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

We consider an IoT sensing network with multiple users, multiple energyharvesting sensors, and a wireless edge node acting as a gateway between theusers and sensors. The users request for updates about the value of physicalprocesses, each of which is measured by one sensor. The edge node has a cachestorage that stores the most recently received measurements from each sensor.Upon receiving a request, the edge node can either command the correspondingsensor to send a status update, or use the data in the cache. We aim to findthe best action of the edge node to minimize the average long-term cost whichtrade-offs between the age of information and energy consumption. We propose apractical reinforcement learning approach that finds an optimal policy withoutknowing the exact battery levels of the sensors.

Age-Aware Status Update Control for Energy Harvesting IoT Sensors via Reinforcement Learning