We’ve been here a long time, and there’s no real foreseeable end to our stay. We have molded it after our needs, we keep doing so, and still we’re not quite satisfied. We could leave at any time, just leave and never again visit, but that’s just theoretical – you know it’s not really an option. We’ve grown addicted to it.
If you somehow haven’t managed to figure it out by now, I’m talking about the internet. It’s our home away from home, but also our job, our free time, and our all-in-one source of information. And there’s one big problem with it – it’s too slow. But according to a new study from our very own United States, web pages will load 34% faster thanks to MIT.
A team of researchers from MIT’s Computer Science and Artificial Intelligence Laboratory, or CSAIL for short, and Harvard managed to develop a technology that will help reduce internet loading times by 34 percent.
Polaris, as the technology was dubbed, works by figuring out the absolute best way possible to overlap downloading the objects of a page so that it would lead to better and faster loading times. Not to be confused with the recent ‘The 100’ revelation, Poalris is simply a way to better download the contents of a page so that it loads faster.
To better explain how the whole thing works without actually giving away the technical details, James Mickens, one of the study’s co-authors, made a very interesting analogy to a travelling businessman.
Let’s say a businessman is visiting a city. When he gets there, he finds out about the existence of other cities nearby that he has to visit for work. He can then start planning how to visit each city, and where to go next. This is how regular web pages actually load – the script finds new content to load when it gets to the page.
But if the businessman is given a map of all the possible cities he can visit before they even go on their trip, they will have a far easier time planning for how to travel – this is how Polaris works.
The paper will be presented in front of a USENIX Symposium on Networked Systems Design and Implementation by the lead author, Ph.D. student Ravi Netravali, and it was completed with the help of his co-authors, Harvard professor James Mickens, MIT professor Hari Balakrishnan, and MIT student Ameesh Goyal.
Image source: Wikimedia