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/

Zendy Plus

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

Zendy Tools

Zendy Open

We consider the problem of optimally compressing and caching data across acommunication network. Given the data generated at edge nodes and a routingpath, our goal is to determine the optimal data compression ratios and cachingdecisions across the network in order to minimize average latency, which can beshown to be equivalent to maximizing the compression and caching gain under anenergy consumption constraint. We show that this problem is NP-hard in generaland the hardness is caused by the caching decision subproblem, while thecompression sub-problem is polynomial-time solvable. We then propose anapproximation algorithm that achieves a $(1-1/e)$-approximation solution to theoptimum in strongly polynomial time. We show that our proposed algorithmachieve the near-optimal performance in synthetic-based evaluations. In thispaper, we consider a tree-structured network as an illustrative example, butour results easily extend to general network topology at the expense of morecomplicated notations.

Joint Data Compression and Caching: Approaching Optimality with Guarantees