Loosely-stabilizing leader election in a population protocol model

Yuichi Sudo, Junya Nakamura, Yukiko Yamauchi, Fukuhito Ooshita, Hirotsugu Kakugawa, Toshimitsu Masuzawa

Research output: Contribution to journalArticlepeer-review

32 Citations (Scopus)


A self-stabilizing protocol guarantees that starting from any arbitrary initial configuration, a system eventually comes to satisfy its specification and keeps the specification forever. Although self-stabilizing protocols show excellent fault-tolerance against any transient faults (e.g. memory crash), designing self-stabilizing protocols is difficult and, what is worse, might be impossible due to the severe requirements. To circumvent the difficulty and impossibility, we introduce a novel notion of loose-stabilization, that relaxes the closure requirement of self-stabilization; starting from any arbitrary configuration, a system comes to satisfy its specification in a relatively short time, and it keeps the specification not forever but for a long time. To show the effectiveness and feasibility of this new concept, we present a probabilistic loosely-stabilizing leader election protocol in the Probabilistic Population Protocol (PPP) model of complete networks. Starting from any configuration, the protocol elects a unique leader within O(nNlogn) expected steps and keeps the unique leader for Ω(N eN) expected steps, where n is the network size (not known to the protocol) and N is a known upper bound of n. This result proves that introduction of the loose-stabilization circumvents the already-known impossibility result; the self-stabilizing leader election problem in the PPP model of complete networks cannot be solved without the knowledge of the exact network size.

Original languageEnglish
Pages (from-to)100-112
Number of pages13
JournalTheoretical Computer Science
Publication statusPublished - Jul 27 2012

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


Dive into the research topics of 'Loosely-stabilizing leader election in a population protocol model'. Together they form a unique fingerprint.

Cite this