Web pages today commonly include large amounts of JavaScript code in order to offer users a dynamic experience. These scripts often make pages slow to load, partly due to a
fundamental inefficiency in how browsers process JavaScript content: browsers make it easy for web developers to reason about page state by serially executing all scripts on any frame
in a page, but as a result, fail to leverage the multiple CPU cores that are readily available even on low-end phones.
In this paper, we show how to address this inefficiency without requiring pages to be rewritten or browsers to be modified. The key to our solution, Horcrux, is to account
for the non-determinism intrinsic to web page loads and the constraints placed by the browser’s API for parallelism. Horcrux-compliant web servers perform offline analysis of all the JavaScript code on any frame they serve to conservatively identify, for every JavaScript function, the union of the page state that the function could access across all loads of that page. Horcrux’s JavaScript scheduler then uses this information to judiciously parallelize JavaScript execution on the client-side so that the end-state is identical to that of a serial execution, while minimizing coordination and offloading overheads. Across a wide range of pages, phones, and mobile networks covering web workloads in both developed and emerging regions, Horcrux reduces median browser computation delays by 31-44% and page load times by 18-37%.
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On Landing and Internal Web Pages: The Strange Case of Jekyll and Hyde in Web Performance Measurement
There is a rich body of literature on measuring and optimizing nearly every aspect of the web, including characterizing the structure and content of web pages, devising new techniques to load pages quickly, and evaluating such techniques. Virtually all of this prior work used a single page, namely the landing page (i.e., root document, "/"), of each web site as the representative of all pages on that site. In this paper, we characterize the differences between landing and internal (i.e., non-root) pages of 1000 web sites to demonstrate that the structure and content of internal pages differ substantially from those of landing pages, as well as from one another. We review more than a hundred studies published at top-tier networking conferences between 2015 and 2019, and highlight how, in light of these differences, the insights and claims of nearly two-thirds of the relevant studies would need to be revised for them to apply to internal pages.
Going forward, we urge the networking community to include internal pages for measuring and optimizing the web. This recommendation, however, poses a non-trivial challenge: How do we select a set of representative internal web pages from a web site? To address the challenge, we have developed Hispar, a "top list" of 100,000 pages updated weekly comprising both the landing pages and internal pages of around 2000 web sites. We make Hispar and the tools to recreate or customize it publicly available.
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- Award ID(s):
- 1763742
- NSF-PAR ID:
- 10318921
- Date Published:
- Journal Name:
- IMC '20: Proceedings of the ACM Internet Measurement Conference
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3419394.3423626
