arXiv subjects

Can Umut Ileri

Publications and source records attributed to Can Umut Ileri.

3 recordsLinked to original sources

arXiv2026

The Blockchain Execution Dilemma: Optimizing Revenue XOR Fair Ordering

Successive consensus algorithm generations displaced the blockchain performance bottleneck to the execution layer. Recent works address this by parallelizing non-conflicting transactions. Historically, execution followed consensus-level ordering, a practice susceptible to Maximal Extractable Value (MEV) exploitation. Conversely, recent academic proposals introduce rigid fair-ordering protocols that severely restrict transaction reordering. Parallel execution frameworks optimize the sequencing layer, located between consensus and execution, assembling transaction batches from committed blocks and transmitting them to workers to maximize execution parallelism and realized fees. To achieve this, current sequencing implementations may defer transactions, but they do not maintain order fairness. Preserving these properties currently requires sequential execution, drastically reducing profitability and performance. In this work, we address the tension between validator profit and order fairness using a dynamic optimization framework. We introduce a blockchain-agnostic model for transaction sequencing in a continuous setting where block sequencing and execution run concurrently. When sequencing cannot complete within the available time window, our framework dynamically returns its best intermediate result. Within this framework, we propose an anytime genetic algorithm that utilizes gas prices, object sets, and predicted execution times to optimize schedules, with an option to maintain fair ordering. Evaluating our approach on real-world Sui and Ethereum datasets shows it increases validator profit by ~15% and accelerates congestion relief speed by up to 58%. Furthermore, fair-ordering constraints can reduce validator profit by 50% to 60% during high congestion, providing the first evidence that enforcing strict fair ordering might effectively nullify the advantages of advanced sequencing.

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arXiv2025

NEMO: Faster Parallel Execution for Highly Contended Blockchain Workloads (Full version)

Following the design of more efficient blockchain consensus algorithms, the execution layer has emerged as the new performance bottleneck of blockchains, especially under high contention. Current parallel execution frameworks either rely on optimistic concurrency control (OCC) or on pessimistic concurrency control (PCC), both of which see their performance decrease when workloads are highly contended, albeit for different reasons. In this work, we present NEMO, a new blockchain execution engine that combines OCC with the object data model to address this challenge. NEMO introduces four core innovations: (i) a greedy commit rule for transactions using only owned objects; (ii) refined handling of dependencies to reduce re-executions; (iii) the use of incomplete but statically derivable read/write hints to guide execution; and (iv) a priority-based scheduler that favors transactions that unblock others. Through simulated execution experiments, we demonstrate that NEMO significantly reduces redundant computation and achieves higher throughput than representative approaches. For example, with 16 workers NEMO's throughput is up to 42% higher than the one of Block-STM, the state-of-the-art OCC approach, and 61% higher than the pessimistic concurrency control baseline used.

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arXiv2020

XChange: A Blockchain-based Mechanism for Generic Asset Trading In Resource-constrained Environments

An increasing number of industries rely on Internet-of-Things devices to track physical resources. Blockchain technology provides primitives to represent these resources as digital assets on a secure distributed ledger. Due to the proliferation of blockchain-based assets, there is an increasing need for a generic mechanism to trade assets between isolated platforms. To date, there is no such mechanism without reliance on a trusted third party. In this work, we address this shortcoming and present XChange. Unlike existing approaches for decentralized asset trading, we decouple trade management and the actual exchange of assets. XChange mediates trade of any digital asset between isolated blockchain platforms while limiting the fraud conducted by adversarial parties. We first describe a generic, five-phase trading protocol that establishes and executes trade between individuals. This protocol accounts full trade specifications on a separate blockchain. We then devise a lightweight system architecture, composed of all required components for a generic asset marketplace. We implement XChange and conduct real-world experimentation. We leverage an existing, lightweight blockchain, TrustChain, to account all orders and full trade specifications. By deploying XChange on multiple low-resource devices, we show that a full trade completes within half a second. To quantify the scalability of our mechanism, we conduct further experiments on our compute cluster. We conclude that the throughput of XChange, in terms of trades per second, scales linearly with the system load. Furthermore, we find that XChange exhibits superior throughput and order fulfil latency compared to related decentralized exchanges, BitShares and Waves.

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