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Domain big data privacy

The replacement is done in two separate phases, offline and online, to make the recovery faster. The offline phase foresees all possible subdigraphs, pre-calculates them, and ranks several possible replacements.

The online phase compensates the unwanted effects and executes the replacement subdigraph in lieu of the original subdigraph. We have evaluated our approach during an experiment and have found that we could recover more than half of the simulated failures.

These achievements show a significant improvement compared to current approaches. Comparing PaaS offerings in light of SaaS development. Stefan Walraven. Software vendors increasingly aim to apply the Software-as-a-Service SaaS delivery model instead of the traditional on-premise model. Platforms-as-a-Service PaaSsuch as Google App Engine and Windows Azure, deliver a computing platform and solution stack as a service, but they also aim to facilitate the development of cloud applications SaaS.

Such PaaS offerings should enable third parties to build and deliver multi-tenant SaaS applications while shielding the complexity of the underpinning middleware and infrastructure. This paper compares, on the basis of a practical case study, three different and representative PaaS platforms with respect to their support for SaaS application development.

We have reengineered an on-premise enterprise application into a SaaS application and we have subsequently deployed it in three PaaS-based cloud environments. We have investigated the following qualities of the PaaS platforms from the perspective of SaaS development: Developing a decision support system for business model design. Sep Electron Market.

Dave Daas. Software vendors increasingly offer web-based services SaaS at a subscription fee. Because they need a network of service partners to generate customer value, SaaS providers have to focus on business model BM design. In this study, a decision support system DSS is developed to help SaaS in this process, based on a design approach consisting of a design process that is guided by various design methods. The outcome of the design process is a computer-based tool that takes important BM evaluation criteria, such as critical design issues and success factors, into account, by integrating market analysis based on conjoint analysis, providing alternative designs for business models involving companies working together in a value network offering e-services, and including a multi-criteria decision analysis, based on AHP, that can be used to select the business model of the core services and identify the implications for the business model of all the actors involved in the network.

(PDF) Технология Больших данных (Big Data). Основные характеристики и перспективы применения

The DSS is discussed in an illustrative case. The execution of the design process provides insight into how BM design processes can be improved and formalized. The BM decision-making tool illustrates the importance of modularity, i. Sep Huayou Si. But great improvement of capability in SWS-based service discovery is still desired. To address this issue, we present a distributed and semantic-matching-based approach for SWS publication and discovery by leveraging structured P2P technology.

In this paper, first, we present our service matching rule which focuses on the inputs and outputs of SWS. Then, to realize this rule in open distributed environment and achieve the optimal match between a query and its qualified services, we propose not only a concept of ordered-concept-tree OCT to semantically sort the relevant concepts for service matching, but also a method to publish ontologies on structured P2P network to freely share and make full use of the concepts defined in different ontologies for OCT construction.

Finally, we present a method for SWS publication on P2P network and an algorithm for service discovery. We also conduct experiments to evaluate our approach and the experimental results demonstrate its scalability, effectiveness, and callback capability to discover semantic web services.

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Efficient resource allocation for optimizing objectives of cloud users, IaaS provider and SaaS provider in cloud environment. The paper studies efficient resource allocation to optimize objectives of cloud users, IaaS provider and SaaS provider in cloud computing. The paper proposes the composition of different layers in the cloud, such as IaaS and SaaS, and its joint optimization for efficient resource allocation. The efficient resource allocation optimization problem is conducted by subproblems.

The proposed cloud resource allocation optimization algorithm is achieved through an iterative algorithm. The experiments are conducted to compare the performance of proposed joint optimization algorithm for efficient resource allocation with other related works.

Optimal resource provisioning for cloud computing environment. The paper presents an efficient cloud resource provisioning approach.

Основы Big Data. Концепции, алгоритмы и технологии by Томас Эрл

The Software as a Service SaaS provider leases resources from cloud providers and also leases software as services to SaaS users. The cloud provider is to maximize the profit without exceeding the upper bound of energy consumption of cloud provider for provisioning virtual machines VMs to the SaaS provider.

The SaaS users purpose to obtain the optimized QoS to accomplish their jobs with a limited budget and deadline. The proposed optimal cloud resource provisioning algorithm includes two sub-algorithms at different levels: Simulations are conducted to compare the performance of proposed cloud resource provisioning algorithm with related work.

Critical Questions for Big Data. Jun Inform Comm Soc. The era of Big Data has begun. Computer scientists, physicists, economists, mathematicians, political scientists, bio-informaticists, sociologists, and other scholars are clamoring for access to the massive quantities of information produced by and about people, things, and their interactions.

Diverse groups argue about the potential benefits and costs of analyzing genetic sequences, social media interactions, health records, phone logs, government records, and other digital traces left by people. Significant questions emerge. Will large-scale search data help us create better tools, services, and public goods? Or will it usher in a new wave of privacy incursions and invasive marketing? Will data analytics help us understand online communities and political movements?

Or will it be used to track protesters and suppress speech? Given the rise of Big Data as a socio-technical phenomenon, we argue that it is necessary to critically interrogate its assumptions and biases. In this article, we offer six provocations to spark conversations about the issues of Big Data: Healthcare systems are very complex due to extreme heterogeneity in their data and processes.

Researchers and practitioner need to make systems interoperable and integrate for the benefit of all the stakeholders including hospitals, clinicians, medical support staff, and patients. The broader goal of interoperability can only be achieved when standards are practiced. Two different healthcare systems can earn HL7 conformance and compliance but at the same time can be incompatible for interoperability because of varying implementation of HL7 interaction model.

This is mainly because workflows in healthcare systems are very complex. Interoperability on one hand requires flexible mechanism for the mapping of business processes to a standard, HL7 in our example. On the other hand it requires deeper understanding of the standard interaction model and gaps created by their incompatible implementations. In this paper we propose a novel technique of dynamically creating semantic web services as overlay on top of the existing services.

We used Web Service Modeling Framework as an underlying architecture for HL7 process artifacts implementation as semantic web services.

These semantic services are mapped to our proposed interaction ontology. Integrated reasoning mechanism provides necessary execution semantics for more effective and seamless end-to-end communication. The prototype we tested on different processes from the laboratory domain at a local diagnostic laboratory with uninterrupted process flow.

The scenario of Result Query Placer interaction flow and its associated process artifacts are executed for the proof of concept. The proposed solution complements the existing data interoperability in HL7 and leads to semantic process interoperability. The achievement of semantic interoperability results in timely delivery of healthcare services to patients saving precious lives. A semantic reputation system in P2P-based Semantic Web. Jan A reputation mechanism is introsuced in P2P-based Semantic Web to utilize reputation information based on semantic similarity of peers in the network.

This approach is evaluated in a simulation of a content sharing system and the experiments show that the system with reputation mechanism outperforms the system without it. Kunal Verma. Web services are the new paradigm for distributed computing. They have much to offer towards interoperability of applications and integration of large scale distributed systems.

To make Web services accessible to users, service providers use Web service registries to publish them. Current infrastructure of registries requires replication of all Web service publications in all Universal Business Registries. Large growth in number of Web services as well as the growth in the number of registries would make this replication impractical. In addition, the current Web service discovery mechanism is inefficient, as it does not support discovery based on the capabilities of the services, leading to a lot of irrelevant matches.

Semantic discovery or matching of services is a promising approach to address this challenge. In this paper, we present a scalable, high performance environment for Web service publication and discovery among multiple registries. This work uses an ontology-based approach to organize registries into domains, enabling domain based classification of all Web services. Each of these registries supports semantic publication and discovery of Web services. We believe that the semantic approach suggested in this paper will significantly improve Web service publication and discovery involving a large number of registries.

Exploring injection prevention technologies for security-aware distributed collaborative manufacturing on the Semantic Web. Security is one of the key challenges for the development of distributed collaborative manufacturing systems. This paper firstly presents the possible injection attacks in RDBMS-based collaborative system on the Semantic Web and gives their classification.

Based on this classification, the paper then describes an attempt at detecting command injections to the distributed collaborative manufacturing systems by comparing the inputs related nodes that are intended with the resulting parse tree in run time. By testing on two commonly used RDF databases and one real Semantic Web application, it shows that SemGuard is efficient, taking less than 10ms overhead to protect the context information of a distributed collaborative manufacturing system.

Summarizing Vocabularies in the Global Semantic Web. In the Semantic Web, vocabularies are defined and shared among knowledge workers to describe linked data for scientific, industrial or daily life usage.

With the rapid growth of online vocabularies, there is an emergent need for approaches helping users understand vocabularies quickly. In this paper, we study the summarization of vocabularies to help users understand vocabularies.

Vocabulary summarization is based on the structural analysis and pragmatics statistics in the global Semantic Web. Local Bipartite Model and Expanded Bipartite Model of a vocabulary are proposed to characterize the structure in a vocabulary and links between vocabularies. A structural importance for each RDF sentence in the vocabulary is assessed using link analysis. Meanwhile, pragmatics importance of each RDF sentence is assessed using the statistics of instantiation of its terms in the Semantic Web.

Summaries are produced by extracting important RDF sentences in vocabularies under a re-ranking strategy. Preliminary experiments show that it is feasible to help users understand a vocabulary through its summary. Web service description and discovery based on semantic model. A novel semantic model of Web service description and discovery was proposed through an extension for profile model of Web ontology language for services OWL-S in this paper.

Similarity matching of Web services was implemented through computing weighted summation of semantic similarity value based on specific domain ontology and dynamical satisfy extent evaluation for quality of service QoS.

Experiments show that the provided semantic matching model is efficient. Application Development over Software-as-a-Service Platforms. Conference Paper. Javier Espadas. New web development and deployment platforms are arising; some examples of these are Apex of Salesforce. These software delivery platforms SDP are meant to serve as the basis for the delivery of an important percentage of the software offer.

In the other hand, application development over these new platforms is not a defined process. Building applications over an SDP change the way software is designed, developed and delivered. Common methods of software development should be analyzed and redefined in order to fulfill the requirements of these new ways of constructing and delivering software. This paper presents the analysis of the impact of these requirements and proposes guidelines to be applied for application development in software-as-a-service SaaS environments.

The purpose of semantic web services discovery is to use semantic knowledge to find services that can be composed to form an admissible answer to a query. In this paper we consider the advantage of adopting a knowledge-based approach to web services discovery.

Services are described by means of terminological axioms and constrained clauses. We apply a specific resolution and a constraint propagation mechanism to evaluate queries over services. A semantic-augmented multi-level matching model of Web services. Semantic Web services, augmenting Web service descriptions using semantic Web technology, were introduced to facilitate the publication, discovery, and execution of Web services at the semantic level.

Semantic matchmakers enhance the capability of UDDI service registries in the semantic Web services architecture by applying some matching algorithms between advertisements and requests described in OWL-S to recognize various degrees of matching for Web services.

This paper proposes a novel semantics-enhanced Web service framework and a multi-level matching model for Web services. The matching process is achieved at five levels: A case study on collaborative design is used to demonstrate the proposed approach.

However, while some market research and IT provider firms fervently support this point of view, others already conjure up the failure of this on-demand sourcing option. Oftentimes based on weak empirical data and shaky reasoning, these inconsistent perspectives lack scientific rigor and neglect to present a more differentiated picture of SaaS-adoption.

This study seeks to deepen the understanding of factors driving the adoption of Software-as-a-Service SaaS. Grounded in transaction cost theory, the resource-based view, and the theory of planned behavior, we develop a research model to assess SaaS-adoption at the application level. Survey data of firms in Germany with valid response items across different industries were collected to test the theoretical model.

Our analysis revealed that patterns on the decision on SaaS-adoption differ across application types.

Технологии и инфраструктура Big Data

Social influence, attitude toward SaaS-adoption, adoption uncertainty, and strategic value turned out to be the strongest and most consistent drivers across all application types. Furthermore, we found that firm size does not matter in SaaS-adoption, since large enterprises and small- and medium-sized companies had similar adoption rates.

Overall, this study provides relevant findings that IT vendors can use to better appeal to potential companies that consider adopting SaaS.

[963] Big Data, Big Business

Product Differentiation for Software-as-a-Service Providers. Arne Katzmarzik. Ильин, Е. Колкер, А. Лисица, Большие. Coakley, G. Crocetti, P. Dressner, W. Kellum Transforming. Jee, G.

Informatics Research, vol. Promise and. Tene, J. Po lonetsky, Privacy in the age of big data: A time for big. Paper No. He rland, T M. Khoshgoftaar, R. Alyass, M. Turcotte, D. Meyre, From big data analysis t o. Medical Genomics, vol. Retrieved Технологии Data Mining в Медицине. Аннотация — В статье описаны цели, задачи и этапы. Исследована роль технологии data mining в анализе.

Ключевые слова — Knowledge Discovery in Da tabasedata. Современные больницы хорошо оснащены. Обширное количество. Чтобы удовлетворить. KDD впервые был введен в середине - х годов с целью. KDD представляет собой автоматическ ийпоисков ый. Процесс KDD обычно состоит из с ледующих этапов [ 3.

Этот шаг готовит почву для понимания того. Люд ям. Этот процесс включает в себя выбор способов поиска. Этап предназначен для повышения надежности данных. Он в ключает в себя очистку данных, таких как о бработка. Исследователи находятся под влиянием принц ипа. М етоды прео бразования данн ых. Этот шаг часто имеет решающее значение для успеха. Н апример, в медицинск. Предложены четыре подхода для уменьшения. Пер вый подход заключается. Второй подход является с убъективным.

Третий подход использует алгоритмы. Последний — четвертый подход использует. Этот подход. Принимается решение, какую задачу data mining. Это во многом зависит от ц елей KDD. Data mining предназначена. Download full-text. Citations 0. References Controlling Data Volume, Velocity, and Variety. Jan Doug Laney.

Privacy in the Age of Big Data: A Time for Big Decisions. Our highly qualified support team is able to assist you with any help you might need.

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