Minimizing the Number of Opinions for Fault-Tolerant Distributed Decision Using Well-Quasi Orderings
Résumé
The notion of deciding a \emph{distributed language} $\m{L}$
is of growing interest in various distributed computing settings.
Each process $p_i$ is given an input value $x_i$, and the processes should
collectively decide
whether their set of input values $x=(x_i)_i$ is a valid state of the system w.r.t.\
to some specification, i.e., if $x\in\m{L}$.
In \emph{non-deterministic} distributed decision each process $p_i$ gets a local
certificate $c_i$ in addition to its input $x_i$. If the input $x\in\m{L}$
then there exists a certificate $c=(c_i)_i$ such that the processes collectively
accept $x$, and if $x\not\in\m{L}$, then for every $c$, the processes
should collectively reject $x$. The collective decision is expressed
by the set of \emph{opinions} emitted by the processes, and one aims
at minimizing the number of possible opinions emitted by each process.
In this paper we study non-deterministic distributed decision
in asynchronous systems where processes may crash.
In this setting, it is known that the number
of opinions needed to deterministically decide a language can grow with
$n$, the number of processes in the system.
We prove that every distributed language $\m{L}$ can be
non-deterministically decided using only three opinions, with certificates of
size $\lceil\log \alpha(n)\rceil+1$ bits, where $\alpha$
grows at least as slowly as the inverse of
the Ackerman function.
The result is optimal, as we show that there are distributed
languages that cannot be decided using just two opinions, even with
arbitrarily large certificates.
To prove our upper bound, we introduce the notion of \emph{distributed
encoding of the integers}, that provides an explicit construction of
a long \emph{bad sequence} in the \emph{well-quasi-ordering}
$(\{0,1\}^*,\leq_*)$ controlled by the successor function.
Thus, we provide a new class of applications for well-quasi-orderings
that lies outside logic and complexity theory. For the lower bound we
use combinatorial topology techniques.