12th International Symposium on Stabilization, Safety, and Security of Distributed Systems (SSS 2010)
New York City, USA
September 20-22, 2010
Davis Auditorium, Columbia University
Self-Stabilization Track
Franck Petit, LIP6, UPMC Paris 6, France
Philippas Tsigas, Chalmers University, Sweden
Track Program Committee:
James Aspnes, Yale University, CT, USA
Borzoo Bonakdarpour, Verimag Laboratory, France
Alain Cournier, MIS, University de Picardie Jules Verne, France
Ajoy Datta, University of Nevada Las Vegas, USA
Murat Demirbas, Buffalo University, NY, USA
Stéphane Devismes,Verimag, University Grenoble 1, France
Ted Herman, University of Iowa, USA
Amos Israeli, Netanya Academic College, Israel
Colette Johnen, LaBRI, Université Bordeaux, France
Toshimisu Masuzawa, Osaka University , Japan
Elad Michael Schiller, Chalmers university , Sweden
Sébastien Tixeuil, LIP6, UPMC Paris 6, France
Volker Turau, Hamburg Universtity of Technology, Germany
Koichi Wada, Nagoya Institute of Technology , Japan
Maurice Tchuente, ICSU, Africa
Stabilization is the cornerstone of the long series of SSS conferences
initiated in 1989. (Self-)Stabilization is the property of an
autonomous process to obtain a correct behavior in finite time,
regardless of the initial state it was in. In other words,
stabilization enables (distributed) systems to automatically recover
from unexpected behaviors with respect to an expected behavior.
Depending on the system characteristics, such unexpected behaviors can
be topological changes, transient faults affecting the process state
or the channel content, perturbations of radio waves, etc. Recently,
the range of distributed systems, where stabilization offers a
promising approach, has largely expanded, e.g., peer-to-peer networks,
grid systems, large-scale wireless sensor networks, mobile ad hoc
networks, mobile robot networks, nanorobotic, VLSI, etc.
Topics include, but are not limited to:
stabilization in distributed and networked systems.
stabilizing and emergent properties in dynamic networks.
stabilization in the context of VLSI.
stabilizing properties in self-managed, self-assembling, autonomic,
or adaptive systems.
stabilizing properties in self-optimizing and self-protecting systems.
performance and complexity analysis of self-stabilization.
impossibility results and lower bounds for stabilization.
self-stabilization in decentralized and real-time control applications.
self-healing applications of self-stabilization.
self-stabilization in agent-based systems.
stabilization of code and data.
applications of stabilization, experience reports.
stochastic, physical, and biological models to analyze stabilization properties.
