Over the years our internet connections have gotten faster, but thanks to these increases in speed we’ve been able to develop websites that are increasingly complex. As a result, we can still find ourselves tapping our fingers impatiently on the sides of our phones or across our keyboards as we wait for a page to load. There have been data compression techniques developed in order to try and reduce load times, but researchers at MIT Computer Science and Artificial Intelligence Laboratory and Harvard University have decided to go in a slightly different direction with their attempt that they’re saying is “more consistent and more substantive” with its results.
The Polaris system essentially gives your browser a plan of action, logging all of a web page’s dependencies and compiling them into a graph that your browser can use to establish the most efficient loading path ahead of time. The team acknowledge that dependency tracking methods like this have been attempted before, but say these methods that focussed on comparing lexical relationships don’t”capture more subtle dependencies” that Polaris is able to.
The team have compare the process to that of a travelling salesman:
“When you visit one city, you sometimes discover more cities you have to visit before going home. If someone gave you the entire list of cities ahead of time, you could plan the fastest possible route. Without the list, though, you have to discover new cities as you go, which results in unnecessary zig-zagging between far-away cities.
For a Web browser, loading all of a page’s objects is like visiting all of the cities. Polaris effectively gives you a list of all the cities before your trip actually begins. It’s what allows the browser to load a webpage more quickly.”
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