On the Space Complexity of Set Agreement

The $k$-set agreement problem is a generalization of the classical consensus problem in which processes are permitted to output up to $k$ different input values. In a system of $n$ processes, an $m$-obstruction-free solution to the problem requires termination only in executions where the number of processes taking steps is eventually bounded by $m$. This family of progress conditions generalizes wait-freedom ($m=n$) and obstruction-freedom ($m=1$). In this paper, we prove upper and lower bounds on the number of registers required to solve $m$-obstruction-free $k$-set agreement, considering both one-shot and repeated formulations. In particular, we show that repeated $k$ set agreement can be solved using $n+2m-k$ registers and establish a nearly matching lower bound of $n+m-k$

Of Choices, Failures and Asynchrony: The Many Faces of Set Agreement

Set agreement is a fundamental problem in distributed computing in which processes collectively choose a small subset of values from a larger set of proposals. The impossibility of fault-tolerant set agreement in asynchronous networks is one of the seminal results in distributed computing. In synchronous networks, too, the complexity of set agreement has been a significant research challenge that has now been resolved. Real systems, however, are neither purely synchronous nor purely asynchronous. Rather, they tend to alternate between periods of synchrony and periods of asynchrony. Nothing specific is known about the complexity of set agreement in such a "partially synchronous” setting. In this paper, we address this challenge, presenting the first (asymptotically) tight bound on the complexity of set agreement in such systems. We introduce a novel technique for simulating, in a fault-prone asynchronous shared memory, executions of an asynchronous and failure-prone message-passing system in which some fragments appear synchronous to some processes. We use this simulation technique to derive a lower bound on the round complexity of set agreement in a partially synchronous system by a reduction from asynchronous wait-free set agreement. Specifically, we show that every set agreement protocol requires at least $\lfloor\frac{t}{k}\rfloor + 2$ synchronous rounds to decide. We present an (asymptotically) matching algorithm that relies on a distributed asynchrony detection mechanism to decide as soon as possible during periods of synchrony. From these two results, we derive the size of the minimal window of synchrony needed to solve set agreement. By relating synchronous, asynchronous and partially synchronous environments, our simulation technique is of independent interest. In particular, it allows us to obtain a new lower bound on the complexity of early deciding k-set agreement complementary to that of Gafni etal. (in SIAM J. Comput. 40(1):63-78, 2011), and to re-derive the combinatorial topology lower bound of Guerraoui etal. (in Theor. Comput. Sci. 410(6-7):570-580, 2009) in an algorithmic wa

Failure detectors encapsulate fairness

Failure detectors have long been viewed as abstractions for the synchronism present in distributed system models. However, investigations into the exact amount of synchronism encapsulated by a given failure detector have met with limited success. The reason for this is that traditionally, models of partial synchrony are specified with respect to real time, but failure detectors do not encapsulate real time. Instead, we argue that failure detectors encapsulate the fairness in computation and communication. Fairness is a measure of the number of steps executed by one process relative either to the number of steps taken by another process or relative to the duration for which a message is in transit. We argue that failure detectors are substitutable for the fairness properties (rather than real-time properties) of partially synchronous systems. We propose four fairness-based models of partial synchrony and demonstrate that they are, in fact, the ‘weakest system models’ to implement the canonical failure detectors from the Chandra-Toueg hierarchy. We also propose a set of fairness-based models which encapsulate the G[subscript c] parametric failure detectors which eventually and permanently suspect crashed processes, and eventually and permanently trust some fixed set of c correct processes.National Science Foundation (U.S.) (Grant CCF-0964696)National Science Foundation (U.S.) (Grant CCF-0937274)Texas Higher Education Coordinating Board (grant NHARP 000512-0130-2007)National Science Foundation (U.S.) (NSF Science and Technology Center, grant agreement CCF-0939370

The Complexity of Obstruction-Free Implementations

Obstruction-free implementations of concurrent ob jects are optimized for the common case where there is no step contention, and were recently advocated as a solution to the costs associated with synchronization without locks. In this paper, we study this claim and this goes through precisely defining the notions of obstruction-freedom and step contention. We consider several classes of obstruction-free implementations, present corresponding generic ob ject implementations, and prove lower bounds on their complexity. Viewed collectively, our results establish that the worst- case operation time complexity of obstruction-free implementations is high, of step contention. We also show that lock-based implementations are not sub ject to some of the time-complexity lower bounds we present

Structured Derivations of Consensus Algorithms for Failure Detectors

In a seminal paper, Chandra and Toueg showed how unreliable failure detectors could allows processors to achieve consensus in asynchronous message passing systems. Since then, other researchers have developed consensus algorithms for other systems or based on different failure detectors. Each algorithm was developed and proven independently. This paper shows how a consensus algorithm for any of the standard models can be automatically converted to run in any other. These results show more clearly how the different system models and failure detectors can be related. In addition, they may permit the development of new results for new models also through transformations. 1 Introduction The problem of achieving consensus among processors in a distributed system is fundamental in distributed computing. Unfortunately, consensus cannot be achieved in the presence of failures in completely asynchronous systems, either those with message passing [8,9] or those with shared memory [7,8,12]. Thi..