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

The problem of finding network codes for general connections is inherentlydifficult in capacity constrained networks. Resource minimization for generalconnections with network coding is further complicated. Existing methods foridentifying solutions mainly rely on highly restricted classes of networkcodes, and are almost all centralized. In this paper, we introduce linearnetwork mixing coefficients for code constructions of general connections thatgeneralize random linear network coding (RLNC) for multicast connections. Forsuch code constructions, we pose the problem of cost minimization for thesubgraph involved in the coding solution and relate this minimization to apath-based Constraint Satisfaction Problem (CSP) and an edge-based CSP. WhileCSPs are NP-complete in general, we present a path-based probabilisticdistributed algorithm and an edge-based probabilistic distributed algorithmwith almost sure convergence in finite time by applying Communication FreeLearning (CFL). Our approach allows fairly general coding across flows,guarantees no greater cost than routing, and shows a possible distributedimplementation. Numerical results illustrate the performance improvement of ourapproach over existing methods.

A Linear Network Code Construction for General Integer Connections Based on the Constraint Satisfaction Problem