Avoidance, adjacency, and association in distributed systems design

Abstract

Patterns of avoidance, adjacency, and association in complex systems design emerge from the system’s underlying logical architecture (functional relationships among components) and physical architecture (component physical properties and spatial location). Understanding the physical–logical architecture interplay that gives rise to patterns of arrangement requires a quantitative approach that bridges both descriptions. Here, we show that statistical physics reveals patterns of avoidance, adjacency, and association across sets of complex, distributed system design solutions. Using an example arrangement problem and tensor network methods, we identify several phenomena in complex systems design, including placement symmetry breaking, propagating correlation, and emergent localization. Our approach generalizes straightforwardly to a broad range of complex systems design settings where it can provide a platform for investigating basic design phenomena.

Document Details

Document Type
Pub Defense Publication
Publication Date
Apr 08, 2021
Source ID
10.1088/2632-072x/abe27f

Entities

People

  • Andrei A Klishin
  • David J. Singer
  • Greg van Anders

Organizations

  • Natural Sciences and Engineering Research Council
  • Office of Naval Research

Tags

Readers

  • Computer Networking
  • Neural Network Machine Learning.
  • Systems Analysis and Design