Washington, May 3 : Sick and tired of your slow Internet connection? Well, here's the culprit who's responsible for 70 percent of the jam - Peer-to-peer (P2P) file-sharing services, which connect individual users for simultaneous uploads and downloads directly rather than through a central server.
Such a level of use has led to a growing tension between Internet Service Providers (ISPs) and their customers' P2P file-sharing services, and has driven service providers to forcefully reduce P2P traffic at the expense of unhappy subscribers and the risk of government investigations.
Now researchers at Northwestern University's McCormick School of Engineering and Applied Science have discovered a way to ease that tension: Ono, a unique software solution that allows users to efficiently identify nearby P2P clients.
The software, which is freely available and has been downloaded by more than 150,000 users, benefits ISPs by reducing costly cross-network traffic without sacrificing performance for the user.
In fact, when ISPs configure their networks properly, their software significantly improves transfer speeds - by as much as 207 percent on average.
Ono, developed by Fabi¡n E. Bustamante, assistant professor of electrical engineering and computer science, and Ph.D. student David Choffnes, has been deployed for the Azureus BitTorrent P2P file-sharing client.
"Finding nearby computers for transferring data may seem like a simple thing to do, but the problem is that the Internet doesn't have a Google Map. Every computer may have an address, but it doesn't tell you whether the machine is close to you," said Choffnes.
Ono relies on a clever trick based on observations of Internet companies like Akamai (incidentally Hawaiian for "clever"). Akamai is a content-distribution network (CDN), which offloads data traffic from Web sites onto their proprietary network of more than 10,000 servers worldwide.
Using the key assumption that two computers sent to the same CDN server are likely close to each other, Ono allows P2P users to quickly identify nearby users.
"The more users we have, the better the system works, so we're just trying make it easy to spread," says Bustamante.