Orientadores: Ricardo Ribeiro Gudwin, Cesar José Bonjuani Pagan / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação / Made available in DSpace on 2018-08-26T04:03:32Z (GMT). No. of bitstreams: 1 Angelo_TiagoNovaes_M.pdf: 3900207 bytes, checksum: 2eed8dd66c9bdc37e4d58e9eac614c9d (MD5) Previous issue date: 2014 / Resumo: O surgimento das Tecnologias de Comunicação e Informação trouxe uma nova perspectiva para o fortalecimento da democracia nas sociedades modernas. A democracia representativa, modelo predominante nas sociedades atuais, atravessa uma crise de credibilidade cuja principal consequência é o afastamento do cidadão na participação política, enfraquecendo os ideais democráticos. Neste contexto, a tecnologia surge como possibilidade para construção de um novo modelo de participação popular que resgate uma cidadania mais ativa, inaugurando o que denomina-se de democracia digital. O objetivo desta pesquisa foi desenvolver e implementar uma ferramenta, denominada "Extrator de Conhecimento Coletivo", com o propósito de conhecer o que um coletivo pensa a respeito de sua realidade a partir de pequenos relatos de seus participantes, dando voz à população num processo de democracia participativa. Os fundamentos teóricos baseiam-se em métodos de mineração de dados, sumarizadores extrativos e redes complexas. A ferramenta foi implementada e testada usando um banco de dados formado por opiniões de clientes a respeito de suas estadias em um Hotel. Os resultados apresentaram-se satisfatórios. Para trabalhos futuros, a proposta é que o Extrator de Conhecimento Coletivo seja o núcleo de processamento de dados de um espaço virtual onde a população pode se expressar e exercer ativamente sua cidadania / Abstract: The emergence of Information and Communication Technologies brought a new perspective to the strengthening of democracy in modern societies. The representative democracy, prevalent model in today's societies, crosses a crisis of credibility whose main consequence is the removal of citizen participation in politics, weakening democratic ideals. In this context, technology emerges as a possibility for construction of a new model of popular participation to rescue more active citizenship, inaugurating what is called digital democracy. The objective of this research was to develop and implement a tool called "Collective Knowledge Extractor", with the purpose of knowing what the collective thinks about his reality through small reports of its participants, giving voice to the people in a process participatory democracy. The theoretical foundations are based on methods of data mining, extractive summarizers and complex networks. The tool was implemented and tested using a database consisting of customer reviews about their stay in a Hotel. The results were satisfactory. For future work, the proposal is that the Extractor Collective Knowledge be the core data processing of a virtual space where people can express themselves and actively exercise their citizenship / Mestrado / Engenharia de Computação / Mestre em Engenharia Elétrica

The transformation of the legacy electric grid to Smart Grid (SG) poses numerous challenges in the design and development of an efficient SG communications network. While there has been an increasing interest in identifying the SG communications network and possible SG applications, specific research challenges at the network protocol have not been elaborated yet. This dissertation revisited each layer of a TCP/IP protocol stack which basically was designed for a wired network and optimized their performance in IEEE 802.11s-based Advanced Metering Infrastructure (AMI) communications network against the following challenges: security and privacy, AMI data explosion, periodic simultaneous data reporting scheduling, poor Transport Control Protocol (TCP) performance, Address Resolution Protocol (ARP) broadcast, and network interoperability. To address these challenges, layered and/or cross-layered protocol improvements were proposed for each layer of TCP/IP protocol stack. At the application layer, a tree-based periodic time schedule and a time division multiple access-based scheduling were proposed to reduce high contention when smart meters simultaneously send their reading. Homomorphic encryption performance was investigated to handle AMI data explosion while providing security and privacy. At the transport layer, a tree-based fixed Retransmission Timeout (RTO) setting and a path-error aware RTO that exploits rich information of IEEE 802.11s data-link layer path selection were proposed to address higher delay due to TCP mechanisms. At the network layer, ARP requests create broadcast storm problems in IEEE 802.11s due to the use of MAC addresses for routing. A secure piggybacking-based ARP was proposed to eliminate this issue. The tunneling mechanisms in the LTE network cause a downlink traffic problem to IEEE 802.11s. For the network interoperability, at the network layer of EPC network, a novel UE access list was proposed to address this issue. At the data-link layer, to handle QoS mismatch between IEEE 802.11s and LTE network, Dual Queues approach was proposed for the Enhanced Distributed Channel Access. The effectiveness of all proposed approaches was validated through extensive simulation experiments using a network simulator. The simulation results showed that the proposed approaches outperformed the traditional TCP/IP protocols in terms of end to end delay, packet delivery ratio, throughput, and collection time.

Web designers are expected to perform the difficult task of adapting a site’s design to fit changing usage trends. Web analytics tools give designers a window into website usage patterns, but they must be analyzed and applied to a website's user interface design manually. A framework for marrying live analytics data with user interface design could allow for interfaces that adapt dynamically to usage patterns, with little or no action from the designers. The goal of this research is to create a framework that utilizes web analytics data to automatically update and enhance web user interfaces. In this research, we present a solution for extracting analytics data via web services from Google Analytics and transforming them into reporting data that will inform user interface improvements. Once data are extracted and summarized, we expose the summarized reports via our own web services in a form that can be used by our client side User Interface (UI) framework. This client side framework will dynamically update the content and navigation on the page to reflect the data mined from the web usage reports. The resulting system will react to changing usage patterns of a website and update the user interface accordingly. We evaluated our framework by assigning navigation tasks to users on the UNF website and measuring the time it took them to complete those tasks, one group with our framework enabled, and one group using the original website. We found that the group that used the modified version of the site with our framework enabled was able to navigate the site more quickly and effectively.

Web 2.0 applications have become ubiquitous over the past few years because they provide useful features such as a rich, responsive graphical user interface that supports interactive and dynamic content. Social networking websites, blogs, auctions, online banking, online shopping and video sharing websites are noteworthy examples of Web 2.0 applications. The market for public cloud service providers is growing rapidly, and cloud providers offer an ever-growing list of services. As a result, developers and researchers find it challenging when deciding which public cloud service to use for deploying, experimenting or testing Web 2.0 applications. This study compares the scalability and performance of a social-events calendar application on two Infrastructure as a Service (IaaS) cloud services – Amazon EC2 and HP Cloud. This study captures and compares metrics on three different instance configurations for each cloud service such as the number of concurrent users (load), as well as response time and throughput (performance). Additionally, the total price of the three different instance configurations for each cloud service is calculated and compared. This comparison of the scalability, performance and price metrics provides developers and researchers with an insight into the scalability and performance characteristics of the three instance configurations for each cloud service, which simplifies the process of determining which cloud service and instance configuration to use for deploying their Web 2.0 applications. This study uses CloudStone – an open-source, three-tier web application benchmarking tool that simulates Web 2.0 application activities – as a realistic workload generator and to capture the intended metrics. The comparison of the collected metrics indicate that all of the tested Amazon EC2 instance configurations provide better scalability and lower latency at a lower cost than the respective HP Cloud instance configurations; however, the tested HP Cloud instance configurations provide a greater storage capacity than the Amazon EC2 instance configurations, which is an important consideration for data-intensive Web 2.0 applications.

High Performance Computing (HPC) applications are data-intensive scientific software requiring significant CPU and data storage capabilities. Researchers have examined the performance of Amazon Elastic Compute Cloud (EC2) environment across several HPC benchmarks; however, an extensive HPC benchmark study and a comparison between Amazon EC2 and Windows Azure (Microsoft’s cloud computing platform), with metrics such as memory bandwidth, Input/Output (I/O) performance, and communication computational performance, are largely absent. The purpose of this study is to perform an exhaustive HPC benchmark comparison on EC2 and Windows Azure platforms. We implement existing benchmarks to evaluate and analyze performance of two public clouds spanning both IaaS and PaaS types. We use Amazon EC2 and Windows Azure as platforms for hosting HPC benchmarks with variations such as instance types, number of nodes, hardware and software. This is accomplished by running benchmarks including STREAM, IOR and NPB benchmarks on these platforms on varied number of nodes for small and medium instance types. These benchmarks measure the memory bandwidth, I/O performance, communication and computational performance. Benchmarking cloud platforms provides useful objective measures of their worthiness for HPC applications in addition to assessing their consistency and predictability in supporting them.

The purpose of this project is to design an electronic commerce site for MarocMart company. MarocMart.com is an one-stop shopping company for a number of high quality products: carpets, jewelry, pottery, wood, leather, metals, and fashion items, etc... Each article is unique, hand-made by Moroccan craftsmen.

This project will simulate an online real estate company using JSP, Java Servlet and JavaBean technology.

Online Multimedia Communication System is a project aimed at providing people the ability to store and share their multimedia files. The users and administrator can modify and view the files and database information from a normal web browser. Furthermore, this site offers a secure environment to keep all the users' information private.

Unmanned aerial vehicles (UAVs) are emerging as enablers for supporting many applications and services, such as precision agriculture, search and rescue, temporary network deployment, coverage extension, and security. UAVs are being considered for integration into emerging wireless networks as aerial users, aerial relays (ARs), or aerial base stations (ABSs). This dissertation proposes employing UAVs to contribute to physical layer techniques that enhance the security performance of advanced wireless networks and services in terms of availability, resilience, and confidentiality. The focus is on securing terrestrial cellular communications against eavesdropping with a cellular-connected UAV that is dispatched as an AR or ABS. The research develops mathematical tools and applies machine learning algorithms to jointly optimize UAV trajectory and advanced communication parameters for improving the secrecy rate of wireless links, covering various communication scenarios: static and mobile users, single and multiple users, and single and multiple eavesdroppers with and without knowledge of the location of attackers and their channel state information. The analysis is based on established air-to-ground and air-to-air channel models for single and multiple antenna systems while taking into consideration the limited on-board energy resources of cellular-connected UAVs. Simulation results show fast algorithm convergence and significant improvements in terms of channel secrecy capacity that can be achieved when UAVs assist terrestrial cellular networks as proposed here over state-of-the-art solutions. In addition, numerical results demonstrate that the proposed methods scale well with the number of users to be served and with different eavesdropping distributions. The presented solutions are wireless protocol agnostic, can complement traditional security principles, and can be extended to address other communication security and performance needs.

Vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication enable the sharing, in real time, of vehicular locations and speeds with other vehicles, traffic signals, and traffic control centers. This shared information can help traffic to better traverse intersections, road segments, and congested neighborhoods, thereby reducing travel times, increasing driver safety, generating data for traffic planning, and reducing vehicular pollution. This study, which focuses on vehicular pollution, used an analysis of data from NREL, BTS, and the EPA to determine that the widespread use of V2V-based truck platooning—the convoying of trucks in close proximity to one another so as to reduce air drag across the convoy—could eliminate 37.9 million metric tons of CO2 emissions between 2022 and 2026.