Skip to Content
Uncategorized

Wireless Isn’t What You Think It Is

Dartmouth’s Computer Science Department has released a technical report comparing actual wireless network performance with what both models and most people think wireless performance actually is.Quoting from the abstract: Although it is tempting to assume that all radios have circular…

Dartmouth’s Computer Science Department has released a technical report comparing actual wireless network performance with what both models and most people think wireless performance actually is.

Quoting from the abstract:


Although it is tempting to assume that all radios have circular range, have perfect coverage in that range, and travel on a two-dimensional plane, most researchers are increasingly aware of the need to represent more realistic features, including hills, obstacles, link asymmetries, and unpredictable fading. Although many have noted the complexity of real radio propagation, and some have quantified the effect of overly simple assumptions on the simulation of ad~hoc network protocols, we provide a comprehensive review of six assumptions that are still part of many ad~hoc network simulation studies. In particular, we use an extensive set of measurements from a large outdoor routing experiment to demonstrate the weakness of these assumptions, and show how these assumptions cause simulation results to differ significantly from experimental results.

Keep Reading

Most Popular

Large language models can do jaw-dropping things. But nobody knows exactly why.

And that's a problem. Figuring it out is one of the biggest scientific puzzles of our time and a crucial step towards controlling more powerful future models.

OpenAI teases an amazing new generative video model called Sora

The firm is sharing Sora with a small group of safety testers but the rest of us will have to wait to learn more.

The problem with plug-in hybrids? Their drivers.

Plug-in hybrids are often sold as a transition to EVs, but new data from Europe shows we’re still underestimating the emissions they produce.

Google DeepMind’s new generative model makes Super Mario–like games from scratch

Genie learns how to control games by watching hours and hours of video. It could help train next-gen robots too.

Stay connected

Illustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at customer-service@technologyreview.com with a list of newsletters you’d like to receive.