An overview of the firing squad synchronization problem
Proceedings on LITP spring school on Theoretical Computer Science on Automata networks
Self-stabilizing symmetry breaking in constant-space (extended abstract)
STOC '92 Proceedings of the twenty-fourth annual ACM symposium on Theory of computing
Distributed Algorithms for Unidirectional Networks
SIAM Journal on Computing
Memory-efficient and self-stabilizing network RESET (extended abstract)
PODC '94 Proceedings of the thirteenth annual ACM symposium on Principles of distributed computing
Faster computation on directed networks of automata
Proceedings of the fourteenth annual ACM symposium on Principles of distributed computing
Computing with snakes in directed networks of automata
Journal of Algorithms
Local and global properties in networks of processors (Extended Abstract)
STOC '80 Proceedings of the twelfth annual ACM symposium on Theory of computing
Computation: finite and infinite machines
Computation: finite and infinite machines
Sequential Machines: Selected Papers
Sequential Machines: Selected Papers
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We consider several problems relating to strongly-connected directed networks of identical finite-state processors that work synchronously in discrete time steps. The conceptually simplest of these problems is the Wake Up and Report Problem; this is the problem of having a unique "root" processor send a signal to all other processors in the network and then enter a special "done" state only when all other processors have received the signal. The most difficult of the problems we consider is the classic Firing Squad Synchronization Problem; this is the much-studied problem of achieving macro-synchrorization in a network given micro-synchronization. We show via a complex algorithmic application of the "snake" data stucture first introduced in Even, Litman, and Winkler[6] that these two problems in particular are asymptotically time-equivalent up to a constant factor. This result leads immediately to the inclusion of several other related problems into this new asymptotic time-class.