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

Geoffrey Hinton tells us why he’s now scared of the tech he helped build

“I have suddenly switched my views on whether these things are going to be more intelligent than us.”

ChatGPT is going to change education, not destroy it

The narrative around cheating students doesn’t tell the whole story. Meet the teachers who think generative AI could actually make learning better.

Meet the people who use Notion to plan their whole lives

The workplace tool’s appeal extends far beyond organizing work projects. Many users find it’s just as useful for managing their free time.

Learning to code isn’t enough

Historically, learn-to-code efforts have provided opportunities for the few, but new efforts are aiming to be inclusive.

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.