Counting in Population Protocols on Graphs

📅 2026-08-18
📈 Citations: 0
Influential: 0
📄 PDF
🤖 AI Summary
研究了图上群体协议中计数问题,通过随机调度和状态转换方法,在无需节点标识符的情况下实现了近似计数,使用了约O(n)状态并在特定次数交互后稳定。
📝 Abstract
We consider the problem of counting the number of agents in a population protocol where the agents are connected by an underlying graph $G=(V,E)$ with $|V|=n$ nodes. In each step, a random scheduler selects an edge uniformly at random, and the incident nodes make a state transition. As per standard assumptions, agents are identical and anonymous, that is, have no identifiers. To break symmetry, in each interaction one of the agents is declared as the initiator uniformly at random. Our size counting protocol uses $\tilde O(n)$ states and stabilizes in $O( B(G) \cdot \log^2(n) + L(G) \cdot \log(n))$ interactions with high probability, where $B(G)$ is the broadcast time and $L(G)$ is the load balancing time. Our protocol is based on novel protocols for sampling independent random bits (given that the scheduler determines an initiator and responder) and approximating $\log n$ up to an additive error of $O(\log \log n)$ with high probability. The latter uses $O(poly\log(n))$ states and $O(B(G)\cdot\log^2 n)$ interactions. Both results may be of independent interest. The main protocol for exact counting requires the presence of a unique leader, the other two do not. None of the protocols requires any knowledge about the graph $G$. We conclude with impossibility results for terminating uniform population protocols that compute graph-size properties (like counting nodes or determining parity) with and without a leader.
Problem

Research questions and friction points this paper is trying to address.

Population Protocols
Graphs
Counting
Agents
Innovation

Methods, ideas, or system contributions that make the work stand out.

population protocols
counting
graph theory
random bits generation
approximation of logarithm
🔎 Similar Papers
No similar papers found.
💼 Related Jobs
No related jobs found.
P
Petra Berenbrink
University of Hamburg, Germany
Robert Elsässer
Robert Elsässer
University of Salzburg
Algorithms
T
Tom Friedetzky
Durham University, U.K.
T
Thorsten Götte
University of Hamburg, Germany
L
Lukas Hintze
University of Hamburg, Germany
D
Dominik Kaaser
Hamburg University of Technology, Germany