arXiv subjects

Wojciech Golab

Publications and source records attributed to Wojciech Golab.

17 recordsLinked to original sources

arXiv2026

Analyzing Linearizability in Relativistic Distributed Systems

Einstein's theory of relativity correctly predicted that time is relative, and subject to both kinematic and gravitational dilation. Therefore, executions of distributed systems cannot always be modeled as sequences of events totally ordered according to wall clock time. To address this fundamental problem, Gilbert and Golab formulated a generalization of Herlihy and Wing's linearizability property for shared objects, which they called \emph{relativistic linearizability}, and introduced a collection of theoretical tools to facilitate rigorous analysis. While they conjectured that several widely-studied classically linearizable algorithms are also relativistically linearizable, their work stopped short of presenting formal proofs of correctness, as pointed out recently by Jayanti. In this paper, we explain how Gilbert and Golab's techniques can be used to establish relativistic linearizability for a replicated state machine, as well as variations of the widely studied read/write register construction of Attiya, Bar-Noy and Dolev (ABD). Our results establish a stronger form of relativistic linearizability than Jayanti's central theorem for these asynchronous algorithms.

cs.DC↗

arXiv2026

A Tunable Incentive Mechanism for Binary Aggregation Without Verification

Binary aggregation without verifiable ground truth arises when agents' reports must be aggregated without access to gold-standard labels. This paper studies a tunable reward--penalty mechanism for binary aggregation without verification. Agents choose between a conforming strategy, which reports an informative private signal, and a non-conforming strategy, which follows a deterministic prior-informed report rule. For this mechanism, we derive cost-adjusted sufficient conditions for incentive compatibility and individual rationality as bounds on the reward--penalty ratio. The analysis identifies feasible ratio regions, cases in which ratio adjustment restores feasibility, and parameter regimes in which no ratio satisfies both constraints under the modeled construction. We also state a conditional all-conforming Nash equilibrium result within the restricted strategy set. Entropy-based scaling and stake-weighted redistribution are treated as extensions, with stake-weighted redistribution inducing agent-specific incentive constraints. Numerical checks support the closed-form Tier 1 quantities and illustrate threshold sensitivity.

cs.GT↗

arXiv2026

Decoupling Reentrancy Protection from Smart Contract Implementation Logic

Reentrancy attacks remain a persistent threat to decentralized applications (DApps), with malicious actors siphoning around 80M USD from the DApp ecosystem last year by exploiting EVM's inter-contract message-passing semantics. Existing research focuses primarily on detection, relying on known attack patterns, and fails to provide deployable solutions that eliminate the vulnerability. Traditional reentrancy guards are similarly limited, offering incomplete coverage across attack variations and lacking robustness against complex DApp interactions. In this paper, we introduce Sentinel, a novel proxy-based approach that mitigates reentrancy vulnerabilities in a type-agnostic way by integrating reentrancy logic directly into the proxy layer, intercepting all calls to the underlying implementation contract. Key features include a dual-mode operational system offering both a gas-optimized internal guard and a high-security external lock registry for cross-contract reentrancy prevention. The proxy also intelligently handles static calls, enabling safe view-function execution while protecting against Read-Only Reentrancy (ROR) attacks. Through rigorous evaluation on a dataset of 70 vulnerable smart contracts, Sentinel achieves 100% security coverage across four major reentrancy attack categories, outperforming existing solutions by over 40%

cs.CR↗

arXiv2026

Credit Limits beyond Full Collateralization in Decentralized Micropayments: Incentive Conditions

In decentralized non-custodial micropayments, the central challenge is not whether payments can be executed directly, but under what conditions such systems can offer credit limits without requiring full collateral backing. Existing approaches typically tie available credit to posted collateral, causing liquidity requirements to scale with transaction volume and settlement exposure and limiting the practical usefulness of credit-based micropayments. This paper characterizes the incentive conditions under which credit-based non-custodial micropayments can operate beyond full collateralization while remaining incentive compatible. We model repeated buyer--merchant interactions under public monitoring and identify the roles of bounded exposure, verifiable settlement outcomes, and continuation value in deterring strategic default under non-custodial execution. The resulting characterization clarifies the trade-off between capital efficiency and the enforcement conditions required to sustain under-collateralized credit expansion without custodial trust. As an illustrative application-layer instantiation, an Arbitrum Nitro prototype provides execution-level evidence that the settlement, commitment, and incentive-enforcement paths of a credit-limit-based design can be realized with low on-chain overhead.

cs.GT↗

arXiv2024

A Game Theoretic Analysis of Validator Strategies in Ethereum 2.0

Ethereum 2.0 is the second-largest cryptocurrency by market capitalization and a widely used smart contract platform. Therefore, examining the reliability of Ethereum 2.0's incentive mechanism is crucial, particularly its effectiveness in encouraging validators to adhere to the Ethereum 2.0's protocol. This paper studies the incentive mechanism of Ethereum 2.0 and evaluates its robustness by analyzing the interaction between block proposers and attesters in a single slot. To this end, we use Bayesian games to model the strategies of block proposers and attesters and calculate their expected utilities. Our results demonstrate that the Ethereum 2.0 incentive mechanism is incentive-compatible and promotes cooperation among validators. We prove that a Bayesian Nash equilibrium and an ex ante dominant strategy exist between the block proposer and attesters in a single slot. Our research provides a solid foundation for further analysis of Ethereum 2.0's incentive mechanism and insights for individuals considering participation as a validator in Ethereum 2.0.

cs.GT↗

arXiv2023

IRS: An Incentive-compatible Reward Scheme for Algorand

Founded in 2017, Algorand is one of the world's first carbon-negative, public blockchains inspired by proof of stake. Algorand uses a Byzantine agreement protocol to add new blocks to the blockchain. The protocol can tolerate malicious users as long as a supermajority of the stake is controlled by non-malicious users. The protocol achieves about 100x more throughput compared to Bitcoin and can be easily scaled to millions of nodes. Despite its impressive features, Algorand lacks a reward-distribution scheme that can effectively incentivize nodes to participate in the protocol. In this work, we study the incentive issue in Algorand through the lens of game theory. We model the Algorand protocol as a Bayesian game and propose a novel reward scheme to address the incentive issue in Algorand. We derive necessary conditions to ensure that participation in the protocol is a Bayesian Nash equilibrium under our proposed reward scheme even in the presence of a malicious adversary. We also present quantitative analysis of our proposed reward scheme by applying it to two real-world deployment scenarios. We estimate the costs of running an Algorand node and simulate the protocol to measure the overheads in terms of computation, storage, and networking.

cs.GT↗

arXiv2019

Shallow Overlay Trees Suffice for High-Throughput Consensus

All-to-all data transmission is a typical data transmission pattern in blockchain systems. Developing an optimization scheme that provides high throughput and low latency data transmission can significantly benefit the performance of those systems. In this work, we consider the problem of optimizing all-to-all data transmission in a wide area network(WAN) using overlay multicast. We prove that in a congestion-free core network model, using shallow broadcast trees with heights up to two is sufficient for all-to-all data transmission to achieve the optimal throughput allowed by the available network resources.

cs.DC↗

arXiv2018

Recoverable Consensus in Shared Memory

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.

cs.DC↗

arXiv2016

OptEx: A Deadline-Aware Cost Optimization Model for Spark

We present OptEx, a closed-form model of job execution on Apache Spark, a popular parallel processing engine. To the best of our knowledge, OptEx is the first work that analytically models job completion time on Spark. The model can be used to estimate the completion time of a given Spark job on a cloud, with respect to the size of the input dataset, the number of iterations, the number of nodes comprising the underlying cluster. Experimental results demonstrate that OptEx yields a mean relative error of 6% in estimating the job completion time. Furthermore, the model can be applied for estimating the cost optimal cluster composition for running a given Spark job on a cloud under a completion deadline specified in the SLO (i.e., Service Level Objective). We show experimentally that OptEx is able to correctly estimate the cost optimal cluster composition for running a given Spark job under an SLO deadline with an accuracy of 98%.

cs.DC↗

arXiv2016

OptCon: An Adaptable SLA-Aware Consistency Tuning Framework for Quorum-based Stores

Users of distributed datastores that employ quorum-based replication are burdened with the choice of a suitable client-centric consistency setting for each storage operation. The above matching choice is difficult to reason about as it requires deliberating about the tradeoff between the latency and staleness, i.e., how stale (old) the result is. The latency and staleness for a given operation depend on the client-centric consistency setting applied, as well as dynamic parameters such as the current workload and network condition.We present OptCon, a novel machine learning-based predictive framework, that can automate the choice of client-centric consistency setting under user-specified latency and staleness thresholds given in the service level agreement (SLA). Under a given SLA, OptCon predicts a client-centric consistency setting that is matching, i.e., it is weak enough to satisfy the latency threshold, while being strong enough to satisfy the staleness threshold. While manually tuned consistency settings remain fixed unless explicitly reconfigured, OptCon tunes consistency settings on a per-operation basis with respect to changing workload and network state. Using decision tree learning, OptCon yields 0.14 cross validation error in predicting matching consistency settings under latency and staleness thresholds given in the SLA. We demonstrate experimentally that OptCon is at least as effective as any manually chosen consistency settings in adapting to the SLA thresholds for different use cases. We also demonstrate that OptCon adapts to variations in workload, whereas a given manually chosen fixed consistency setting satisfies the SLA only for a characteristic workload.

cs.DC↗

arXiv2015

Continuous Partial Quorums for Consistency-Latency Tuning in Distributed NoSQL Storage Systems

NoSQL storage systems are used extensively by web applications and provide an attractive alternative to conventional databases when the need for scalability outweighs the need for transactions. Several of these systems provide quorum-based replication and present the application developer with a choice of multiple client-side "consistency levels" that determine the number of replicas accessed by reads and writes, which in turn affects both latency and the consistency observed by the client application. Since using a fixed combination of read and write consistency levels for a given application provides only a limited number of discrete options, we investigate techniques that allow more fine-grained tuning of the consistency-latency trade-off, as may be required to support consistency-based service level agreements (SLAs). We propose a novel technique called \emph{continuous partial quorums} (CPQ) that assigns the consistency level on a per-operation basis by choosing randomly between two options, such as eventual and strong consistency, with a tunable probability. We evaluate our technique experimentally using Apache Cassandra and demonstrate that it outperforms an alternative tuning technique that delays operations artificially.

cs.DC↗

arXiv2013

Deconstructing Queue-Based Mutual Exclusion

We formulate a modular approach to the design and analysis of a particular class of mutual exclusion algorithms for shared memory multiprocessor systems. Specifically, we consider algorithms that organize waiting processes into a queue. Such algorithms can achieve O(1) remote memory reference (RMR) complexity, which minimizes (asymptotically) the amount of traffic through the processor-memory interconnect. We first describe a generic mutual exclusion algorithm that relies on a linearizable implementation of a particular queue-like data structure that we call MutexQueue. Next, we show two implementations of MutexQueue using O(1) RMRs per operation based on synchronization primitives commonly available in multiprocessors. These implementations follow closely the queuing code embedded in previously published mutual exclusion algorithms. We provide rigorous correctness proofs and RMR complexity analyses of the algorithms we present.

cs.DC↗

arXiv2013

On the k-Atomicity-Verification Problem

Modern Internet-scale storage systems often provide weak consistency in exchange for better performance and resilience. An important weak consistency property is k-atomicity, which bounds the staleness of values returned by read operations. The k-atomicity-verification problem (or k-AV for short) is the problem of deciding whether a given history of operations is k-atomic. The 1-AV problem is equivalent to verifying atomicity/linearizability, a well-known and solved problem. However, for k > 2, no polynomial-time k-AV algorithm is known. This paper makes the following contributions towards solving the k-AV problem. First, we present a simple 2- AV algorithm called LBT, which is likely to be efficient (quasilinear) for histories that arise in practice, although it is less efficient (quadratic) in the worst case. Second, we present a more involved 2-AV algorithm called FZF, which runs efficiently (quasilinear) even in the worst case. To our knowledge, these are the first algorithms that solve the 2-AV problem fully. Third, we show that the weighted k-AV problem, a natural extension of the k-AV problem, is NP-complete.

cs.DC↗

arXiv2012

Toward a Principled Framework for Benchmarking Consistency

Large-scale key-value storage systems sacrifice consistency in the interest of dependability (i.e., partition tolerance and availability), as well as performance (i.e., latency). Such systems provide eventual consistency,which---to this point---has been difficult to quantify in real systems. Given the many implementations and deployments of eventually-consistent systems (e.g., NoSQL systems), attempts have been made to measure this consistency empirically, but they suffer from important drawbacks. For example, state-of-the art consistency benchmarks exercise the system only in restricted ways and disrupt the workload, which limits their accuracy. In this paper, we take the position that a consistency benchmark should paint a comprehensive picture of the relationship between the storage system under consideration, the workload, the pattern of failures, and the consistency observed by clients. To illustrate our point, we first survey prior efforts to quantify eventual consistency. We then present a benchmarking technique that overcomes the shortcomings of existing techniques to measure the consistency observed by clients as they execute the workload under consideration. This method is versatile and minimally disruptive to the system under test. As a proof of concept, we demonstrate this tool on Cassandra.

cs.DC↗

arXiv2012

Minuet: A Scalable Distributed Multiversion B-Tree

Data management systems have traditionally been designed to support either long-running analytics queries or short-lived transactions, but an increasing number of applications need both. For example, online games, socio-mobile apps, and e-commerce sites need to not only maintain operational state, but also analyze that data quickly to make predictions and recommendations that improve user experience. In this paper, we present Minuet, a distributed, main-memory B-tree that supports both transactions and copy-on-write snapshots for in-situ analytics. Minuet uses main-memory storage to enable low-latency transactional operations as well as analytics queries without compromising transaction performance. In addition to supporting read-only analytics queries on snapshots, Minuet supports writable clones, so that users can create branching versions of the data. This feature can be quite useful, e.g. to support complex "what-if" analysis or to facilitate wide-area replication. Our experiments show that Minuet outperforms a commercial main-memory database in many ways. It scales to hundreds of cores and TBs of memory, and can process hundreds of thousands of B-tree operations per second while executing long-running scans.

cs.DB↗

arXiv2011

A Complexity Separation Between the Cache-Coherent and Distributed Shared Memory Models

We consider asynchronous multiprocessor systems where processes communicate by accessing shared memory. Exchange of information among processes in such a multiprocessor necessitates costly memory accesses called \emph{remote memory references} (RMRs), which generate communication on the interconnect joining processors and main memory. In this paper we compare two popular shared memory architecture models, namely the \emph{cache-coherent} (CC) and \emph{distributed shared memory} (DSM) models, in terms of their power for solving synchronization problems efficiently with respect to RMRs. The particular problem we consider entails one process sending a "signal" to a subset of other processes. We show that a variant of this problem can be solved very efficiently with respect to RMRs in the CC model, but not so in the DSM model, even when we consider amortized RMR complexity. To our knowledge, this is the first separation in terms of amortized RMR complexity between the CC and DSM models. It is also the first separation in terms of RMR complexity (for asynchronous systems) that does not rely in any way on wait-freedom---the requirement that a process makes progress in a bounded number of its own steps.

cs.DC↗

arXiv2011

Linearizable Implementations Do Not Suffice for Randomized Distributed Computation

Linearizability is the gold standard among algorithm designers for deducing the correctness of a distributed algorithm using implemented shared objects from the correctness of the corresponding algorithm using atomic versions of the same objects. We show that linearizability does not suffice for this purpose when processes can exploit randomization, and we discuss the existence of alternative correctness conditions.

cs.DC↗