Web Workers Research Articles

HydroCompute: An open-source web-based computational library for hydrology and environmental sciences

We present HydroCompute, a high-performance client-side computational library specifically designed for web-based hydrological and environmental science applications. Leveraging state-of-the-art technologies in web-based scientific computing, the library facilitates both sequential and parallel simulations, optimizing computational efficiency. Employing multithreading via web workers, HydroCompute enables the porting and utilization of various engines, including WebGPU, Web Assembly, and native JavaScript code. Furthermore, the library supports local data transfers through peer-to-peer communication using WebRTC. The flexible architecture and open-source nature of HydroCompute provide effective data management and decision-making capabilities, allowing users to integrate their own code into the framework. To demonstrate the capabilities of the library, we conducted two case studies: a benchmarking study assessing the performance of different engines and a real-time data processing and analysis application for the state of Iowa. The results exemplify HydroCompute's potential to enhance computational efficiency and contribute to the interoperability and advancement of hydrological and environmental sciences.

Towards progressive geospatial information processing on web systems: a case study for watershed analysis in Iowa

Geographic Information Systems (GIS) are available as stand-alone desktop applications as well as web platforms for vector- and raster-based geospatial data processing and visualization. While each approach offers certain advantages, limitations exist that motivate the development of hybrid systems that will increase the productivity of users for performing interactive data analytics using multidimensional gridded data. Web-based applications are platform-independent, however, require the internet to communicate with servers for data management and processing which raises issues for performance, data integrity, handling, and transfer of massive multidimensional raster data. On the other hand, stand-alone desktop applications can usually function without relying on the internet, however, they are platform-dependent, making distribution and maintenance of these systems difficult. This paper presents RasterJS, a hybrid client-side web library for geospatial data processing that is built on the Progressive Web Application (PWA) architecture to operate seamlessly in both Online and Offline modes. A packaged version of this system is also presented with the help of Web Bundles API for offline access and distribution. RasterJS entails the use of latest web technologies that are supported by modern web browsers, including Service Workers API, Cache API, IndexedDB API, Notifications API, Push API, and Web Workers API, in order to bring geospatial analytics capabilities to large-scale raster data for client-side processing. Each of these technologies acts as a component in the RasterJS to collectively provide a similar experience to users in both Online and Offline modes in terms of performing geospatial analysis activities such as flow direction calculation with hydro-conditioning, raindrop flow tracking, and watershed delineation. A large-scale case study is included in the study for watershed analysis to demonstrate the capabilities and limitations of the library. The framework further presents the potential to be utilized for other use cases that rely on raster processing, including land use, agriculture, soil erosion, transportation, and population studies.

DuckDB-wasm

We introduce DuckDB-Wasm, a WebAssembly version of the database system DuckDB, to provide fast analytical processing for the Web. DuckDB-Wasm evaluates SQL queries asynchronously in web workers, supports efficient user-defined functions written in JavaScript, and features a browser-agnostic filesystem that reads local and remote data in pages. DuckDB-Wasm outperforms previous data processing libraries for the Web in the TPC-H benchmark at multiple scale factors. We demonstrate the capabilities of an analytical database in the browser using an interactive SQL shell.

Search methods for abnormal activities of web applications

Subject of Research. The paper presents a review of existing detection methods for abnormal activities of web applications. Comparative characteristics are given. Priorities for improving information security tools in web applications are shown. Method. For evaluation of search methods for abnormal activities of web applications, criteria for selecting indicators were defined. Particular attention was paid to such indicators as: the launching speed of web applications after loading, web application responsiveness to user actions and the number of abnormal activities found in comparison with the number of malfunctions found. Three methods of searching for abnormal activities were compared: statistical code scanning, dynamic code scanning and network traffic monitoring. We considered advantages and disadvantages of each method and implementation examples. Main Results. It is shown that the dynamic method of searching for abnormal activities has the best characteristics. The method provides the identification of anomalies associated with traffic transfer and anomalies that occur during the local operation of web applications. The method is implemented as a code analyzer built into the browser engine. The analyzer checks all calls of the web application to the engine and detects abnormal activity based on such calls. In contrast to static scanning, dynamic scanning identifies anomalies in Web Workers, WebAssembly and in the parts of code that are downloaded over the network after the application starts. Practical Relevance. The work can be useful to information security specialists who deal with the problems of protecting web applications, as well as programmers and system administrators at application creation and implementation stage. The results of the work can find practical use in the development of web applications, browsers, and information protection software.

Java Script Data Transformation Library using Fork Join Pool and Web Workers Technology

Transforming large amounts of data takes a lot of processing time so that the optimization technique is required. One way that can be used to perform optimization is multithreading. Nowadays, processor is proliferating. The average processor in community is multi-core processor that can do parallel processing. Prior to the emergence of Web Workers, JavaScript is a poor programming language for parallel programming. The emergence of Web Workers allows JavaScript to do a better job in parallel programming. Fork Join Pool is a method that implements the Divide and Conquers algorithm, so it is suitable for the use in multithreading. This data transformation library was created by implementing the ForkJoinPool method using Web Workers technology in JavaScript. This program is written in JavaScript and HTML language. Based on results of testing phase that has been done, it is proven that ForkJoinPool method can be implemented using Web Workers technology in JavaScript as a data transformation library. In addition, it can be concluded that the data transformation library usage affects the speed of data transformation which depends on the data transformation complexity. The higher the complexity of data transformation performed, the effectiveness in the use of data transformation libraries will increase.

Geant-val:

One of the key factors for the successful development of Monte- Carlo programs for physics simulations is to properly organize regression testing and validation. Geant4, the world-standard toolkit for HEP detector simulation, heavily relies on this activity. The CERN SFT group, which contributes to the development, testing, deployment and support of the toolkit, is also in charge of running on a monthly basis a set of community-developed tests using the development releases of Geant4. We present the web application Geant-val developed for visualizing the results of these tests so that comparisons between different Geant4 releases can be made. The application is written using the Express.js, Node.js and Angular frameworks and uses PostgreSQL for storing test results. Test results are visualised using ROOT and JSROOT. In addition to pure visual comparisons, we perform different statistical tests (χ2, Kolmogorov- Smirnov, etc.) on the client side using JavaScript Web Workers.

Max-Margin Majority Voting for Learning from Crowds.

Learning-from-crowds aims to design proper aggregation strategies to infer the unknown true labels from the noisy labels provided by ordinary web workers. This paper presents max-margin majority voting (M$^3$3V) to improve the discriminative ability of majority voting and further presents a Bayesian generalization to incorporate the flexibility of generative methods on modeling noisy observations with worker confusion matrices for different application settings. We first introduce the crowdsourcing margin of majority voting, then we formulate the joint learning as a regularized Bayesian inference (RegBayes) problem, where the posterior regularization is derived by maximizing the margin between the aggregated score of a potential true label and that of any alternative label. Our Bayesian model naturally covers the Dawid-Skene estimator and M$^3$3V as its two special cases. Due to the flexibility of our model, we extend it to handle crowdsourced labels with an ordinal structure with the main ideas about the crowdsourcing margin unchanged. Moreover, we consider an online learning-from-crowds setting where labels coming in a stream. Empirical results demonstrate that our methods are competitive, often achieving better results than state-of-the-art estimators.

Selective Verification Strategy for Learning From Crowds

To deal with the low qualities of web workers in crowdsourcing, many unsupervised label aggregation methods have been investigated but most of them provide inconsistent performance. In this paper, we explore the learning from crowds with selective verification problem. In addition to the noisy responses from the crowds, it also collects the ground truths for a well-chosen subset of tasks as the reference, then aggregates the redundant responses based on the patterns provided by both the supervised and unsupervised signal. To improve the labeling efficiency, we propose the EBM selecting strategy for choosing the verification subset, which is based on the loss error minimization. Specifically, we first establish the expected loss error given the semi-supervised learning estimate, then find the subset that minimizes this selecting criterion. We do extensive empirical comparisons on both synthetic and real-world datasets to show the benefits of this new learning setting as well as our proposal.

Lightweight Volunteer Computing Platform using Web Workers

Volunteer computing is a very appealing way of utilizing vast available resources in an efficient way. However currently available platforms supporting this computing style are either difficult to use or not available at all, being the results of e.g. finished scientific projects. In this paper a novel, lightweight volunteer computing platform is presented. In order to contribute the resources to this platform, only a web-browser is required without the need to install any additional plug-ins or other software. In this paper, besides general considerations and presentation of the platform structure and functionalities, selected results proving its efficiency are shown.

Web designers and developers experiences of information literacy: A phenomenographic study

The qualitative research reported here identifies how web designers and developers experience information literacy. Using a phenomenographic approach, this cohort's experience is presented through a map of variation, which includes four different ways of experiencing information literacy. Analysis of 23 in-depth interviews with web workers from different stages of the web design and development process suggested the four ways web workers experience information literacy: staying informed, building a successful website, solving a problem or participating in a community of practice. The study advances the existing understanding of the concept of information literacy, especially in a professional context and from a relational perspective. Additionally, using the web professionals' world as the context of the study, the research contributes to the field of website design and development by shedding light on less-researched information experiences of people involved in the web industry.

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.

GPU-based remote visualization of dynamic molecular data on the web

Visualization of dynamic data from molecular dynamics simulations is crucial for understanding the functioning of molecules. Many existing visualization tools have mainly focused on supporting a single user working on a desktop computer. Technical advancements in browser features increase the potential for the development of web-based collaborative visualization tools. Although web-based molecular viewers already exist, their support for dynamic molecular data at interactive rates is lacking. To address this gap, we present an efficient web application for visualization of dynamic molecular data using WebGL that exploits HTML5 technologies like WebSockets and Web Workers. GPU-based ray casting techniques offer fast rendering times and produce images with higher visual quality. Efficient data encoding techniques are used to minimize the data transferred to the client; therefore saving bandwidth and improving the transfer times. We demonstrate the feasibility of visualizing large dynamic molecular data with more than one million atoms in the browser at interactive frame rates. Our approach allows scientists at arbitrary locations to concurrently visually analyze the same data. The interactive parameterization of the visualization can be shared among multiple clients, providing the basis for collaborative research. Moreover, the application can be employed for remote simulation monitoring on mobile devices.

Dynamic web worker pool management for highly parallel javascript web applications

SummaryJavaScript web applications are improving performance mainly thanks to the inclusion of new standards by HTML5. Among others, web workers API allows multithreaded JavaScript web apps to exploit parallel processors. However, developers have difficulties to determine the minimum number of web workers that provide the highest performance. But even if developers found out this optimal number, it is a static value configured at the beginning of the execution. Because users tend to execute other applications in background, the estimated number of web workers could be non‐optimal, because it may overload or underutilize the system. In this paper, we propose a solution for highly parallel web apps to dynamically adapt the number of running web workers to the actual available resources, avoiding the hassle to estimate a static optimal number of threads. The solution consists in the inclusion of a web worker pool and a simple management algorithm in the web app. Even though there are co‐running applications, the results show our approach dynamically enables a number of web workers close to the optimal. Our proposal, which is independent of the web browser, overcomes the lack of knowledge of the underlying processor architecture as well as dynamic resources availability changes. Copyright © 2015 John Wiley & Sons, Ltd.

Guiding Novice Web Workers in Making Image Descriptions Using Templates

This article compares two methods of employing novice Web workers to author descriptions of science, technology, engineering, and mathematics images to make them accessible to individuals with visual and print-reading disabilities. The goal is to identify methods of creating image descriptions that are inexpensive, effective, and follow established accessibility guidelines. The first method explicitly presented the guidelines to the worker, then the worker constructed the image description in an empty text box and table. The second method queried the worker for image information and then used responses to construct a template-based description according to established guidelines. The descriptions generated through queried image description (QID) were more likely to include information on the image category, title, caption, and units. They were also more similar to one another, based on Jaccard distances of q-grams, indicating that their word usage and structure were more standardized. Last, the workers preferred describing images using QID and found the task easier. Therefore, explicit instruction on image-description guidelines is not sufficient to produce quality image descriptions when using novice Web workers. Instead, it is better to provide information about images, then generate descriptions from responses using templates.

Capataz: a framework for distributing algorithms via the World Wide Web

In recent years, some scientists have embraced the distributed computing paradigm. As experiments and simulations demand ever more computing power, coordinating the efforts of many different processors is often the only reasonable resort. We developed an open-source distributed computing framework based on web technologies, and named it Capataz. Acting as an HTTP server, web browsers running on many different devices can connect to it to contribute in the execution of distributed algorithms written in Javascript. Capataz takes advantage of architectures with many cores using web workers.
 This paper presents an improvement in Capataz´ usability and why it was needed. In previous experiments the total time of distributed algorithms proved to be susceptible to changes in the execution time of the jobs. The system now adapts by bundling jobs together if they are too simple. The computational experiment to test the solution is a brute force estimation of pi. The benchmark results show that by bundling jobs, the overall perfomance is greatly increased.

La tutela giuridica dell’attività creativa dei nuovi lavoratori del web

This article deals with the creative activity of web workers and explores feasible forms of legal protection. Digital works, as long as characterized by a minimal creative content, are protected by copyright law as creative intellectual work. The rise of the web, however, has changed the scenario in which workers carry out their works, the economic model, the legal actors and the author himself. The subject defined in copyright law is very different from workers of the web who resemble more to authorial forms of different periods and cultures. In this context, the A. proposes a redefinition of legal framework and new forms of protection for digital creative contents through a rethinking of the relationship between author and work.

BrainBrowser: distributed, web-based neurological data visualization.

Recent years have seen massive, distributed datasets become the norm in neuroimaging research, and the methodologies used to analyze them have, in response, become more collaborative and exploratory. Tools and infrastructure are continuously being developed and deployed to facilitate research in this context: grid computation platforms to process the data, distributed data stores to house and share them, high-speed networks to move them around and collaborative, often web-based, platforms to provide access to and sometimes manage the entire system. BrainBrowser is a lightweight, high-performance JavaScript visualization library built to provide easy-to-use, powerful, on-demand visualization of remote datasets in this new research environment. BrainBrowser leverages modern web technologies, such as WebGL, HTML5 and Web Workers, to visualize 3D surface and volumetric neuroimaging data in any modern web browser without requiring any browser plugins. It is thus trivial to integrate BrainBrowser into any web-based platform. BrainBrowser is simple enough to produce a basic web-based visualization in a few lines of code, while at the same time being robust enough to create full-featured visualization applications. BrainBrowser can dynamically load the data required for a given visualization, so no network bandwidth needs to be waisted on data that will not be used. BrainBrowser's integration into the standardized web platform also allows users to consider using 3D data visualization in novel ways, such as for data distribution, data sharing and dynamic online publications. BrainBrowser is already being used in two major online platforms, CBRAIN and LORIS, and has been used to make the 1TB MACACC dataset openly accessible.

Privilege Separation in Browser Extensions Based on Web Workers

In this paper, we propose to use Web Workers [1], isolated parallel threads in current browser working in the background, to enforce privilege separation in chrome extensions. Our tests show that our design is applicable to most chrome extensions (those not using the jquery library) and achieves a reduction in TCB up to 77 percent for our examples. Our implementation shows that our design is efficient enough to enforce privilege separation in chrome extensions and not needs to modify the browser or learn new high-level languages.

Fast access to the CMS detector condition data employing HTML5 technologies

This paper focuses on using HTML version 5 (HTML5) for accessing condition data for the CMS experiment, evaluating the benefits and risks posed by the use of this technology. According to the authors of HTML5, this technology attempts to solve issues found in previous iterations of HTML and addresses the needs of web applications, an area previously not adequately covered by HTML.We demonstrate that employing HTML5 brings important benefits in terms of access performance to the CMS condition data. The combined use of web storage and web sockets allows increasing the performance and reducing the costs in term of computation power, memory usage and network bandwidth for client and server. Above all, the web workers allow creating different scripts that can be executed using multi-thread mode, exploiting multi-core microprocessors. Web workers have been employed in order to substantially decrease the web page rendering time to display the condition data stored in the CMS condition database.

Load distribution by using Web Workers for a real‐time web application

PurposeThe purpose of this paper is to propose a load distribution technique for a web server. It utilizes Web Workers, which is a new feature of Javascript.Design/methodology/approachThe authors have been implementing a web‐based MORPG as an interactive, real‐time web application; previously, the web server alone was responsible for manipulating the behavior of all the game characters. As more users logged in, the workload on the server was increased. Hence, the authors have implemented a technique whereby the CPU load of the server is distributed among the clients.FindingsThe authors found that some caching mechanism is useful for utilizing client‐side calculation. The caching suppresses the increase of communication load. A performance evaluation reveals that the technique plays a role in decreasing the CGI latency of both low‐end server and high‐end server. The average latency is reduced to 59.5 percent of the original system.Originality/valueWeb Workers allows scripts to be executed with keeping the page response on a web browser. It is intended to be used for raising user experience. This technique utilizes Web Workers for a web server to distribute the load to its clients.