platforms invite us to rethink a solution in this new context. As such a solution is proposed in this project to RITI, made up of a small team to be installed in customer premises and an automatic provisioning system and telephone switching in the cloud. The main challenge for obtaining such a product was the large number of hardware and software components to be integrated, passing points as diverse as a Raspberry with its Grandstream interface adapter, Asterisk with its trunk and protocol contexts, platforms such as AWS and Docker. It is important to highlight that the stated objectives were achieved, obtaining a functional, resilient and scalable solution where complexity is centralized in the components hosted in the cloud. In this way, the benefits of virtualization and consolidation in the cloud have been extended to telephony in recent years. Finally, all the software components of the system are either free open source projects, or original developments by the authors of the same.

Iq Semantic: Semantic Web Intelligent Querying Framework

Abstract The continuous expansion of the semantic web and of the linked open data cloud meant more semantic data are available for querying from endpoints all over the web. We propose extending a standard SPARQL interface with UI and Natural Language Processing features to allow easier and more intelligent querying. The paper describes some usage scenarios for easy querying and launches a discussion on the advantages of such an implementation.

A Development of Medical Records Management System to Health Care Decision Makers using Cloud Technologies

Electronic Health Record systems continue to be incorporated into health care facilities to reduce the problems and limits of paper-based methodology but their deployment has been slow due to high investment and storage costs. The Enterprise Electronic Cloud-based Health Record System is planned, created and checked for recording, recovering, chronicling and surveying patients and other clinical records. Cloud Data fills in as a coordinates information bank over every single authoritative emergency clinic, middleware gives a typical stage to all electronic health record frameworks between remote medical clinics while a security approval server gives access to approves clients and denies unapproved clients access to records or assets in the system. In this model, complex mixes are redistributed to open cloud servers, leaving nearly the whole intricate of private key generator, sender and beneficiary. In addition, PKG communication costs with users have been optimized. In addition, we are building a comprehensive library called libabe compatible with mobile devices, and the access control mechanism is distributed in a logical environment, including public cloud servers, a laptop and an inexpensive mobile device with interactive resources.

Open cells exhibit weaker entrainment of free-tropospheric biomass burning aerosol into the south-east Atlantic boundary layer

Abstract. This work presents synergistic satellite, airborne and surface-based observations of a pocket of open cells (POC) in the remote south-east Atlantic. The observations were obtained over and upwind of Ascension Island during the CLouds and Aerosol Radiative Impacts and Forcing (CLARIFY) and the Layered Smoke Interacting with Clouds (LASIC) field experiments. A novel aspect of this case study is that an extensive free-tropospheric biomass burning aerosol plume that had been transported from the African continent was observed to be in contact with the boundary layer inversion over the POC and the surrounding closed cellular cloud regime. The in situ measurements show marked contrasts in the boundary layer thermodynamic structure, cloud properties, precipitation and aerosol conditions between the open cells and surrounding overcast cloud field. The data demonstrate that the overlying biomass burning aerosol was mixing down into the boundary layer in the stratocumulus cloud downwind of the POC, with elevated carbon monoxide, black carbon mass loadings and accumulation-mode aerosol concentrations measured beneath the trade-wind inversion. The stratocumulus cloud in this region was moderately polluted and exhibited very little precipitation falling below cloud base. A rapid transition to actively precipitating cumulus clouds and detrained stratiform remnants in the form of thin quiescent veil clouds was observed across the boundary into and deep within the POC. The subcloud layer in the POC was much cleaner than that in the stratocumulus region. The clouds in the POC formed within an ultra-clean layer (accumulation-mode aerosol concentrations of approximately a few cm−3) in the upper region of the boundary layer, which was likely to have been formed via efficient collision–coalescence and sedimentation processes. Enhanced Aitken-mode aerosol concentrations were also observed intermittently in this ultra-clean layer, suggesting that new particle formation was taking place. Across the boundary layer inversion and immediately above the ultra-clean layer, accumulation-mode aerosol concentrations were ∼ 1000 cm−3. Importantly, the air mass in the POC showed no evidence of elevated carbon monoxide over and above typical background conditions at this location and time of year. As carbon monoxide is a good tracer for biomass burning aerosol that is not readily removed by cloud processing and precipitation, it demonstrates that the open cellular convection in the POC is not able to entrain large quantities of the free-tropospheric aerosol that was sitting directly on top of the boundary layer inversion. This suggests that the structure of the mesoscale cellular convection may play an important role in regulating the transport of aerosol from the free troposphere down into the marine boundary layer. We then develop a climatology of open cellular cloud conditions in the south-east Atlantic from 19 years of September Moderate Resolution Imaging Spectroradiometer (MODIS) Terra imagery. This shows that the maxima in open cell frequency (> 0.25) occurs far offshore and in a region where subsiding biomass burning aerosol plumes may often come into contact with the underlying boundary layer cloud. If the results from the observational case study applied more broadly, then the apparent low susceptibility of open cells to free-tropospheric intrusions of additional cloud condensation nuclei could have some important consequences for aerosol–cloud interactions in the region.

The H2020 OCRE Project Opens the Gates of the Commercial Cloud and EO Services Usage to the Research Community

Cloud and Earth Observation (EO) based services offer the European Research community a wealth of powerful tools. However, for many researchers these tools are currently out of reach. It is difficult to find and select suitable services. Establishing agreements with cloud and EO service providers and ensuring legal and technical compliance requires specialist skills and takes an inordinate amount of time. Equally, service providers find it difficult to reach and meet the needs of the research community in technical, financial and legal areas. The Open Clouds for Research Environments consortium (OCRE) will change this, by putting in place an easy adoption route. In the autumn of 2019, OCRE will run a pan-European tender and establish framework agreements with service providers who meet the requirements of the research community. 10.000 European research and education institutes will be able to directly consume these offerings via the European Open Science Cloud service catalogue, through ready-to-use agreements. They will not have to run a tender of their own. In addition, to stimulate usage, OCRE will make available 9.5 million euro in service credits (vouchers), through adoption funds from the European Commission. OCRE is a pioneer project without precedence, with potentially high impact in the future EO market activities and evolution of service offering, with the objective to burst the usage of EO commercial services by the research environment.

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.

Digital Transformation of the Process of Creation of Aviation Techniques based on the Mind Sphere Platform

The article is dedicated to the analysis of the digital transformation processes of the procedure of making aviation technics based on the usage of high technological platform MindSphere. The architecture and tools of the Siemens IIoT MindSphere open cloud operating system are reviewed. There are the capabilities of the MindSphere platform for the digital transformation of industrial enterprises. In theoretical part of this article, the authors consider perspective technologies of digitalization at domestic aviation enterprises, where the main factors are work in the sphere of introducing artificial intelligence and creating unique digital twins of aircrafts. The research is based on the comprehensive analysis and synthesis with the following forming of the final grade of the main results of realization of technological domestic enterprises’ transformation. In the course of the study, the task is to identify key areas and areas of technological transformation and the possibility of using promising information technologies (IT) systems. The article’s authors point out that for solution of tasks of predictive analytics, multivariate analysis, trend prediction, and pattern analysis based on artificial intelligence / machine learning methods aviation enterprises have to use technological abilities of the platform MindSphere. It is defined that the development a full-fledged virtual object model based on technologies included in the platform Mindsphere will allow solving a lot of problems during its development and also there comes up an opportunity to qualitatively analyze the various options for the developed product and optimize the time / expenses connected to its last development. During the conducted analysis, it was found out that technologies Siemens PLM (Product lifecycle) Software on the platform MindSphere allow making verified models aircraft, their units, components and systems, as well as conduct their virtual tests. For typical aviation systems and components of the solution suggest available libraries of customized models, due to which reliable calculations and rejection of part of field tests are possible. In the result of the conducted research authors come to the conclusion that with the help of the platform MindSphere enterprises, holdings, and even whole industries it will be able to close digital chains between the design, manufacture, and product operation.

Study on utilization access control mechanism of resources in geological cloud environment

In order to solve the problem in access control of open geological cloud resources, from the view of usage an access control model was proposed based on trust and role. Firstly, geological cloud resources were divided into five categories according to the actual usage of geological cloud resource, and the access control needs of various resources were analyzed in detail. Secondly, a layered access control model of geological cloud resource was designed, in which the access control process was defined and the evaluation method of user trust based on set pair analysis was given. Finally, the results and safety analysis showed the rationality and validity of proposed model.

Cloud connection oriented real‐time monitoring system for atmospheric particles

To meet the requirements of data acquisition from mobile pollution sources and unfixed data acquisition points in atmospheric particle monitoring system, this study designs a real-time monitoring system for atmospheric particles such as PM2.5 based on a single-chip microcomputer, an ET-iLink open cloud platform and an Android operating system. The movable data acquisition nodes for atmospheric particles are designed. The laser scattering method is used to obtain the data of atmospheric particle concentration, which are uploaded to the cloud platform through the GPRS network. The Android application obtains the real time data of atmospheric particle concentration from the cloud platform. Thus the real-time remote monitoring for atmospheric particles is realised. The test results show that the system has the following advantages: stable performance, high scalability and low error rate.

RETRACTED ARTICLE: Defense model for preserving the wind turbine Records in Cloud Using fog Computing with coupling based cryptography

Security of information put away and handled on the open cloud is a noteworthy concern. In this paper we contend that hybrid cloud gives a perfect situation to applications that require the participation of different associations, every association needs to facilitate a few parts of its movement and offer a few information with a few different associations yet has severe security prerequisites for its very own private information. Such applications could profit by a hybrid cloud condition. In a perfect world, “big data” ought to be scrambled and put away on the open cloud. In this the data from the windmill, wind pump or wind charger are to be stored in cloud, that data must be secured in the cloud by means of a fog computing capability. Towards termination, a third party one round verified key understanding convention had been projected in view of the bilinear blending cryptography that may produce a session key among the members and impart among them safely. At last, the secluded wind turbine information’s were gotten to, put away safely via executing a lure procedure. In this computational cost is low and key size is reduced when compared to all other existing systems. The proposed system reduces the computational cost at 97% compared with the other existing systems.

4239 Published By: Blue Eyes Intelligence Engineering & Sciences Publication Retrieval Number: E6720018520/2020©BEIESP DOI:10.35940/ijrte.E6720.018520 Journal Website: www.ijrte.org Data Obfuscation Technique for Security in Cloud Computing

Cloud computing is at present a day's changes into the most crushed in marvels to use for enormous scale alliance or for person who need unmistakable structure organizations with least expense. Usually person's data is dealt with on open Cloud which is accessible to everybody for get to. These focal raises some issue in reverse to adaptable organizations gave by cloud suppliers, similar to Confidentiality, Integrity, Availability, Authorization and some more. Starting late, Lots of decisions are open to guarantee the data and most perfect ways is to use encryption. Encryption can't give enough confirmation while contemplating heaps of customers' fragile data. It in like manner eats up greater chance to perform encryption and translating process for every single inquiry. Moreover it is definitely not an OK practice to contemplate customer driven considering the way that once customer data is moved on Cloud premises, customer doesn't have direct control over this data. To empty load of Cloud server likewise to give acceptable security to customer's data, we propose a methodology by joining the two procedures viz. Jumbling and Encryption in this assessment paper. Customer data may be scrambled if protection is needed for its records or reports and the SaaS Cloud organization is reviewed using obscurity techniques. Using this two-way approach, we may assume that the proposed agreement provides sufficient protections for darkened access and safety of even open data on cloud servers. Our point is additionally to give appropriate assessment on data disordering for security in cloud computing.

Private and Secure Distributed Matrix Multiplication With Flexible Communication Load

Large matrix multiplications are central to large-scale machine learning applications. These operations are often carried out on a distributed computing platform with a master server and multiple workers in the cloud operating in parallel. For such distributed platforms, it has been recently shown that coding over the input data matrices can reduce the computational delay, yielding a trade-off between recovery threshold, i.e., the number of workers required to recover the matrix product, and communication load, i.e., the total amount of data to be downloaded from the workers. In this paper, in addition to exact recovery requirements, we impose security and privacy constraints on the data matrices, and study the recovery threshold as a function of the communication load. We first assume that both matrices contain private information and that workers can collude to eavesdrop on the content of these data matrices. For this problem, we introduce a novel class of secure codes, referred to as secure generalized PolyDot (SGPD) codes, that generalize state-of-the-art non-secure codes for matrix multiplication. SGPD codes allow a flexible trade-off between recovery threshold and communication load for a fixed maximum number of colluding workers while providing perfect secrecy for the two data matrices. We then study a connection between secure matrix multiplication and private information retrieval. We specifically assume that one of the data matrices is taken from a public set known to all the workers. In this setup, the identity of the matrix of interest should be kept private from the workers. For this model, we present a variant of generalized PolyDot codes that can guarantee both secrecy of one matrix and privacy for the identity of the other matrix for the case of no colluding servers.

Real-time monitoring of physical education classroom in colleges and universities based on open IoT and cloud computing

The teaching effect of college physical education classroom needs to be combined with artificial intelligence system. From the actual situation, the current college physical education classroom is mostly based on manual teaching and manual management, so the teaching effect is not good. In order to change the traditional teaching mode and improve the classroom detection effect, based on the open Internet of Things and cloud computing technology, this paper builds a real-time monitoring system of college physical education classroom, and proposes a number of new and improved algorithms, which provide a theoretical and technical basis for the application of automatic identity positioning in large scenes. Moreover, this study obtains field scenes through field image data collection and field data processing, and then combines the regional scenes with field measured data to verify accuracy and trends to obtain students’ morphological characteristics. In addition, this paper designs practical experiments to verify the system performance. The research results show that the intelligent system constructed in this paper has certain effects and can be applied to physical education.

A mutualistic framework for sustainable capacity sharing in manufacturing

In order to decrease the ecological impact and footprint of supply chain actors, a promising mechanism for sustainability in the industry is represented by sharing resources with each other in a mutualistic way. The paper aims at introducing a novel framework that facilitates the collaborative work of manufacturing facilities and helps participants dynamically and safely negotiate available capacities shared within the federation. The center of the framework is an open API cloud- and simulation-based platform which supports the strategic collaboration of federated companies while helping them optimize resource utilization, avoid shortages and minimize the environmental impact of their logistics.

Distributed Denial of Service (DDoS) Attacks Detection System for OpenStack-based Private Cloud

Cloud computing technique is commonly used by fast growing Internet-based applications. Moving to cloud computing results in reducing the cost of managing and maintaining IT infrastructure. Different organizations controls the cloud resources over internet using networking protocols and standards. This makes IT infrastructure distributed in nature but controlled centrally, which opens the door to the attackers for intrusions. Attacks as Distributed Denial of Service (DDoS) is one of the most popular intrusions in private cloud which cause a degradation of services being reduced or denial of services. In this work the sole focus is on DDoS attack which specifically targeted towards detection of bandwidth flooding and connection flooding. Such attacks target the network layer of the cloud set up with invalid requests and make it denial to legitimate requests. Thus, the entire cloud set up becomes vulnerable and can be disrupted by these DDoS attacks. To overcome this a cloud operating system which has an integrated firewall with DDoS detection system is required. Here a system with OpenStack integrated firewall and raw socket programming for monitoring the network traffic is proposed. Based on the dataset generated in controlled DDoS attack environment, algorithms such as Decision tree, K nearest neighbor (KNN), Naive Bayes and Deep Neural Network (DNN) algorithms are compared against the trained model. Eventually, DDoS attacks are detected, and administrator of the private cloud is notified.

Performance Optimization Through Data Pipeline in Heterogenious Hadoop Cluster

Big data has received a momentum from both The scholarly group and organisation. The MapReduce version has risen into a noteworthy figuring mannequin on the aspect of large information research. Hadoop, that is an open supply utilization of the MapReduce mannequin, has been generally taken up by the network. Cloud expert businesses, for example, Amazon EC2 cloud have now upheld Hadoop client applications. no matter the whole lot, a key take a seem at is that the cloud educated co-ops do not a have asset provisioning tool to satisfy client occupations with due date prerequisites. As of now, it's miles completely the consumer duty to assess the require degree of property for his or her pastime running in an open cloud. This postulation correct-knownshows a Hadoop execution mannequin that exactly gauges the execution duration of exertions and in a similar manner arrangements the desired degree of property for a vocation to be finished indoors a due date. The proposed mannequin utilizes in the neighborhood Weighted Linear Regression (LWLR) mannequin to assess execution time of a vocation and Lagrange Multiplier device for asset provisioning to fulfill client art work with a given due date.

ПРОЄКТУВАННЯ І ВИКОРИСТАННЯ ВІДКРИТОГО ХМАРО ОРІЄНТОВАНОГО ОСВІТНЬО-НАУКОВОГО СЕРЕДОВИЩА ЗАКЛАДУ ВИЩОЇ ОСВІТИ

У статті висвітлено результати теоретичних і експериментальних досліджень проблем проєктування, впровадження і використання відкритого хмаро орієнтованого освітньо-наукового середовища закладу вищої освіти, що проводилися в Інституті інформаційних технологій і засобів навчання НАПН України протягом 2011-2019 рр. Висвітлено науково-методичні засади дослідження, поняттєво-термінологічний апарат, окреслено методологічні принципи проєктування середовища, обґрунтовано загальну модель та методичну систему його формування і розвитку. У моделі відображено особливості процесу формування і розвитку середовища, що спрямований на досягнення цілей педагогічної системи, серед яких – формування ІКТ-компетентного фахівця; розширення доступу до ІКТ; використання в освіті і наукових дослідженнях найсучасніших засобів і технологій. Методична система охоплює ряд методик, що об’єднані системо утворюючим чинником, яким є хмаро орієнтований підхід, що спирається на відповідні базові характеристики і сервісні моделі. До складу методичної системи входять: методика використання науково-навчальної хмари наукової/освітньої установи, що спрямована на поліпшення організації і підвищення ефективності наукових досліджень, упровадження їх результатів; методики використання хмаро орієнтованих компонентів навчального призначення на базі гібридної хмари AWS а також спеціалізованих предметно орієнтованих сервісів. Охарактеризовано шляхи добору методик на базі запропонованої моделі в педагогічних системах закладу вищої освіти, визначено перспективи їх використання. Здійснено аналіз і оцінку досвіду впровадження і використання окремих сервісів і компонентів хмаро орієнтованого освітньо-наукового середовища у закладах вищої освіти України. Наведено результати експериментальних досліджень використання сервісів хмаро орієнтованого середовища в процесі навчання наукових, науково-педагогічних, педагогічних кадрів. Проведено аналіз і оцінку перспектив розвитку хмаро орієнтованого освітньо-наукового середовища на підставі запропонованих підходів.

Social sciences, humanities and their interoperability with the European Open Science Cloud: What is SSHOC?

The EC H2020 cluster project SSHOC aims to provide a full-fledged Social Sciences and Humanities Open Cloud where data, tools, and training are available and accessible for users of SSH data. The focus of the project is determined by the goal to further the innovation of infrastructural support for digital scholarship, to stimulate multidisciplinary collaboration across the various subfields of SSH and beyond, and to increase the potential for societal impact. The intention is to create a European open cloud ecosystem for social sciences and humanities, consisting of an infrastructural and human component. SSHOC will encourage secure environments for sharing and using sensitive and confidential data. It will contribute to the Open Science agenda and realization of the European Open Science Cloud (EOSC), as well as contribute to innovations stemming from the coupling of heterogeneous data types and work on the Interoperability principle of FAIR.

Aes Cryptograph For Secure Cloud Storage

In cloud computing disseminated assets are shared by means of system in open condition. Subsequently client can without much of a stretch access their information from anyplace. Simultaneously exist protection and security problems because of numerous causes. Initial one is emotional improvement in system advances. Another is expanded interest for computing assets, which make numerous associations to re-appropriate their information stockpiling. So there is a requirement for secure cloud stockpiling administration in open cloud condition where the supplier isn't a confided in one. Our research tends to various information security and protection assurance problems in a cloud computing condition and suggests a technique for giving diverse security administrations like validation, approval and classification alongside checking in postponement. 128 piece Advanced Cryptograph Standard (AES) is utilized to increment information security and classification. In this supported methodology information is encoded utilizing AES and afterward transferred on a cloud. The supported model uses Short Message Service (SMS) ready instrument with keeping away from unapproved access to client information.

Cloud-computing and precision medicine: Big data offers big opportunities

Abstract Research on large shared medical datasets and data-driven research are gaining fast momentum and provide major opportunities for improving health systems as well as individual care. Such Open Data can shed light on the causes of disease and effects of treatment including adverse reactions side-effects of treatments, while also facilitating analyses tailored to an individual’s characteristics, known as personalized or precision medicine. Precision medicine treatments will take personalization to the next level and be effective for individual patients based on their genomic, environmental, and lifestyle factors. High-throughput sequencing technologies and open databases have made precision medicine possible but up to now only large research centres could handle the large scale technology needed for its processing. Aside from issues such as user trust, data privacy, transparency over the control of data ownership, and the implications of data analytics for personal privacy with potentially intrusive inferences, recent advances by Berkeley using open source Big Data technologies and Cloud Computing Services has allowed precision medicine studies to be conducted by small and agile research labs and researchers around the world.