A Linear Network Code Construction for General Integer Connections Based on the Constraint Satisfaction Problem
Name
1502.06321.pdf
Description
Submitted version
Size
1.34 MB
Format
Adobe PDF
Checksum (MD5)
88ff0c2d597030115e7a778887a02ac3
Author(s)
Cui, Ying
Medard, Muriel
Yeh, Edmund
Leith, Douglas
Lai, Fan
Duffy, Ken R
Date Issued
2017
Journal
Networking, IEEE-ACM Transactions on
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Version
Original manuscript
Abstract
© 2017 IEEE. The problem of finding network codes for general connections is inherently difficult in capacity constrained networks. Resource minimization for general connections with network coding is further complicated. Existing methods for identifying solutions mainly rely on highly restricted classes of network codes, and are almost all centralized. In this paper, we introduce linear network mixing coefficients for code constructions of general connections that generalize random linear network coding for multicast connections. For such code constructions, we pose the problem of cost minimization for the subgraph involved in the coding solution and relate this minimization to a path-based constraint satisfaction problem CSP and an edge-based CSP. While CSPs are NP-complete in general, we present a path-based probabilistic distributed algorithm and an edge-based probabilistic distributed algorithm with almost sure convergence in finite time by applying communication free learning. Our approach allows fairly general coding across flows, guarantees no greater cost than routing, and shows a possible distributed implementation. Numerical results illustrate the performance improvement of our approach over existing methods.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/TNET.2017.2746755
