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Article
Sum-Networks from Incidence Structures: Construction and Capacity Analysis
IEEE Transactions on Information Theory
  • Ardhendu S. Tripathy, Missouri University of Science and Technology
  • Aditya Ramamoorthy
Abstract

A sum-network is an instance of a function computation problem over a directed acyclic network, in which each terminal node wants to compute the sum over a finite field of the information observed at all the source nodes. Many characteristics of the well-studied multiple unicast network communication problem also hold for sum-networks, due to a known reduction between the two problems. In this paper, we describe an algorithm to construct families of sum-network instances using incidence structures. The computation capacity of several of these sum-network families is evaluated. Unlike the coding capacity of a multiple unicast problem, the computation capacity of sum-networks depends on the characteristic of the finite field over which the sum is computed. This dependence is very strong; we show examples of sum-networks that have a rate-1 solution over one characteristic but a rate close to zero over a different characteristic. In addition, a sum-network can have arbitrarily different computation capacities for different alphabets.

Department(s)
Computer Science
Comments

This work was supported by the National Science Foundation under Grant CCF-1149860, Grant CCF-1320416, Grant CCF-1718470, and Grant DMS-1120597.

This paper was presented in part at the 2014 52nd Allerton Conference on Communication, Control, and Computing and the 2015 IEEE International Symposium on Information Theory.

Keywords and Phrases
  • Characteristic,
  • Function Computation,
  • Incidence Structures,
  • Network Coding,
  • Sum-Networks
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2018 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
5-1-2018
Publication Date
01 May 2018
Disciplines
Citation Information
Ardhendu S. Tripathy and Aditya Ramamoorthy. "Sum-Networks from Incidence Structures: Construction and Capacity Analysis" IEEE Transactions on Information Theory Vol. 64 Iss. 5 (2018) p. 3461 - 3480 ISSN: 0018-9448; 1557-9654
Available at: http://works.bepress.com/ardhendu-s-tripathy/15/