English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

This paper investigates the throughput capacity of a flow crossing amulti-hop wireless network, whose geometry is characterized by generalrandomness laws including Uniform, Poisson, Heavy-Tailed distributions for boththe nodes' densities and the number of hops. The key contribution is todemonstrate \textit{how} the \textit{per-flow throughput} depends on thedistribution of 1) the number of nodes $N_j$ inside hops' interference sets, 2)the number of hops $K$, and 3) the degree of spatial correlations. Therandomness in both $N_j$'s and $K$ is advantageous, i.e., it can yield largerscalings (as large as $\Theta(n)$) than in non-random settings. An interestingconsequence is that the per-flow capacity can exhibit the opposite behavior tothe network capacity, which was shown to suffer from a logarithmic decrease inthe presence of randomness. In turn, spatial correlations along the end-to-endpath are detrimental by a logarithmic term.

On the Catalyzing Effect of Randomness on the Per-Flow Throughput in Wireless Networks