Conference proceeding
Client-side Reconstruction of Composite Mementos Using ServiceWorker
2017 ACM/IEEE JOINT CONFERENCE ON DIGITAL LIBRARIES (JCDL 2017), pp 237-240
01 Jan 2017
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
We use the ServiceWorker (SW) API to intercept HTTP requests for embedded resources and reconstruct Composite Mementos without the need for conventional URL rewriting typically performed by web archives. URL rewriting is a problem for archival replay systems, especially for URLs constructed by JavaScript, that frequently results in incorrect URI references. By intercepting requests on the client using SW, we are able to strategically reroute instead of rewrite. Our implementation moves rewriting to clients, saving servers' computing resources and allowing servers to return responses more quickly. In our experiments, retrieving the original instead of rewritten pages from the archive resulted in a one-third reduction in time overhead and a one-fifth reduction in data overhead. Our system, reconstructive. js, prevents the live web from leaking into Composite Mementos while being easy to distribute and maintain.
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Details
- Title
- Client-side Reconstruction of Composite Mementos Using ServiceWorker
- Creators
- Sawood Alam - Old Dominion UniversityMat Kelly - Old Dominion UniversityMichele C. Weigle - Old Dominion UniversityMichael L. Nelson - Old Dominion University
- Publication Details
- 2017 ACM/IEEE JOINT CONFERENCE ON DIGITAL LIBRARIES (JCDL 2017), pp 237-240
- Series
- ACM-IEEE Joint Conference on Digital Libraries JCDL
- Publisher
- IEEE
- Number of pages
- 4
- Grant note
- III 1526700 / NSF; National Science Foundation (NSF)
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000464555400026
- Scopus ID
- 2-s2.0-85028023748
- Other Identifier
- 991021786594404721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Information Systems
- Computer Science, Theory & Methods
- Information Science & Library Science