Ncentered

Ncentered is an open-source software library and research framework for network-centered analytics and optimization. It provides a modular set of data structures and algorithms for modeling graphs and solving center-based optimization problems under the n-centered paradigm, where a selected set of center nodes provides coverage for the remainder of the network.

Origin and development: Ncentered was introduced by researchers from the Institute of Computing Sciences and the University of Northbridge in 2018. It has since undergone several major releases and is maintained by a community of contributors. The project emphasizes interoperability, extensibility, and a clean API for researchers and practitioners.

Key components: The library includes graph representations (directed/undirected, weighted/unweighted), a suite of centrality measures (degree, betweenness, closeness, eigenvector), and tools for center-based analysis. It implements n-centered clustering and related optimization solvers, along with data I/O adapters for common formats and visualization hooks. It supports multi-threaded CPU execution and optional GPU acceleration via a CUDA backend.

N-centered problem: In the n-centered framework, one selects a set of centers such that every node lies within a specified distance measure to a nearest center, with objectives such as minimizing the maximum distance (the classic n-center problem) or minimizing total assignment cost. The library provides exact and heuristic algorithms, including greedy and local-search approaches, with configurable distance metrics.

Applications and reception: Ncentered is used in academic research on network design, facility placement, logistics, and social network analysis. It is noted for its modular architecture and clear API, though performance on very large graphs can require hardware acceleration or problem-specific tuning.

See also: k-center problem; facility location; centrality measures; graph theory.