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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Geographically locating an IP address is of interest for many purposes. There are two major ways to obtain the location of an IP address: querying commercial databases or conducting latency measurements. For structural Internet nodes, such as routers, commercial databases are limited by low accuracy, while current measurement-based approaches overwhelm users with setup overhead and scalability issues. In this work we present our system HLOC, aiming to combine the ease of database use with the accuracy of latency measurements. We evaluate HLOC on a comprehensive router data set of 1.4M IPv4 and 183k IPv6 routers. HLOC first extracts location hints from rDNS names, and then conducts multi-tier latency measurements. Configuration complexity is minimized by using publicly available large-scale measurement frameworks such as RIPE Atlas. Using this measurement, we can confirm or disprove the location hints found in domain names. We publicly release HLOC's ready-to-use source code, enabling researchers to easily increase geolocation accuracy with minimum overhead.

HLOC: Hints-based geolocation leveraging multiple measurement frameworks