NeTS: Small: Data Driven Mobile Web Performance

NetS：小型：数据驱动的移动 Web 性能

基本信息

批准号：
1814285
负责人：
Theophilus Benson
金额：
$ 50万
依托单位：
Brown University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-10-01 至 2023-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1814285&HistoricalAwards=false
关键词：
NeTS Small Data Driven Mobile

项目摘要

The world is growing increasingly dependent on web services; they are now a vital part of business, personal and social aspects of daily life. Unfortunately, users continue to be plagued by a myriad of performance problems, e.g., videos that stall while buffering, slow web page load times, and web pages that crash. These performance problems occur for multiple reasons, the principal one being a lack of correctly configured and adequately tuned networking protocols and algorithms that can deliver the desired quality of service. Moreover, as the set of web services and technologies continues to grow and broaden, the performance implications of these poorly configured networks are likely to become more widespread and apparent. The project vision is to develop an alternative approach to managing and configuring web servers that can meet end user's performance expectations: a method which improves performance by tailoring the web server's configurations to match the specifics of each application and end user's technology. If successful, this proposal will fundamentally impact widely accepted principles for managing services and will enable a broad range of users to benefit from efficient operation of the growing set of essential web services.This project proposes an ambitious research agenda based on a data-driven specialization of the web serving stacks, wherein the stack learns the optimal protocol optimizations and parameters for each user and, in turn, uses this information to specialize or tune the web stack to improve the end user's experience. The proposed research has five thrusts: First, the project will conduct a large-scale systematic study on the interactions between protocol configuration options, e.g., optimizations, device profiles, web complexity, and network conditions and develop tools to analyze and interpret the implications of these interactions. Second, it will develop a new architecture for managing web servers that provides a flexible and uniform interface for collecting telemetry data and configuring protocol parameters and optimizations. Third, the researchers will develop a dynamic learning framework that scalably and accurately learns and predicts the optimal configuration for each user. Fourth, the project proposes to develop a novel programming interface that enables end-users and their devices to participate in the learning process by providing feedback and meta-data that is only available on the client side. Finally, the researchers will consider a number of design and implementation challenges necessary to realize this new approach, including adjusting to drastic changes in network conditions, tackling complex relationships between configuration parameters and user experience, making real-time predictions, etc. This project will actively undertake tasks to realize broader impact through educational outreach across all levels of education, with a focus on undergraduate and high school students, and under-represented minorities in Science, Technology, Engineering, and Mathematics.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

世界越来越依赖网络服务；它们现在已成为日常生活中商业、个人和社会方面的重要组成部分。不幸的是，用户仍然受到无数性能问题的困扰，例如视频在缓冲时停止、网页加载时间缓慢以及网页崩溃。出现这些性能问题的原因有多种，其中最主要的一个是缺乏能够提供所需服务质量的正确配置和充分调整的网络协议和算法。此外，随着网络服务和技术的不断增长和拓宽，这些配置不当的网络对性能的影响可能会变得更加普遍和明显。该项目的愿景是开发一种管理和配置 Web 服务器的替代方法，以满足最终用户的性能期望：一种通过定制 Web 服务器的配置以匹配每个应用程序和最终用户技术的具体情况来提高性能的方法。如果成功，该提案将从根本上影响广泛接受的服务管理原则，并使广泛的用户能够从不断增长的基本网络服务的高效运营中受益。该项目提出了一个基于数据驱动专业化的雄心勃勃的研究议程Web 服务堆栈，其中堆栈学习每个用户的最佳协议优化和参数，然后使用此信息来专门化或调整 Web 堆栈以改善最终用户的体验。拟议的研究有五个重点：首先，该项目将对协议配置选项（例如优化、设备配置文件、网络复杂性和网络条件）之间的相互作用进行大规模系统研究，并开发工具来分析和解释这些选项的影响。这些相互作用。其次，它将开发一种用于管理网络服务器的新架构，该架构为收集遥测数据以及配置协议参数和优化提供灵活且统一的界面。第三，研究人员将开发一个动态学习框架，可扩展且准确地学习和预测每个用户的最佳配置。第四，该项目建议开发一种新颖的编程接口，使最终用户及其设备能够通过提供仅在客户端可用的反馈和元数据来参与学习过程。最后，研究人员将考虑实现这种新方法所需的许多设计和实施挑战，包括适应网络条件的剧烈变化、处理配置参数和用户体验之间的复杂关系、进行实时预测等。该项目将积极承担任务，通过各级教育的教育推广来实现更广泛的影响，重点是本科生和高中生，以及科学、技术、工程和数学领域代表性不足的少数群体。该奖项反映了 NSF 的法定使命，并已认为值得支持通过使用基金会的智力优点和更广泛的影响审查标准进行评估。

项目成果

期刊论文数量（8）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

WebMedic: Disentangling the Memory-Functionality Tension for the Next Billion Mobile Web Users

WebMedic：为下一个十亿移动网络用户解决内存功能紧张的问题

DOI：
10.1145/3446382.3448652
发表时间：
2021-02-24
期刊：
Proceedings of the 22nd International Workshop on Mobile Computing Systems and Applications
影响因子：
0
作者：
Usama Naseer;Theophilus A. Benson;R. Netravali
通讯作者：
R. Netravali

JS Capsules: A Framework for Capturing Fine-grained JavaScript Memory Measurements for the Mobile Web.

JS Capsules：用于捕获移动 Web 细粒度 JavaScript 内存测量的框架。