Fast and Compact Distributed Verification and Self-Stabilization of a DFS Tree

We present algorithms for distributed verification and silent-stabilization of a DFS(Depth First Search) spanning tree of a connected network. Computing and maintaining such a DFS tree is an important task, e.g., for constructing efficient routing schemes. Our algorithm improves upon previous work in various ways. Comparable previous work has space and time complexities of $O(n\log \Delta)$ bits per node and $O(nD)$ respectively, where $\Delta$ is the highest degree of a node, $n$ is the number of nodes and $D$ is the diameter of the network. In contrast, our algorithm has a space complexity of $O(\log n)$ bits per node, which is optimal for silent-stabilizing spanning trees and runs in $O(n)$ time. In addition, our solution is modular since it utilizes the distributed verification algorithm as an independent subtask of the overall solution. It is possible to use the verification algorithm as a stand alone task or as a subtask in another algorithm. To demonstrate the simplicity of constructing efficient DFS algorithms using the modular approach, We also present a (non-sielnt) self-stabilizing DFS token circulation algorithm for general networks based on our silent-stabilizing DFS tree. The complexities of this token circulation algorithm are comparable to the known ones

Fast and compact self-stabilizing verification, computation, and fault detection of an MST

This paper demonstrates the usefulness of distributed local verification of proofs, as a tool for the design of self-stabilizing algorithms.In particular, it introduces a somewhat generalized notion of distributed local proofs, and utilizes it for improving the time complexity significantly, while maintaining space optimality. As a result, we show that optimizing the memory size carries at most a small cost in terms of time, in the context of Minimum Spanning Tree (MST). That is, we present algorithms that are both time and space efficient for both constructing an MST and for verifying it.This involves several parts that may be considered contributions in themselves.First, we generalize the notion of local proofs, trading off the time complexity for memory efficiency. This adds a dimension to the study of distributed local proofs, which has been gaining attention recently. Specifically, we design a (self-stabilizing) proof labeling scheme which is memory optimal (i.e., $O(\log n)$ bits per node), and whose time complexity is $O(\log ^2 n)$ in synchronous networks, or $O(\Delta \log ^3 n)$ time in asynchronous ones, where $\Delta$ is the maximum degree of nodes. This answers an open problem posed by Awerbuch and Varghese (FOCS 1991). We also show that $\Omega(\log n)$ time is necessary, even in synchronous networks. Another property is that if $f$ faults occurred, then, within the requireddetection time above, they are detected by some node in the $O(f\log n)$ locality of each of the faults.Second, we show how to enhance a known transformer that makes input/output algorithms self-stabilizing. It now takes as input an efficient construction algorithm and an efficient self-stabilizing proof labeling scheme, and produces an efficient self-stabilizing algorithm. When used for MST, the transformer produces a memory optimal self-stabilizing algorithm, whose time complexity, namely, $O(n)$, is significantly better even than that of previous algorithms. (The time complexity of previous MST algorithms that used $\Omega(\log^2 n)$ memory bits per node was $O(n^2)$, and the time for optimal space algorithms was $O(n|E|)$.) Inherited from our proof labelling scheme, our self-stabilising MST construction algorithm also has the following two properties: (1) if faults occur after the construction ended, then they are detected by some nodes within $O(\log ^2 n)$ time in synchronous networks, or within $O(\Delta \log ^3 n)$ time in asynchronous ones, and (2) if $f$ faults occurred, then, within the required detection time above, they are detected within the $O(f\log n)$ locality of each of the faults. We also show how to improve the above two properties, at the expense of some increase in the memory

On the Limits and Practice of Automatically Designing Self-Stabilization

A protocol is said to be self-stabilizing when the distributed system executing it is guaranteed to recover from any fault that does not cause permanent damage. Designing such protocols is hard since they must recover from all possible states, therefore we investigate how feasible it is to synthesize them automatically. We show that synthesizing stabilization on a fixed topology is NP-complete in the number of system states. When a solution is found, we further show that verifying its correctness on a general topology (with any number of processes) is undecidable, even for very simple unidirectional rings. Despite these negative results, we develop an algorithm to synthesize a self-stabilizing protocol given its desired topology, legitimate states, and behavior. By analogy to shadow puppetry, where a puppeteer may design a complex puppet to cast a desired shadow, a protocol may need to be designed in a complex way that does not even resemble its specification. Our shadow/puppet synthesis algorithm addresses this concern and, using a complete backtracking search, has automatically designed 4 new self-stabilizing protocols with minimal process space requirements: 2-state maximal matching on bidirectional rings, 5-state token passing on unidirectional rings, 3-state token passing on bidirectional chains, and 4-state orientation on daisy chains

Petrinetze zum Entwurf selbststabilisierender Algorithmen

Edsger W. Dijkstra prägte im Jahr 1974 den Begriff Selbststabilisierung (self-stabilization) in der Informatik. Ein System ist selbststabilisierend, wenn es von jedem denkbaren Zustand aus nach einer endlichen Anzahl von Aktionen ein stabiles Verhalten erreicht. Im Mittelpunkt dieser Arbeit steht der Entwurf selbststabilisierender Algorithmen. Wir stellen eine Petrinetz-basierte Methode zum Entwurf selbststabilisierender Algorithmen vor. Wir validieren unsere Methode an mehreren Fallstudien: Ausgehend von algorithmischen Ideen existierender Algorithmen beschreiben wir jeweils die die schrittweise Entwicklung eines neuen Algorithmus. Dazu gehört ein neuer randomisierter selbststabilisierender Algorithmus zur Leader Election in einem Ring von Prozessoren. Dieser Algorithmus ist abgeleitet aus einem publizierten Algorithmus, von dem wir hier erstmals zeigen, daß er fehlerhaft arbeitet. Wir weisen die Speicherminimalität unseres Algorithmus nach. Ein weiteres Ergebnis ist der erste Algorithmus, der ohne Time-Out-Aktionen selbststabilisierenden Tokenaustausch in asynchronen Systemen realisiert. Petrinetze bilden einen einheitlichen formalen Rahmen für die Modellierung und Verifikation dieser Algorithmen.In 1974, Edsger W. Dijkstra suggested the notion of self-stabilization. A system is self-stabilizing if regardless of the initial state it eventually reaches a stable behaviour. This thesis focuses on the design of self-stabilizing algorithms. We introduce a new Petri net based method for the design of self-stabilizing algorithms. We validate our method on several case studies. In each of the case studies, our stepwise design starts from an algorithmic idea and leads to a new self-stabilizing algorithm. One of these algorithms is a new randomized self-stabilizing algorithm for leader election in a ring of processors. This algorithm is derived from a published algorithm which we show to be incorrect. We prove that our algorithm is space-minimal. A further result is the first algorithm for token-passing in a asynchronous environment which works without time-out actions. Petri nets form a unique framework for modelling and verification of these algorithms