The Step Complexity of Multidimensional Approximate Agreement

Approximate agreement allows a set of n processes to obtain outputs that are within a specified distance ? > 0 of one another and within the convex hull of the inputs. When the inputs are real numbers, there is a wait-free shared-memory approximate agreement algorithm [Moran, 1995] whose step complexity is in O(n log(S/?)), where S, the spread of the inputs, is the maximal distance between inputs. There is another wait-free algorithm [Schenk, 1995] that avoids the dependence on n and achieves O(log(M/?)) step complexity where M, the magnitude of the inputs, is the absolute value of the maximal input. This paper considers whether it is possible to obtain an approximate agreement algorithm whose step complexity depends on neither n nor the magnitude of the inputs, which can be much larger than their spread. On the negative side, we prove that ?(min{(log M)/(log log M), (?log n)/(log log n)}) is a lower bound on the step complexity of approximate agreement, even when the inputs are real numbers. On the positive side, we prove that a polylogarithmic dependence on n and S/? can be achieved, by presenting an approximate agreement algorithm with O(log n (log n + log(S/?))) step complexity. Our algorithm works for multidimensional domains. The step complexity can be further restricted to be in O(min{log n (log n + log (S/?)), log(M/?)}) when the inputs are real numbers

Optimal Resilience in Systems That Mix Shared Memory and Message Passing

We investigate the minimal number of failures that can partition a system where processes communicate both through shared memory and by message passing. We prove that this number precisely captures the resilience that can be achieved by algorithms that implement a variety of shared objects, like registers and atomic snapshots, and solve common tasks, like randomized consensus, approximate agreement and renaming. This has implications for the m&m-model of [Aguilera et al., 2018] and for the hybrid, cluster-based model of [Damien Imbs and Michel Raynal, 2013; Michel Raynal and Jiannong Cao, 2019]

Byzantine Lattice Agreement in Asynchronous Systems

We study the Byzantine lattice agreement (BLA) problem in asynchronous distributed message passing systems. In the BLA problem, each process proposes a value from a join semi-lattice and needs to output a value also in the lattice such that all output values of correct processes lie on a chain despite the presence of Byzantine processes. We present an algorithm for this problem with round complexity of O(log f) which tolerates f < n/5 Byzantine failures in the asynchronous setting without digital signatures, where n is the number of processes. This is the first algorithm which has logarithmic round complexity for this problem in asynchronous setting. Before our work, Di Luna et al give an algorithm for this problem which takes O(f) rounds and tolerates f < n/3 Byzantine failures. We also show how this algorithm can be modified to work in the authenticated setting (i.e., with digital signatures) to tolerate f < n/3 Byzantine failures

Wait-Free and Obstruction-Free Snapshot

The snapshot problem was first proposed over a decade ago and has since been well-studied in the distributed algorithms community. The challenge is to design a data structure consisting of $m$ components, shared by upto $n$ concurrent processes, that supports two operations. The first, $Update(i,v)$, atomically writes $v$ to the $i$th component. The second, $Scan()$, returns an atomic snapshot of all $m$ components. We consider two termination properties: wait-freedom, which requires a process to always terminate in a bounded number of its own steps, and the weaker obstruction-freedom, which requires such termination only for processes that eventually execute uninterrupted. First, we present a simple, time and space optimal, obstruction-free solution to the single-writer, multi-scanner version of the snapshot problem (wherein concurrent Updates never occur on the same component). Second, we assume hardware support for compare&swap (CAS) to give a time-optimal, wait-free solution to the multi-writer, single-scanner snapshot problem (wherein concurrent Scans never occur). This algorithm uses only $O(mn)$ space and has optimal CAS, write and remote-reference complexities. Additionally, it can be augmented to implement a general snapshot object with the same time and space bounds, thus improving the space complexity of $O(mn^2)$ of the only previously known time-optimal solution

Polynomial-Time Verification and Testing of Implementations of the Snapshot Data Structure

We analyze correctness of implementations of the snapshot data structure in terms of linearizability. We show that such implementations can be verified in polynomial time. Additionally, we identify a set of representative executions for testing and show that the correctness of each of these executions can be validated in linear time. These results present a significant speedup considering that verifying linearizability of implementations of concurrent data structures, in general, is EXPSPACE-complete in the number of program-states, and testing linearizability is NP-complete in the length of the tested execution. The crux of our approach is identifying a class of executions, which we call simple, such that a snapshot implementation is linearizable if and only if all of its simple executions are linearizable. We then divide all possible non-linearizable simple executions into three categories and construct a small automaton that recognizes each category. We describe two implementations (one for verification and one for testing) of an automata-based approach that we develop based on this result and an evaluation that demonstrates significant improvements over existing tools. For verification, we show that restricting a state-of-the-art tool to analyzing only simple executions saves resources and allows the analysis of more complex cases. Specifically, restricting attention to simple executions finds bugs in 27 instances, whereas, without this restriction, we were only able to find 14 of the 30 bugs in the instances we examined. We also show that our technique accelerates testing performance significantly. Specifically, our implementation solves the complete set of 900 problems we generated, whereas the state-of-the-art linearizability testing tool solves only 554 problems

The Space Complexity of Scannable Objects with Bounded Components

A fundamental task in the asynchronous shared memory model is obtaining a consistent view of a collection of shared objects while they are being modified concurrently by other processes. A scannable object addresses this problem. A scannable object is a sequence of readable objects called components, each of which can be accessed independently. It also supports the Scan operation, which simultaneously reads all of the components of the object. In this paper, we consider the space complexity of an n-process, k-component scannable object implementation from objects with bounded domain sizes. If the value of each component can change only a finite number of times, then there is a simple lock-free implementation from k objects. However, more objects are needed if each component is fully reusable, i.e. for every pair of values v, v\u27, there is a sequence of operations that changes the value of the component from v to v\u27. We considered the special case of scannable binary objects, where each component has domain {0, 1}, in PODC 2021. Here, we present upper and lower bounds on the space complexity of any n-process implementation of a scannable object O with k fully reusable components from an arbitrary set of objects with bounded domain sizes. We construct a lock-free implementation from k objects of the same types as the components of O along with ?n/b? objects with domain size 2^b. By weakening the progress condition to obstruction-freedom, we construct an implementation from k objects of the same types as the components of O along with ?n/(b-1)? objects with domain size b. When the domain size of each component and each object used to implement O is equal to b and n ? b^k - bk + k, we prove that 1/2? (k + (n-1)/b - log_b n) objects are required. This asymptotically matches our obstruction-free upper bound. When n > b^k - bk + k, we prove that 1/2? (b^{k-1} - {(b-1)k + 1}/b) objects are required. We also present a lower bound on the number of objects needed when the domain sizes of the components and the objects used by the implementation are arbitrary and finite

How hard is it to take a snapshot

Abstract. The snapshot object is an important and well-studied primitive in distributed computing. This paper will present some implementations of snapshots from registers, in both asycnhronous and synchronous systems, and discuss known lower bounds on the time and space complexity of this problem