Many differentially private and classical non-private graph algorithms rely crucially on determining whether some property of each vertex meets a threshold. For example, for the k-core decomposition problem, the classic peeling algorithm iteratively removes a vertex if its induced degree falls below a threshold. The sparse vector technique (SVT) is generally used to transform non-private threshold queries into private ones with only a small additive loss in accuracy. However, a naive application of SVT in the graph setting leads to an amplification of the error by a factor of n due to composition, as SVT is applied to every vertex. In this paper, we resolve this problem by formulating a novel generalized sparse vector technique which we call the Multidimensional AboveThreshold (MAT) Mechanism which generalizes SVT (applied to vectors with one dimension) to vectors with multiple dimensions. When applied to vectors with n dimensions, we solve a number of important graph problems with better bounds than previous work. Specifically, we apply our MAT mechanism to obtain a set of improved bounds for a variety of problems including k-core decomposition, densest subgraph, low out-degree ordering, and vertex coloring. We give a tight local edge differentially private (LEDP) algorithm for k-core decomposition that results in an approximation with O(ε^{-1} log n) additive error and no multiplicative error in O(n) rounds. We also give a new (2+η)-factor multiplicative, O(ε^{-1} log n) additive error algorithm in O(log² n) rounds for any constant η > 0. Both of these results are asymptotically tight against our new lower bound of Ω(log n) for any constant-factor approximation algorithm for k-core decomposition. Our new algorithms for k-core decomposition also directly lead to new algorithms for the related problems of densest subgraph and low out-degree ordering. Finally, we give novel LEDP differentially private defective coloring algorithms that use number of colors given in terms of the arboricity of the graph.

The class of extension-based proofs encompasses traditional valency arguments. It has been shown that they are insufficient to establish the impossibility of (n-1)-set agreement among n ≥ 3 processes in an asynchronous system with crash failures. We generalize this definition to k-exhaustive extension-based proofs, in which a prover can learn the maximum length of all executions involving a set of at most k processes from a specified configuration (which may be infinite). An upper bound on the length of these executions enables the prover to determine the outputs of all these executions. When k = n, this enables the prover to perform an exhaustive search of all reachable configurations, so it knows everything about the protocol. On the other hand, extension based proofs are as powerful as 1-exhaustive extension-based proofs. For any task with no deterministic, wait-free solution among n ≥ 2 processes, we show that there is an (n-1)-exhaustive extension-based proof of its impossibility. This is done using a new characterization of such tasks. In contrast, we prove that for 1 ≤ k ≤ n-2, there is no k-exhaustive extension-based proof of the impossibility of (n-1)-set agreement.

Since the mid-1980s it has been known that Byzantine Agreement can be solved with probability 1 asynchronously, even against an omniscient, computationally unbounded adversary that can adaptively corrupt up to f < n/3 parties. Moreover, the problem is insoluble with f ≥ n/3 corruptions. However, Bracha’s [ 13 ] 1984 protocol (see also Ben-Or [ 8 ]) achieved f < n/3 resilience at the cost of exponential expected latency 2 Θ ( n ) , a bound that has never been improved in this model with f = ⌊ (n-1)/3 ⌋ corruptions. In this article, we prove that Byzantine Agreement in the asynchronous, full information model can be solved with probability 1 against an adaptive adversary that can corrupt f < n/3 parties, while incurring only polynomial latency with high probability . Our protocol follows an earlier polynomial latency protocol of King and Saia [ 33 , 34 ], which had suboptimal resilience, namely f ≈ n /10 9 [ 33 , 34 ]. Resilience f = (n-1)/3 is uniquely difficult, as this is the point at which the influence of the Byzantine and honest players are of roughly equal strength. The core technical problem we solve is to design a collective coin-flipping protocol that eventually lets us flip a coin with an unambiguous outcome. In the beginning, the influence of the Byzantine players is too powerful to overcome, and they can essentially fix the coin’s behavior at will. We guarantee that after just a polynomial number of executions of the coin-flipping protocol, either (a) the Byzantine players fail to fix the behavior of the coin (thereby ending the game) or (b) we can “blacklist” players such that the blacklisting rate for Byzantine players is at least as large as the blacklisting rate for good players. The blacklisting criterion is based on a simple statistical test of fraud detection .

Abstract. Determining the number of registers required for solving obstruction-free (or randomized wait-free) [Formula: see text]-set agreement is an open problem that highlights important gaps in our understanding of the space complexity of synchronization. The best known upper bound on the number of registers needed to solve this problem among [Formula: see text] processes is [Formula: see text] registers. No general lower bound better than 2 was known. We prove that any obstruction-free protocol solving [Formula: see text]-set agreement among [Formula: see text] processes must use at least [Formula: see text] registers. In particular, we get a tight lower bound of exactly [Formula: see text] registers for solving obstruction-free and randomized wait-free consensus. Our main tool is a simulation that serves as a reduction from the impossibility of deterministic wait-free [Formula: see text]-set agreement. In particular, we show that if an obstruction-free protocol for [Formula: see text]-set agreement uses fewer registers, then it is possible for [Formula: see text] processes to simulate the protocol and deterministically solve [Formula: see text]-set agreement in a wait-free manner, which is impossible. An important aspect of the simulation is the ability of simulating processes to revise the past of simulated processes. We introduce an augmented snapshot object, which facilitates this. More generally, our simulation applies to the broad class of colorless tasks. We can use it to prove, for example, a lower bound on the number of registers needed to solve obstruction-free [Formula: see text]-approximate agreement, which matches the best known upper bound to within a factor of 2 when [Formula: see text] is sufficiently small. No general lower bound for this problem was known. Finally, we prove that any lower bound on the number of registers used by obstruction-free protocols applies to protocols that satisfy nondeterministic solo-termination. Hence, our lower bounds for obstruction-free protocols also hold for randomized wait-free protocols.

Since the mid-1980s it has been known that Byzantine Agreement can be solved with probability 1 asynchronously, even against an omniscient, computationally unbounded adversary that can adaptively corrupt up to f < n/3 parties. Moreover, the problem is insoluble with f ≥ n/3 corruptions. However, Bracha's [Bra87] 1984 protocol (see also Ben-Or [Ben83]) achieved f < n/3 resilience at the cost of exponential expected latency 2θ(n), a bound that has never been improved in this model with f = ⌊(n- 1)/3⌋ corruptions.

Abstract. We introduce extension-based proofs, a class of impossibility proofs that includes valency arguments. They are modelled as an interaction between a prover and a protocol. Using proofs based on combinatorial topology, it has been shown that it is impossible to deterministically solve [Formula: see text]-set agreement among [Formula: see text] processes or approximate agreement on a cycle of length 4 among [Formula: see text] processes in a wait-free manner in asynchronous models where processes communicate using objects that can be constructed from shared registers. However, it was unknown whether proofs based on simpler techniques were possible. We show that these impossibility results cannot be obtained by extension-based proofs in the iterated snapshot model and, hence, extension-based proofs are limited in power.

It has been known since the early 1980s that Byzantine Agreement in the full information, asynchronous model is impossible to solve deterministically against even one crash fault [FLP 1985], but that it can be solved with probability 1 [Ben-Or 1983], even against an adversary that controls the scheduling of all messages and corrupts up to f

Abstract Many shared memory algorithms have to deal with the problem of determining whether the value of a shared object has changed in between two successive accesses of that object by a process when the responses from both are the same. Motivated by this problem, we define the signal detection problem, which can be studied on a purely combinatorial level. Consider a system with n + 1 processes consisting of n readers and one signaller. The processes communicate through a shared blackboard that can store a value from a domain of size m. Processes are scheduled by an adversary. When scheduled, a process reads the blackboard, modifies its contents arbitrarily, and, provided it is a reader, returns a Boolean value. A reader must return true if the signaller has taken a step since the reader’s preceding step; otherwise it must return false. Intuitively, in a system with n processes, signal detection should require at least n bits of shared information, i.e., m ≥ 2n. But a proof of this conjecture remains elusive. For the general case, we prove a lower bound of m ≥ n2. For restricted versions of the problem, where the processes are oblivious or where the signaller must write a fixed sequence of values, we prove a tight lower bound of m ≥ 2n. We also consider a version of the problem where each reader takes at most two steps. In this case, we prove that m = n + 1 blackboard values are necessary and sufficient.

In the consensus problem, there are $n$ processes that each has a private input value. Each nonfaulty process must output a single value such that no two processes output different values and the output is the input value of some process. There are many consensus protocols for systems where the processes may only communicate by reading and writing to shared registers. Of particular interest are protocols that have progress guarantees such as randomized wait-freedom or obstruction-freedom. In 1992, it was proved that such protocols must use $\Omega(\sqrt{n})$ registers. In 2015, this was improved to $\Omega(n)$ registers in the anonymous setting, where processes do not have identifiers. We prove that every randomized wait-free or obstruction-free protocol for solving consensus among $n$ processes must use at least $n-1$ registers.

We introduce extension-based proofs, a class of impossibility proofs that includes valency arguments. They are modelled as an interaction between a prover and a protocol. Using proofs based on combinatorial topology, it has been shown that it is impossible to deterministically solve k-set agreement among n > k ≥ 2 processes in a wait-free manner. However, it was unknown whether proofs based on simpler techniques were possible. We explain why this impossibility result cannot be obtained by an extension-based proof and, hence, extension-based proofs are limited in power.

Herlihy's consensus hierarchy ranks the power of various synchronization primitives for solving consensus in a model where asynchronous processes communicate through shared memory and fail by halting. This paper revisits the consensus hierarchy in a model with crash-recovery failures, where the specification of consensus, called \emph{recoverable consensus} in this paper, is weakened by allowing non-terminating executions when a process fails infinitely often. Two variations of this model are considered: independent failures, and simultaneous (i.e., system-wide) failures. Several results are proved in this model: (i) We prove that any primitive at level two of Herlihy's hierarchy remains at level two if simultaneous crash-recovery failures are introduced. This is accomplished by transforming (one instance of) any 2-process conventional consensus algorithm to a 2-process recoverable consensus algorithm. (ii) For any $n > 1$ and $f > 0$, we show how to use $f+1$ instances of any conventional $n$-process consensus algorithm and $Θ(f + n)$ read/write registers to solve $n$-process recoverable consensus when crash-recovery failures are independent, assuming that every execution contains at most $f$ such failures. (iii) Next, we prove for any $f > 0$ that any 2-process recoverable consensus algorithm that uses TAS and read/writer registers requires at least $f+1$ TAS objects, assuming that crash-recovery failures are independent and every execution contains at most $f$ such failures. (iv) Lastly, we generalize and strengthen (iii) by proving that any universal construction of $n$-process recoverable consensus from a type $T$ with consensus number $n$ and read/write registers requires at least $f+1$ base objects of type $T$ in executions with up to $f$ failures.

It is impossible to deterministically solve wait-free consensus in an asynchronous system. The classic proof uses a valency argument, which constructs an infinite execution by repeatedly extending a finite execution. We introduce extension-based proofs, a class of impossibility proofs that are modelled as an interaction between a prover and a protocol and that include valency arguments.

Determining the number of registers required for solving x-obstruction-free (or randomized wait-free) k-set agreement for x ≤ k is an open problem that highlights important gaps in our understanding of the space complexity of synchronization. In x-obstruction-free protocols, processes are required to return in executions where at most x processes take steps. The best known upper bound on the number of registers needed to solve this problem among n>k processes is n-k+x registers. No general lower bound better than 2 was known.

For many years, Herlihy's elegant computability based Consensus Hierarchy has been our best explanation of the relative power of various types of multiprocessor synchronization objects when used in deterministic algorithms. However, key to this hierarchy is treating these instructions as distinct objects, an approach that is far from the real-world, where multiprocessor programs apply synchronization instructions to collections of arbitrary memory locations. We were surprised to realize that, when considering instructions applied to memory locations, the computability based hierarchy collapses. This leaves open the question of how to better captures the power of various synchronization instructions.

Existing n-process randomized wait-free and obstruction-free consensus protocols from registers all use at least n registers. In 1992, it was proved that such protocols must use Ω(√n) registers. Recently, this was improved to Ω(n) registers in the anonymous setting, where processes do not have identifiers. We have recently proved that at least n-1 registers are needed, even if processes have identifiers.

Existing n-process randomized wait-free (and obstruction-free) consensus protocols from registers all use at least n registers. In 1992, it was proved that such protocols must use Omega(sqrt(n)) registers. Recently, this was improved to Omega(n) registers in the anonymous setting, where processes do not have identifiers. Closing the gap in the general case, however, remained an open problem. We resolve this problem by proving that every randomized wait-free (or obstruction-free) consensus protocol for n processes must use at least n-1 registers.

Existing n-process implementations of atomic snapshots from registers use large registers. We consider the problem of implementing an m-component snapshot from small, Theta(log(n))-bit registers. A natural solution is to consider simulating the large registers. Doing so straightforwardly can significantly increase the step complexity. We introduce the notion of an interruptible read and show how it can reduce the step complexity of simulating the large registers in the snapshot of Afek et al. In particular, we show how to modify a recent large register simulation to support interruptible reads. Using this modified simulation, the step complexity of UPDATE and SCAN changes from Theta(n*m) to Theta(n*m+m*w), instead of Theta(n*m*w), if each component of the snapshot consists of Theta(w*log(n)) bits. We also show how to modify a limited-use snapshot to use small registers when the number of UPDATE operations is in n^{O(1)}. In this case, we change the step complexity of UPDATE from Theta((log(n))^3) to O(w + (log(n))^2*log(m)) and the step complexity of SCAN from Theta(log(n)) to O(m*w + log(n)).