A Quorum Sensing Inspired Algorithm for Dynamic Clustering

TL;DR

This paper introduces a novel clustering algorithm inspired by quorum sensing, capable of handling static and dynamic data, with proven stability and convergence, demonstrated on diverse synthetic and real-world applications.

Contribution

The paper presents a new quorum sensing-inspired clustering algorithm that adapts to time-varying data and demonstrates stability, convergence, and versatility across multiple applications.

Findings

Effective on synthetic and real datasets

Handles static and dynamic data

Shows promising results in diverse applications

Abstract

Quorum sensing is a decentralized biological process, through which a community of cells with no global awareness coordinate their functional behaviors based solely on cell-medium interactions and local decisions. This paper draws inspirations from quorum sensing and colony competition to derive a new algorithm for data clustering. The algorithm treats each data as a single cell, and uses knowledge of local connectivity to cluster cells into multiple colonies simultaneously. It simulates auto-inducers secretion in quorum sensing to tune the influence radius for each cell. At the same time, sparsely distributed core cells spread their influences to form colonies, and interactions between colonies eventually determine each cell's identity. The algorithm has the flexibility to analyze not only static but also time-varying data, which surpasses the capacity of many existing algorithms. Its stability and convergence properties are established. The algorithm is tested on several applications, including both synthetic and real benchmarks data sets, alleles clustering, community detection, image segmentation. In particular, the algorithm's distinctive capability to deal with time-varying data allows us to experiment it on novel applications such as robotic swarms grouping and switching model identification. We believe that the algorithm's promising performance would stimulate many more exciting applications.