Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data.

Hsueh-Ping Chen

dblp:67/5733 · DBLP profile ↗
← Back
4ranked-venue papers
2as first author
2since 2021 · last 2026
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 4 · 2 first-author · 2 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
3 papers
Distributed computing theory · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Distributed computing theory
self-stabilization
1.332021
Time-Optimal Self-Stabilizing Leader Election in Population Protocols · PODC 2021
Self-Stabilizing Leader Election in Regular Graphs · PODC 2020
Self-Stabilizing Leader Election · PODC 2019
Distributed computing theory › self-stabilization
self-stabilizing leader election
0.822020
Self-Stabilizing Leader Election in Regular Graphs · PODC 2020
Self-Stabilizing Leader Election · PODC 2019
Distributed computing theory
population protocols
0.732021
Time-Optimal Self-Stabilizing Leader Election in Population Protocols · PODC 2021
Self-Stabilizing Leader Election in Regular Graphs · PODC 2020
Self-Stabilizing Leader Election · PODC 2019
Distributed computing theory
leader election
0.512021
Time-Optimal Self-Stabilizing Leader Election in Population Protocols · PODC 2021
YearPublicationVenuePosition
2026 Time-optimal self-stabilizing leader election in population protocols
abstract
Abstract We consider the standard population protocol model, where ( a priori ) indistinguishable and anonymous agents interact in pairs according to uniformly random scheduling. The self-stabilizing leader election problem requires the protocol to converge on a single leader agent from any possible initial configuration. We initiate the study of time complexity of population protocols solving this problem in its original setting: with probability 1, in a complete communication graph. The only previously known protocol by Cai, Izumi, and Wada [Theor. Comput. Syst. 50] runs in expected parallel time $$\Theta (n^2)$$ Θ ( n 2 ) and has the optimal number of n states in a population of n agents. The existing protocol has the additional property that it becomes silent, i.e., the agents’ states eventually stop changing. Observing that any silent protocol solving self-stabilizing leader election requires $$\Omega (n)$$ Ω ( n ) expected parallel time, we introduce a silent protocol that uses optimal O ( n ) parallel time and states. Without any silence constraints, we show that it is possible to solve self-stabilizing leader election in asymptotically optimal expected parallel time of $$O(\log n)$$ O ( log n ) , but using at least exponential states (a quasipolynomial number of bits). All of our protocols (and also that of Cai et al.) work by solving the more difficult ranking problem: assigning agents the ranks $$1,\ldots ,n$$ 1 , … , n .
Janna Burman, Ho-Lin Chen, Hsueh-Ping Chen, David Doty, Thomas Nowak, Eric Severson
Distributed Comput.3
2021 Time-Optimal Self-Stabilizing Leader Election in Population Protocols
abstract
We consider the standard population protocol model, where (a priori) indistinguishable and anonymous agents interact in pairs according to uniformly random scheduling. The self-stabilizing leader election problem requires the protocol to converge on a single leader agent from any possible initial configuration. We initiate the study of time complexity of population protocols solving this problem in its original setting: with probability 1, in a complete communication graph. The only previously known protocol by Cai, Izumi, and Wada [Theor. Comput. Syst. 50] runs in expected parallel time Θ(n2) and has the optimal number of n states in a population of n agents. The existing protocol has the additional property that it becomes silent, i.e., the agents' states eventually stop changing.
Janna Burman, Ho-Lin Chen, Hsueh-Ping Chen, David Doty, Thomas Nowak 0001, Eric E. Severson, Chuan Xu 0002
PODC3
2020 Self-Stabilizing Leader Election in Regular Graphs
abstract
Population protocols [3] are used as a distributed model that captures the behavior of passively mobile agents. Leader election is one of the most well-studied problems in this model. In this paper, we focus on the self-stabilizing leader election (SSLE) problem proposed by Angluin et al. [5]. Previously, it is known that SSLE can be performed on arbitrary rings and tori with a constant number of states [11], but SSLE on complete graphs requires Ω(n) states [9].
Hsueh-Ping Chen, Ho-Lin Chen
PODC1
2019 Self-Stabilizing Leader Election
abstract
In this paper, we study the self-stabilizing leader election (SSLE) problem in population protocols. We construct a non-deterministic population protocol that can solve SSLE on directed rings of all sizes. Our algorithm uses a constant number of states and can be converted to a deterministic population protocol on undirected rings using previous techniques [8]. Furthermore, we extend our algorithm to perform SSLE on directed and undirected tori of arbitrary sizes.
Hsueh-Ping Chen, Ho-Lin Chen
PODC1