Improved Leader Election for Self-Organizing Programmable Matter
Year: 2017
Type: preprint
Abstract: We consider programmable matter that consists of computationally limited devices (called particles) that are able to self-organize in order to achieve some collective goal without the need for central control or external intervention. We use the geometric amoebot model to describe such self-organizing particle systems, which defines how particles can actively move and communicate with one another. In this paper, we present an efficient local-control algorithm which solves the leader election problem in O(n) asynchronous rounds with high probability, where n is the number of particles in the system. Our algorithm relies only on local information --- particles do not have unique identifiers, any knowledge of n, or any sort of global coordinate system --- and requires only constant memory per particle.
Source: arXiv (Cornell University)
Institutions: Arizona State University, Paderborn University
Language: English
Subfield: Mechanical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2952567239