This paper provides a comprehensive empirical analysis of the economics and dynamics behind arbitrages between centralized and decentralized exchanges (CEX-DEX) on Ethereum. We refine heuristics to identify arbitrage transactions from on-chain data and introduce a robust empirical framework to estimate arbitrage revenue without knowing traders' actual behaviors on CEX. Leveraging an extensive dataset spanning 19 months from August 2023 to March 2025, we estimate a total of 233.8M USD extracted by 19 major CEX-DEX searchers from 7,203,560 identified CEX-DEX arbitrages. Our analysis reveals increasing centralization trends as three searchers captured three-quarters of both volume and extracted value. We also demonstrate that searchers' profitability is tied to their integration level with block builders and uncover exclusive searcher-builder relationships and their market impact. Finally, we correct the previously underestimated profitability of block builders who vertically integrate with a searcher. These insights illuminate the darkest corner of the MEV landscape and highlight the critical implications of CEX-DEX arbitrages for Ethereum's decentralization.

Block production on the Ethereum blockchain has adopted an auction-based mechanism known as Proposer-Builder Separation (PBS), where validators outsource block creation to builders competing in MEV-Boost auctions for Maximal Extractable Value (MEV) rewards. We employ empirical game-theoretic analysis based on simulations to examine how advantages in latency and MEV access shape builder strategic bidding and auction outcomes. We find that a small set of dominant builders leverage these advantages, consolidating power, reducing auction efficiency, and heightening centralization. Our results underscore the need for fair MEV distribution and sustained efforts to promote decentralization in Ethereum’s block building market.

The MEV-Boost block auction contributes approximately 90% of all Ethereum blocks. Between October 2023 and March 2024, only three builders produced 80% of them, highlighting the concentration of power within the block builder market. To foster competition and preserve Ethereum's decentralized ethos and censorship-resistance properties, understanding the dominant players' competitive edges is essential. In this paper, we identify features that play a significant role in builders' ability to win blocks and earn profits by conducting a comprehensive empirical analysis of MEV-Boost auctions over a six-month period. We reveal that block market share positively correlates with order flow diversity, while profitability correlates with access to order flow from Exclusive Providers, such as integrated searchers and external providers with exclusivity deals. Additionally, we show a positive correlation between market share and profit margin among the top ten builders, with features such as exclusive signal, non-atomic arbitrages, and Telegram bot flow strongly correlating with both metrics. This highlights a "chicken-and-egg" problem where builders need differentiated order flow to profit, but only receive such flow if they have a significant market share. Overall, this work provides an in-depth analysis of the key features driving the builder market towards centralization and offers valuable insights for designing further iterations of Ethereum block auctions, preserving Ethereum's censorship resistance properties.

The Ethereum block-building process has changed significantly since the emergence of Proposer-Builder Separation. Validators access blocks through a marketplace, where block builders bid for the right to construct the block and earn MEV (Maximal Extractable Value) rewards in an on-chain competition, known as the MEV-boost auction. While more than 90% of blocks are currently built via MEV-Boost, tradeoffs between builders’ strategic behaviors and auction design remain poorly understood. In this paper we address this gap. We introduce a game-theoretic model for MEV-Boost auctions and use simulations to study different builders’ bidding strategies observed in practice. We study various strategic interactions and auction setups and evaluate how the interplay between critical elements such as access to MEV opportunities and improved connectivity to relays impact bidding performance. Our results demonstrate the importance of latency on the effectiveness of builders’ strategies and the overall auction outcome from the proposer’s perspective.

In 1985, Dolev and Reischuk proved a fundamental communication lower bounds on protocols achieving fault tolerant synchronous broadcast and consensus: any deterministic protocol solving those tasks (even against omission faults) requires at least a quadratic number of messages to be sent by nonfaulty parties. In contrast, many blockchain systems achieve consensus with seemingly linear communication per instance against Byzantine faults. We explore this dissonance in three main ways. First, we extend the Dolev-Reischuk family of lower bounds and prove a new lower bound for Crusader Broadcast protocols. Our lower bound for crusader broadcast requires non-trivial extensions and a much stronger Byzantine adversary with the ability to simulate honest parties. Secondly, we extend our lower bounds to all-but-m Crusader Broadcast, in which up to m parties are allowed to output a different value. Finally, we discuss the ways in which these lower bounds relate to the security of blockchain systems. We show how Eclipse-style attacks in such systems can be viewed as specific instances of the attacks used in our lower bound for Crusader Broadcast. This connection suggests a more systematic way of analyzing and reasoning about Eclipse-style attacks through the lens of the Dolev-Reischuk family of attacks.

Over the years, medical informatics researchers have studied how to use software technologies to provide decision support for using evidence-based medical procedures. Software professionals have investigated how to support hospital administration, therapy and laboratory workflows. For many of these efforts, managing the exceptions in the workflows is a key issue since the medical workflows must cope with a wide variety of patient medical situations as well as those of the healthcare environments. This paper presents an analysis of past research in managing medical workflow exceptions, and proposes future research that would benefit the medical applications. The paper is focused on three topics: representing, handling and analyzing exceptions. Based upon our analysis, we believe that techniques for verifying exception management models and for handling dynamic exceptions should be useful and possibly essential for developing large scale, practical medical workflow systems.