Performance scalability analysis of JavaScript applications with web workers

Web applications are getting closer to the performance of native applications taking advantage of new standard–based technologies. The recent HTML5 standard includes, among others, the Web Workers API that allows executing JavaScript applications on multiple threads, or workers. However, the internals of the browser’s JavaScript virtual machine does not expose direct relation between workers and running threads in the browser and the utilization of logical cores in the processor. As a result, developers do not know how performance actually scales on different environments and therefore what is the optimal number of workers on parallel JavaScript codes. This paper presents the first performance scalability analysis of parallel web apps with multiple workers. We focus on two case studies representative of different worker execution models. Our analyses show performance scaling on different parallel processor microarchitectures and on three major web browsers in the market. Besides, we study the impact of co–running applications on the web app performance. The results provide insights for future approaches to automatically find out the optimal number of workers that provide the best tradeoff between performance and resource usage to preserve system responsiveness and user experience, especially on environments with unexpected changes on system workload.Peer ReviewedPostprint (author's final draft

Distributed D3: A web-based distributed data visualisation framework for Big Data

The influx of Big Data has created an ever-growing need for analytic tools targeting towards the acquisition of insights and knowledge from large datasets. Visual perception as a fundamental tool used by humans to retrieve information from the outside world around us has its unique ability to distinguish patterns pre-attentively. Visual analytics via data visualisations is therefore a very powerful tool and has become ever more important in this era. Data-Driven Documents (D3.js) is a versatile and popular web-based data visualisation library that has tended to be the standard toolkit for visualising data in recent years. However, the library is technically inherent and limited in capability by the single thread model of a single browser window in a single machine, and therefore not able to deal with large datasets. The main objective of this thesis is to overcome this limitation and address possible challenges by developing the Distributed D3 framework that employs distributed mechanism to enable the possibility of delivering web-based visualisations for large-scale data, which also allows to effectively utilise the graphical computational resources of the modern visualisation environments. As a result, the first contribution is that the integrated version of Distributed D3 framework has been developed for the Data Observatory. The work proves the concept of Distributed D3 is feasible in reality and also enables developers to collaborate on large-scale data visualisations by using it on the Data Observatory. The second contribution is that the Distributed D3 has been optimised by investigating the potential bottlenecks for large-scale data visualisation applications. The work finds the key performance bottlenecks of the framework and shows an improvement of the overall performance by 35.7% after optimisations, which improves the scalability and usability of Distributed D3 for large-scale data visualisation applications. The third contribution is that the generic version of Distributed D3 framework has been developed for the customised environments. The work improves the usability and flexibility of the framework and makes it ready to be published in the open-source community for further improvements and usages.Open Acces

Online advertising: analysis of privacy threats and protection approaches

Online advertising, the pillar of the “free” content on the Web, has revolutionized the marketing business in recent years by creating a myriad of new opportunities for advertisers to reach potential customers. The current advertising model builds upon an intricate infrastructure composed of a variety of intermediary entities and technologies whose main aim is to deliver personalized ads. For this purpose, a wealth of user data is collected, aggregated, processed and traded behind the scenes at an unprecedented rate. Despite the enormous value of online advertising, however, the intrusiveness and ubiquity of these practices prompt serious privacy concerns. This article surveys the online advertising infrastructure and its supporting technologies, and presents a thorough overview of the underlying privacy risks and the solutions that may mitigate them. We first analyze the threats and potential privacy attackers in this scenario of online advertising. In particular, we examine the main components of the advertising infrastructure in terms of tracking capabilities, data collection, aggregation level and privacy risk, and overview the tracking and data-sharing technologies employed by these components. Then, we conduct a comprehensive survey of the most relevant privacy mechanisms, and classify and compare them on the basis of their privacy guarantees and impact on the Web.Peer ReviewedPostprint (author's final draft

A WebGL application based on BIM IFC

Dissertação apresentada à Universidade Fernando Pessoa como partes dos requisitos para a obtenção do grau de Mestre em Engenharia Informática, ramo de Computação MóvelThe possibility of displaying high performance 3D accelerated graphics in the browser is seen as an obstacle to the conversion of applications to the web. The release of WebGL made Web3D gain new strength to overcome that obstacle. Architecture, Engineering and Construction (AEC) tools are a type of applications that could benefit with this advance. In the AEC industry, there is a standard candidate for Building Information Modelling (BIM), called Industry Foundation Classes (IFC). This data model promotes interoperability between AEC tools, giving a common format to the applications. This work comes from the need of redesigning a legacy application that allows the user to design, display and calculate building structures. Focusing on the displaying of building structures, this work merges IFC and WebGL into an application, to replicate in a modern way the legacy application capabilities. This is done by developing a server module that processes the IFC data model and a client module that displays that model in a WebGL environment. The result is a prototype web application capable of displaying 3D IFC building models in the browser without plug-ins. A possibilidade de visualização de gráficos acelerados 3D de alto desempenho no navegador ainda é visto como um obstáculo na migração de aplicações para a web. O lançamento do WebGL fez o Web3D ganhar uma nova força para superar esse obstáculo. As ferramentas de Arquitetura, Engenharia e Construção (AEC) são um tipo de aplicações que podem beneficiar com este avanço. Na indústria AEC, há um candidato a padrão para Building Information Modelling (BIM), chamado de Industry Foundation Classes (IFC). Este modelo de dados promove a interoperabilidade entre as ferramentas de AEC, fornecendo um formato comum às aplicações. Este trabalho surge da necessidade de redesenhar uma aplicação legada que permite ao o utilizador projetar, visualizar e calcular estruturas de edifícios. Focando na visualização de estruturas de edifícios, este trabalho funde o IFC e o WebGL numa aplicação, para replicar de forma moderna as capacidades da aplicação legada. Isto é feito através do desenvolvimento de um módulo de servidor que processa o modelo de dados IFC e um módulo de cliente que mostra esse modelo num ambiente WebGL. O resultado é um protótipo duma aplicação web capaz de visualizar modelos 3D de edifícios em formato IFC no browser sem plug-ins

Leveraging Tiled Display for Big Data Visualization Using D3.js

Data visualization has proven effective at detecting patterns and drawing inferences from raw data by transforming it into visual representations. As data grows large, visualizing it faces two major challenges: 1) limited resolution i.e. a screen is limited to a few million pixels but the data can have a billion data points, and 2) computational load i.e. processing of this data becomes computationally challenging for a single node system. This work addresses both of these issues for efficient big data visualization. In the developed system, a High Pixel Density and Large Format display was used enabling the display of fine details on the screen when visualizing data. Apache Spark and Hadoop used in the system allow the computation to be done on a cluster. The system is demonstrated using a global wind flow simulation. The Global Surface Summary of the Day dataset is processed and visualized using web browsers with Data-Driven Documents (D3).js code. We conducted both a performance evaluation and a user study to measure the performance and effectiveness of the system. It was seen that the system was most efficient when visualizing data using streamed bitmap images rather than streamed raw data. The system only rendered images at 6-10 Frames Per Second (FPS) and did not meet our target of rendering images at 30 FPS. The results of the user study concluded that the system is effective and easy to use for data visualization. The outcome of our experiment suggests that the current state of Google Chrome may not be as powerful as required to perform heavy 2D data visualization on the web and still needs more development for visualizing data of large magnitude

Flexi-WVSNP-DASH: A Wireless Video Sensor Network Platform for the Internet of Things

abstract: Video capture, storage, and distribution in wireless video sensor networks (WVSNs) critically depends on the resources of the nodes forming the sensor networks. In the era of big data, Internet of Things (IoT), and distributed demand and solutions, there is a need for multi-dimensional data to be part of the Sensor Network data that is easily accessible and consumable by humanity as well as machinery. Images and video are expected to become as ubiquitous as is the scalar data in traditional sensor networks. The inception of video-streaming over the Internet, heralded a relentless research for effective ways of distributing video in a scalable and cost effective way. There has been novel implementation attempts across several network layers. Due to the inherent complications of backward compatibility and need for standardization across network layers, there has been a refocused attention to address most of the video distribution over the application layer. As a result, a few video streaming solutions over the Hypertext Transfer Protocol (HTTP) have been proposed. Most notable are Apple’s HTTP Live Streaming (HLS) and the Motion Picture Experts Groups Dynamic Adaptive Streaming over HTTP (MPEG-DASH). These frameworks, do not address the typical and future WVSN use cases. A highly flexible Wireless Video Sensor Network Platform and compatible DASH (WVSNP-DASH) are introduced. The platform's goal is to usher video as a data element that can be integrated into traditional and non-Internet networks. A low cost, scalable node is built from the ground up to be fully compatible with the Internet of Things Machine to Machine (M2M) concept, as well as the ability to be easily re-targeted to new applications in a short time. Flexi-WVSNP design includes a multi-radio node, a middle-ware for sensor operation and communication, a cross platform client facing data retriever/player framework, scalable security as well as a cohesive but decoupled hardware and software design.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

3D modeling and visualization of utility networks

Most of the current 2D GIS representations are tied to the limits of the GIS software tools used and are, more properly, simplifications of the real aspects of the territory. The development of 3D GIS tools has brought to life by the belief that the description of the reality and the analysis of the phenomena that take place in it must be done in the proper dimensions. An important field of application of GIS software tools is the utility networks management. Existing software tools that support management and 3D visualisation of utility networks are powerful but very expansive. The aim of the project is to design a general network model that will be used to model an utility network and to visualise it in 3D. The general network model has been designed to be data source and platform independent. It can take data from OGC standard compliant data source like GeoDBMS and WFS Servers and can be enriched by a user defined set of attributes, making it suitable for every network analysis and management need. On the top of the general network model has been designed a geometrical model that transforms the general network model in a 3D model which can be displayed using a WebGL graphic engine. Using the general network model and the geometrical model has been designed and developed a WebGL viewer that visualises the network model over a DTM with a complete navigation system that allows a complete tour of the scene and data query and editingopenEmbargo per motivi di segretezza e di proprietà dei risultati e informazioni sensibil