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Atefeh Zareh Chahoki

Publications and source records attributed to Atefeh Zareh Chahoki.

3 recordsLinked to original sources

Conthereum: Concurrent Ethereum Optimized Transaction Scheduling for Multi-Core Execution

Conthereum is a concurrent Ethereum solution for intra-block parallel transaction execution, enabling validators to utilize multi-core infrastructure and transform the sequential execution model of Ethereum into a parallel one. This shift significantly increases throughput and transactions per second (TPS), while ensuring conflict-free execution in both proposer and attestor modes and preserving execution order consistency in the attestor. At the heart of Conthereum is a novel, lightweight, high-performance scheduler inspired by the Flexible Job Shop Scheduling Problem (FJSS). We propose a custom greedy heuristic algorithm, along with its efficient implementation, that solves this formulation effectively and decisively outperforms existing scheduling methods in finding suboptimal solutions that satisfy the constraints, achieve minimal makespan, and maximize speedup in parallel execution. Additionally, Conthereum includes an offline phase that equips its real-time scheduler with a conflict analysis repository obtained through static analysis of smart contracts, identifying potentially conflicting functions using a pessimistic approach. Building on this novel scheduler and extensive conflict data, Conthereum outperforms existing concurrent intra-block solutions. Empirical evaluations show near-linear throughput gains with increasing computational power on standard 8-core machines. Although scalability deviates from linear with higher core counts and increased transaction conflicts, Conthereum still significantly improves upon the current sequential execution model and outperforms existing concurrent solutions under a wide range of conditions.

cs.CR↗

SoK: Concurrency in Blockchain -- A Systematic Literature Review and the Unveiling of a Misconception

Smart contracts, the cornerstone of blockchain technology, enable secure, automated distributed execution. Given their role in handling large transaction volumes across clients, miners, and validators, exploring concurrency is critical. This includes concurrent transaction execution or validation within blocks, block processing across shards, and miner competition to select and persist transactions. Concurrency and parallelism are a double-edged sword: while they improve throughput, they also introduce risks like race conditions, non-determinism, and vulnerabilities such as deadlock and livelock. This paper presents the first survey of concurrency in smart contracts, offering a systematic literature review organized into key dimensions. First, it establishes a taxonomy of concurrency levels in blockchain systems and discusses proposed solutions for future adoption. Second, it examines vulnerabilities, attacks, and countermeasures in concurrent operations, emphasizing the need for correctness and security. Crucially, we reveal a flawed concurrency assumption in a major research category, which has led to widespread misinterpretation. This work aims to correct that and guide future research toward more accurate models. Finally, we identify gaps in each category to outline future research directions and support blockchain's advancement.

cs.CR↗

Static Analysis for Detecting Transaction Conflicts in Ethereum Smart Contracts

Ethereum smart contracts operate in a concurrent environment where multiple transactions can be submitted simultaneously. However, the Ethereum Virtual Machine (EVM) enforces sequential execution of transactions within each block to prevent conflicts arising from concurrent access to the same state variables. Although this approach guarantees correct behavior, it limits the ability of validators to leverage multi-core architectures for faster transaction processing, thus restricting throughput. Existing solutions introduce concurrency by allowing simultaneous transaction execution combined with runtime conflict detection and rollback mechanisms to maintain correctness. However, these methods incur significant overhead due to continuous conflict tracking and transaction reversion. Recently, alternative approaches have emerged that aim to predict conflicts statically, before execution, by analyzing smart contract code for potential transaction interactions. Despite their promise, there is a lack of comprehensive studies that examine static conflict detection and its broader implications in specific smart contracts. This paper fills this important gap by proposing a novel static analysis method to detect potential transaction conflicts in Ethereum smart contracts. Our method identifies read-write, write-write, and function call conflicts between transaction pairs by analyzing state variable access patterns in Solidity contracts. We implement a tool that parses contract code and performs conflict detection. Evaluation on a dataset of real-world Ethereum smart contracts demonstrates that our approach achieves high precision in identifying potential conflicts. By enabling proactive conflict detection, our tool supports further design of transaction scheduling strategies that reduce runtime failures, enhance validator throughput, and contribute to blockchain scalability.

cs.DC↗