Fault-Tolerant Consensus in Unknown and Anonymous Networks

This paper investigates under which conditions information can be reliably shared and consensus can be solved in unknown and anonymous message-passing networks that suffer from crash-failures. We provide algorithms to emulate registers and solve consensus under different synchrony assumptions. For this, we introduce a novel pseudo leader-election approach which allows a leader-based consensus implementation without breaking symmetry

Distributed eventual leader election in the crash-recovery and general omission failure models.

102 p.Distributed applications are present in many aspects of everyday life. Banking, healthcare or transportation are examples of such applications. These applications are built on top of distributed systems. Roughly speaking, a distributed system is composed of a set of processes that collaborate among them to achieve a common goal. When building such systems, designers have to cope with several issues, such as different synchrony assumptions and failure occurrence. Distributed systems must ensure that the delivered service is trustworthy.Agreement problems compose a fundamental class of problems in distributed systems. All agreement problems follow the same pattern: all processes must agree on some common decision. Most of the agreement problems can be considered as a particular instance of the Consensus problem. Hence, they can be solved by reduction to consensus. However, a fundamental impossibility result, namely (FLP), states that in an asynchronous distributed system it is impossible to achieve consensus deterministically when at least one process may fail. A way to circumvent this obstacle is by using unreliable failure detectors. A failure detector allows to encapsulate synchrony assumptions of the system, providing (possibly incorrect) information about process failures. A particular failure detector, called Omega, has been shown to be the weakest failure detector for solving consensus with a majority of correct processes. Informally, Omega lies on providing an eventual leader election mechanism

Implementing the weakest failure detector for solving consensus

The concept of unreliable failure detector was introduced by Chandra and Toueg as a mechanism that provides information about process failures. This mechanism has been used to solve several agreement problems, such as the consensus problem. In this paper, algorithms that implement failure detectors in partially synchronous systems are presented. First two simple algorithms of the weakest class to solve the consensus problem, namely the Eventually Strong class (⋄S), are presented. While the first algorithm is wait-free, the second algorithm is f-resilient, where f is a known upper bound on the number of faulty processes. Both algorithms guarantee that, eventually, all the correct processes agree permanently on a common correct process, i.e. they also implement a failure detector of the class Omega (Ω). They are also shown to be optimal in terms of the number of communication links used forever. Additionally, a wait-free algorithm that implements a failure detector of the Eventually Perfect class (⋄P) is presented. This algorithm is shown to be optimal in terms of the number of bidirectional links used forever

Contributions on agreement in dynamic distributed systems

139 p.This Ph.D. thesis studies the agreement problem in dynamic distributed systems by integrating both the classical fault-tolerance perspective and the more recent formalism based on evolving graphs. First, we developed a common framework that allows to analyze and compare models of dynamic distributed systems for eventual leader election. The framework extends a previous proposal by Baldoni et al. by including new dimensions and levels of dynamicity. Also, we extend the Time-Varying Graph (TVG) formalism by introducing the necessary timeliness assumptions and the minimal conditions to solve agreement problems. We provide a hierarchy of time-bounded, TVG-based, connectivity classes with increasingly stronger assumptions and specify an implementation of Terminating Reliable Broadcast for each class. Then we define an Omega failure detector, W, for the eventual leader election in dynamic distributed systems, together with a system model, , which is compatible with the timebounded TVG classes. We implement an algorithm that satisfy the properties of W in M. According to our common framework, M results to be weaker than the previous proposed dynamic distributed system models for eventual leader election. Additionally we use simulations to illustrate this fact and show that our leader election algorithm tolerates more general (i.e., dynamic) behaviors, and hence it is of application in a wider range of practical scenarios at the cost of a moderate overhead on stabilization times

The Failure Detector Abstraction

This paper surveys the failure detector concept through two dimensions. First we study failure detectors as building blocks to simplify the design of reliable distributed algorithms. More specifically, we illustrate how failure detectors can factor out timing assumptions to detect failures in distributed agreement algorithms. Second, we study failure detectors as computability benchmarks. That is, we survey the weakest failure detector question and illustrate how failure detectors can be used to classify problems. We also highlights some limitations of the failure detector abstraction along each of the dimensions

A Prescription for Partial Synchrony

Algorithms in message-passing distributed systems often require partial synchrony to tolerate crash failures. Informally, partial synchrony refers to systems where timing bounds on communication and computation may exist, but the knowledge of such bounds is limited. Traditionally, the foundation for the theory of partial synchrony has been real time: a time base measured by counting events external to the system, like the vibrations of Cesium atoms or piezoelectric crystals. Unfortunately, algorithms that are correct relative to many real-time based models of partial synchrony may not behave correctly in empirical distributed systems. For example, a set of popular theoretical models, which we call M_*, assume (eventual) upper bounds on message delay and relative process speeds, regardless of message size and absolute process speeds. Empirical systems with bounded channel capacity and bandwidth cannot realize such assumptions either natively, or through algorithmic constructions. Consequently, empirical deployment of the many M_*-based algorithms risks anomalous behavior. As a result, we argue that real time is the wrong basis for such a theory. Instead, the appropriate foundation for partial synchrony is fairness: a time base measured by counting events internal to the system, like the steps executed by the processes. By way of example, we redefine M_* models with fairness-based bounds and provide algorithmic techniques to implement fairness-based M_* models on a significant subset of the empirical systems. The proposed techniques use failure detectors — system services that provide hints about process crashes — as intermediaries that preserve the fairness constraints native to empirical systems. In effect, algorithms that are correct in M_* models are now proved correct in such empirical systems as well. Demonstrating our results requires solving three open problems. (1) We propose the first unified mathematical framework based on Timed I/O Automata to specify empirical systems, partially synchronous systems, and algorithms that execute within the aforementioned systems. (2) We show that crash tolerance capabilities of popular distributed systems can be denominated exclusively through fairness constraints. (3) We specify exemplar system models that identify the set of weakest system models to implement popular failure detectors

Perspectives on the CAP Theorem

Almost twelve years ago, in 2000, Eric Brewer introduced the idea that there is a fundamental trade-off between consistency, availability, and partition tolerance. This trade-off, which has become known as the CAP Theorem, has been widely discussed ever since. In this paper, we review the CAP Theorem and situate it within the broader context of distributed computing theory. We then discuss the practical implications of the CAP Theorem, and explore some general techniques for coping with the inherent trade-offs that it implies

The eventual leadership in dynamic mobile networking environments

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