Distinct Difference Configurations: Multihop Paths and Key Predistribution in Sensor Networks

TL;DR

This paper studies distinct difference configurations in sensor networks, focusing on their k-hop coverage and constructing configurations that maximize secure connectivity and path density.

Contribution

It introduces bounds for k-hop coverage, connects with B_h sequences, and constructs configurations for optimal local secure connectivity.

Findings

Provided bounds for k-hop coverage of configurations.

Connected configurations with B_h sequences for maximal coverage.

Constructed configurations enabling small vector sums for secure connectivity.

Abstract

A distinct difference configuration is a set of points in $\mathbb{Z}^2$ with the property that the vectors (\emph{difference vectors}) connecting any two of the points are all distinct. Many specific examples of these configurations have been previously studied: the class of distinct difference configurations includes both Costas arrays and sonar sequences, for example. Motivated by an application of these structures in key predistribution for wireless sensor networks, we define the $k$-hop coverage of a distinct difference configuration to be the number of distinct vectors that can be expressed as the sum of $k$ or fewer difference vectors. This is an important parameter when distinct difference configurations are used in the wireless sensor application, as this parameter describes the density of nodes that can be reached by a short secure path in the network. We provide upper and lower bounds for the $k$-hop coverage of a distinct difference configuration with $m$ points, and exploit a connection with $B_{h}$ sequences to construct configurations with maximal $k$-hop coverage. We also construct distinct difference configurations that enable all small vectors to be expressed as the sum of two of the difference vectors of the configuration, an important task for local secure connectivity in the application.