Web浏览器执行环境性能的下一个演变

IF 2.6 4区计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Big Data Pub Date : 2023-08-03 DOI:10.1109/icABCD59051.2023.10220564

Zahir Toufie, Boniface Kabaso

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引用次数: 0

摘要

长期以来，Web浏览器一直希望在其执行环境(EE)中托管和执行功能丰富、计算密集型和复杂的应用程序或简单的计算密集型应用程序(CIAs)，并具有本地桌面性能。有Adobe Shockwave, Macromedia Flash, Java applet, JavaScript编程语言(JS)和最近的WebAssembly编程语言(WASM)，但也有短暂的关系，如Microsoft ActiveX, Silverlight和Apple Quicktime。web浏览器托管和执行具有本地桌面性能的cia的一个障碍是，目前还没有具有支持它们的软件体系结构和设计的web浏览器技术。本文旨在回顾自WASM兴起以来Web作为应用程序平台的演变，在过去十年左右的时间里，在相对于本地桌面应用程序性能的应用程序性能上下文中。同时提出了研究人员应该集中精力的地方，以便将Web推进为能够执行cia的应用程序平台。在未来的工作中，我们计划扩展我们的研究，包括理论贡献，例如提供关于如何提高基于各种软件架构和web浏览器EEs设计的web应用程序性能的见解，方法贡献，例如提供开发、调整或增强的方法和方法，这些方法和方法详细说明了web浏览器EEs的软件架构和设计，这些软件架构和设计比现有的性能更高。以及将为基于我们的研究产生的原型web浏览器EE的生产就绪web浏览器EE奠定基础的实际贡献。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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The Next Evolution of Web Browser Execution Environment Performance

Web browsers have for long been wanting to host and execute feature-rich, compute-intensive, and complex applications or simply Compute-Intensive Applications (CIAs), within their Execution Environment (EE), with native desktop performance. There was Adobe Shockwave, Macromedia Flash, Java Applets, JavaScript Programming Language (JS) and recently WebAssembly Programming Language (WASM), but also short-lived relationships, such as Microsoft ActiveX, Silverlight and Apple Quicktime. One hindrance to web browsers hosting and executing CIAs with native desktop performance is that currently there is no web browser technology with the software architecture and design that can support them. This paper aims to review the evolution of the Web as an application platform since the rise of WASM, over the last decade or so, within the context of application performance relative to that of native desktop application performance. As well as to propose where researchers should focus their efforts in order to advance the Web as an application platform that is capable of executing CIAs. In future work, we plan to extend our study to include theoretical contributions, such as providing insights into how to improve the performance of web applications based on various software architectures and designs for web browser EEs, methodological contributions, such as providing methods and approaches developed, adapted or enhanced which detail the software architecture and design for web browser EEs that have higher performance than currently available, and practical contributions that will lay the groundwork for a production-ready web browser EE based on the prototype web browser EE produced by our study.

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来源期刊

Big Data COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-COMPUTER SCIENCE, THEORY & METHODS

CiteScore

9.10

自引率

2.20%

发文量

期刊介绍： Big Data is the leading peer-reviewed journal covering the challenges and opportunities in collecting, analyzing, and disseminating vast amounts of data. The Journal addresses questions surrounding this powerful and growing field of data science and facilitates the efforts of researchers, business managers, analysts, developers, data scientists, physicists, statisticians, infrastructure developers, academics, and policymakers to improve operations, profitability, and communications within their businesses and institutions. Spanning a broad array of disciplines focusing on novel big data technologies, policies, and innovations, the Journal brings together the community to address current challenges and enforce effective efforts to organize, store, disseminate, protect, manipulate, and, most importantly, find the most effective strategies to make this incredible amount of information work to benefit society, industry, academia, and government. Big Data coverage includes: Big data industry standards, New technologies being developed specifically for big data, Data acquisition, cleaning, distribution, and best practices, Data protection, privacy, and policy, Business interests from research to product, The changing role of business intelligence, Visualization and design principles of big data infrastructures, Physical interfaces and robotics, Social networking advantages for Facebook, Twitter, Amazon, Google, etc, Opportunities around big data and how companies can harness it to their advantage.