6 resultados para proof-of-concept

em Repositório Institucional da Universidade de Aveiro - Portugal


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The continuous flow of technological developments in communications and electronic industries has led to the growing expansion of the Internet of Things (IoT). By leveraging the capabilities of smart networked devices and integrating them into existing industrial, leisure and communication applications, the IoT is expected to positively impact both economy and society, reducing the gap between the physical and digital worlds. Therefore, several efforts have been dedicated to the development of networking solutions addressing the diversity of challenges associated with such a vision. In this context, the integration of Information Centric Networking (ICN) concepts into the core of IoT is a research area gaining momentum and involving both research and industry actors. The massive amount of heterogeneous devices, as well as the data they produce, is a significant challenge for a wide-scale adoption of the IoT. In this paper we propose a service discovery mechanism, based on Named Data Networking (NDN), that leverages the use of a semantic matching mechanism for achieving a flexible discovery process. The development of appropriate service discovery mechanisms enriched with semantic capabilities for understanding and processing context information is a key feature for turning raw data into useful knowledge and ensuring the interoperability among different devices and applications. We assessed the performance of our solution through the implementation and deployment of a proof-of-concept prototype. Obtained results illustrate the potential of integrating semantic and ICN mechanisms to enable a flexible service discovery in IoT scenarios.

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During the last decades, we assisted to what is called “information explosion”. With the advent of the new technologies and new contexts, the volume, velocity and variety of data has increased exponentially, becoming what is known today as big data. Among them, we emphasize telecommunications operators, which gather, using network monitoring equipment, millions of network event records, the Call Detail Records (CDRs) and the Event Detail Records (EDRs), commonly known as xDRs. These records are stored and later processed to compute network performance and quality of service metrics. With the ever increasing number of collected xDRs, its generated volume needing to be stored has increased exponentially, making the current solutions based on relational databases not suited anymore. To tackle this problem, the relational data store can be replaced by Hadoop File System (HDFS). However, HDFS is simply a distributed file system, this way not supporting any aspect of the relational paradigm. To overcome this difficulty, this paper presents a framework that enables the current systems inserting data into relational databases, to keep doing it transparently when migrating to Hadoop. As proof of concept, the developed platform was integrated with the Altaia - a performance and QoS management of telecommunications networks and services.

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Database schemas, in many organizations, are considered one of the critical assets to be protected. From database schemas, it is not only possible to infer the information being collected but also the way organizations manage their businesses and/or activities. One of the ways to disclose database schemas is through the Create, Read, Update and Delete (CRUD) expressions. In fact, their use can follow strict security rules or be unregulated by malicious users. In the first case, users are required to master database schemas. This can be critical when applications that access the database directly, which we call database interface applications (DIA), are developed by third party organizations via outsourcing. In the second case, users can disclose partially or totally database schemas following malicious algorithms based on CRUD expressions. To overcome this vulnerability, we propose a new technique where CRUD expressions cannot be directly manipulated by DIAs any more. Whenever a DIA starts-up, the associated database server generates a random codified token for each CRUD expression and sends it to the DIA that the database servers can use to execute the correspondent CRUD expression. In order to validate our proposal, we present a conceptual architectural model and a proof of concept.

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Call Level Interfaces (CLI) play a key role in business tiers of relational and on some NoSQL database applications whenever a fine tune control between application tiers and the host databases is a key requirement. Unfortunately, in spite of this significant advantage, CLI are low level API, this way not addressing high level architectural requirements. Among the examples we emphasize two situations: a) the need to decouple or not to decouple the development process of business tiers from the development process of application tiers and b) the need to automatically adapt business tiers to new business and/or security needs at runtime. To tackle these CLI drawbacks, and simultaneously keep their advantages, this paper proposes an architecture relying on CLI from which multi-purpose business tiers components are built, herein referred to as Adaptable Business Tier Components (ABTC). Beyond the reference architecture, this paper presents a proof of concept based on Java and Java Database Connectivity (an example of CLI).

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Call Level Interfaces (CLI) are low level API that play a key role in database applications whenever a fine tune control between application tiers and the host databases is a key requirement. Unfortunately, in spite of this significant advantage, CLI were not designed to address organizational requirements and contextual runtime requirements. Among the examples we emphasize the need to decouple or not to decouple the development process of business tiers from the development process of application tiers and also the need to automatically adapt to new business and/or security needs at runtime. To tackle these CLI drawbacks, and simultaneously keep their advantages, this paper proposes an architecture relying on CLI from which multi-purpose business tiers components are built, herein referred to as Adaptable Business Tier Components (ABTC). This paper presents the reference architecture for those components and a proof of concept based on Java and Java Database Connectivity (an example of CLI).

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Given the need of a growing internationalization of business, to have a good command of English is, most of the times important for the development of technical (specific) competences. It is, thus, critical that professionals use accurate terminology to set grounds for a well-succeeded communication. Furthermore, business communication is increasingly moving to ICT-mediated sets and professionals have to be able to promptly adjust to these needs, resorting to trustworthy online information sources, but also using technologies that better serve their business purposes. In this scenario, the main objective of this study is to find evidence as to the utility of concept mapping as a teaching and learning strategy for the appropriation of business English terminology, enabling students to use English more efficiently as language of communication in business context. This study was based on a case study methodology, mainly of exploratory nature. Participants were students (n= 30) enrolled in the subject English Applied to Management II at Águeda School of Technology and Management – University of Aveiro (2013/14 edition). They were asked to create and peer review two concept maps (cmaps), one individually and another in pairs. The data gathered were treated and analysed resorting qualitative (content analysis) and to quantitative (descriptive statistical analysis) techniques. Results of the data analysis unveil that the use of a collaborative concept mapping tool promotes the development of linguistic competences as to the use of business terminology, but also of communication and collaboration competences. Besides, it was also a very important motivation element in the students’ engagement with the subject content.