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

To accommodate low latency and computation-intensive services, such as theInternet-of-Things (IoT), 5G networks are expected to have cloud and edgecomputing capabilities. To this end, we consider a generic network setup wheredevices, performing analytics-related tasks, can partially process a task andoffload its remainder to base stations, which can then reroute it to cloudand/or to edge servers. To account for the potentially unpredictable trafficdemands and edge network dynamics, we formulate the resource allocation as anonline convex optimization problem with service violation constraints and allowlimited communication between neighboring nodes. To address the problem, wepropose an online distributed (across the nodes) primal-dual algorithm andprove that it achieves sublinear regret and violation; in fact, the achievedbound is of the same order as the best known centralized alternative. Ourresults are further supported using the publicly available Milano dataset.

Distributed no-regret edge resource allocation with limited communication