No abstract

The cooperative data exchange problem is studied for the fully connected network. In this problem, each node initially only possesses a subset of the K packets making up the file. Nodes make broadcast transmissions that are received by all other nodes. The goal is for each node to recover the full file. In this paper, we present a polynomial-time deterministic algorithm to compute the optimal (i.e., minimal) number of required broadcast transmissions and to determine the precise transmissions to be made by the nodes. A particular feature of our approach is that each of the K − d transmissions is a linear combination of exactly d + 1 packets, and we show how to optimally choose the value of d. We also show how the coefficients of these linear combinations can be chosen by leveraging a connection to Maximum Distance Separable (MDS) codes. Moreover, we show that our method can be used to solve cooperative data exchange problems with weighted cost as well as the so-called successive local omniscience problem.

We consider spherical codes attaining the Levenshtein upper bounds on the cardinality of codes with prescribed maximal inner product. We prove that the even Levenshtein bounds can be attained only by codes which are tight spherical designs. For every fixed n ≥ 5, there exist only a finite number of codes attaining the odd bounds. We derive different expressions for the distance distribution of a maximal code. As a by‐product, we obtain a result about its inner products. We describe the parameters of those codes meeting the third Levenshtein bound, which have a regular simplex as a derived code. Finally, we discuss a connection between the maximal codes attaining the third bound and strongly regular graphs. © 1999 John Wiley & Sons, Inc. J Combin Designs 7: 316–326, 1999