L2 status and challenges: Dynamic analysis of MEV after Dencun upgrade
Original author: sui 414
Original translation: Vernacular Blockchainorte
In this post, we aim to present a statistical overview of the current state of L2. We will explore the significance of the reduction in L2 transaction fees following the Dencun upgrade in March, examine the evolution of activity on these networks, and highlight new challenges arising from MEV activity. Additionally, we discuss potential obstacles to developing MEV tools and solutions on L2.
1. Positive impact of Dencun upgrade: L2 adoption
1) Transaction fees dropped 10 times
Ethereum Layer 2 (L2) transaction fees consist of two parts: the cost of executing transactions on L2, and the cost of submitting batches of transactions to Ethereum Layer 1 (L1). The specific transaction fee structure and sorting rules of different L2s vary depending on their desarrollo stage and design chohielos.
For example, Arbitrum uses a first-come, first-served basis (FCFS), which processes transactions in the order they are received. In contrast, Optimism (OP Mainnet) and Base (both part of the OP Stack) use a Priority Transaction Fee Auction (PGA) model that includes L2 base fees and priority fees. Users can choose to pay higher priority fees to be included in the block faster and earlier. Understanding these fee structures is critical to understanding the growth of the ecosystem and the dynamics of MEV.
Historically, Ethereum L1 fees have made up the majority of total fees when users use L2 to conduct transactions, accounting for more than 80%, as shown in the black bars in the figure below. However, since the Dencun upgrade on March 14, L2 has switched from using calldata to a more cost-effective method of submitting batches to L1 called blobs 1. This temporary storage method includes its own fee auction mechanism, including a blob base fee and priority fee.
Since the Dencun upgrade, L2 has paid a significant reduction in L1 fees – the chart shows that the transaction fee composition of the OP Stack chain has changed significantly, with L1 fees falling from 90% to just 1%, while L2 fees now account for 99% of the total fees. This shift has led to an overall decrease in the average total transaction fee of L2 by about ten times, for example, the average transaction fee on the OP mainnet has dropped from about $0.5 per transaction to $0.05.
2) L2 activity surges
Following the cost reduction, L2 activity and usage increased significantly, as evidenced by the surge in L2 transaction fees shown in the chart above. Notably, on March 26, Base’s average transaction fee exceeded its pre-upgrade high. In order to accommodate more transactions and reduce network congestion, Base raised its transaction fee target starting on March 26 and has adjusted it several times since then.
The chart below shows daily transaction volume for L2, demonstrating significant growth for networks such as Arbitrum, Base, and OP Mainnet. Specifically, Base has quadrupled its daily transaction volume and now processes approximately 2 million transactions per day.
Although it is difficult to determine whether this is the result of natural growth or the impact of incentive programs and Sybil attack activities, after the EIP-4844 upgrade, there has been a significant increase in active addresses and decentralized exchange (DEX) trading volumes on all major L2s, especially on Base and Arbitrum.
3) Assets transferred to L2
With the improvement of market conditions and the Memecoin craze triggered by WIF on Solana, the total locked value (TVL) of L2 has continued to rise since the end of last year. Notably, Base has become the fastest growing chain, and its total locked value recently surpassed the OP mainnet.
Since the beginning of March, Base has had about $1.5 billion in USDC inflows, part of which is Coinbase moving customer and corporate funds to Base. According to data provided by Artemis, Ethereum has seen $14 billion in outflows to major L2s through 11 major bridges since January 2024. Arbitrum leads with about $7 billion, followed by zkSync, Base, and OP Mainnet. Further data shows that Debridge Finance (a widely used bridge in EVM chains and Solana) confirms that Arbitrum and Base are the main recipients of all outflows.
4) Bad news: Dark Forest is expanding amid cheaper transaction fees
When we further inspect transactions, we find that bot trading activity is driving up L2 transaction fees and rollback rates. We explore this more fully in the next section through a case study using Base data, highlighting the impact of cheaper transaction fees on L2 after the Dencun upgrade.
2. Dencun’s upgraded L2: like Ethereum before Flashbots without a memory pool
1) Network congestion
Challenges began to emerge: On March 26, Bases average daily transaction fee experienced a short-term surge, even exceeding the level before the Dencun upgrade. By June 3, Base adjusted its transaction fee target from 2.5 M Gas/s during the Dencun upgrade to 7.5 M Gas/s, bringing the average transaction fee back to about 5 cents.
The contracts that consume the most transaction fees on Base include Telegram trading robots such as Sigma and Banana Gun, as well as wallets and decentralized exchanges such as Bitget and Uniswap. In addition, a large number of unmarked contracts involve activities such as token minting, memecoin trading, and atomic arbitrage.
By comparing the behavior of popular Telegram bot routes like BananaGun, it is clear that their transactions incur significantly higher transaction fees compared to other transactions. After the upgrade, users of the BananaGun Telegram bot paid peak transaction fees of up to 30 Gwei to execute transactions on Base. This rate has now stabilized at around 3 Gwei, which is 43 times higher than the transaction fees paid by other transactions.
When analyzing the average monthly transaction fees paid by all popular decentralized exchange (DEX) trading bots on Base, compared to all other non-Telegram bot trading (black bars), it is clear that trading bot users incur significantly higher transaction fees.
2) A surge in high rollback rates
Another important indicator of blockchain importance is the transaction rollback rate on the network, which we also observed on L2s after the Dencun upgrade, especially on Base, Arbitrum and OP mainnet. (The rollback rate refers to the proportion of transactions on the blockchain that failed to be successfully confirmed for various reasons.)
Currently, Ethereums transaction rollback rate is about 2%, while Binance Smart Chain and Polygons rollback rate is about 5-6%. Before the upgrade, Bases rollback rate was about 2%, but then rose to about 15%, peaking at 30% on April 4. Similarly, Arbitrum and OP mainnets have also seen periodic surges in failed transactions, ranging between 10% and 20%.
After further analysis, we noticed that the high rollback rate on L2 does not necessarily reflect the experience of every ordinary user. Instead, these rollbacks are likely coming from MEV robots.
Using the following heuristic query, we identified a set of routing contracts with bot-style activity — contracts that appear to experience high rollback rates when executing MEV withdrawal transactions:
Since Dencun was upgraded,
Active Routing: The contract has processed more than 1,000 transactions. Limited Interactions with EOA: Fewer than 10 EOA (Externally Owned Account) wallets have interacted as a transaction sender.
Sender distribution: Less than 50% of transaction senders sent only one transaction, indicating that this route is unlikely to be used by retail users.
Behavioral patterns: Transaction history either covers exactly 24 hours or shows multiple transactions within a single block, indicating non-human behavior.
Exchange concentration: More than 75% of successful transactions involve an exchange.
Detected MEV transactions: More than 10% of successful transactions utilized the atomic MEV strategy, detected based on hildobbys heuristic method2.
Based on these criteria, we detected 51 routers that likely represent a conservative lower bound for bot activity on Base. We divided all transactions processed by routers on Base into two groups and then performed a comparative analysis between them. We found that the average rollback rate for transactions of router contracts with bot-like operations was 60%, while the rollback rate for other transactions was about 10%, and the rollback rate for bot operations was six times that of other transactions.
Based on the above data, we can conclude that bot activities, such as MEV bots and Telegram bots, are likely one of the main reasons for the high transaction fees and rollback rates on Base.
L2s single sequencer infrastructure, coupled with the lack of a public memory pool, promotes dominant MEV strategies involving a large number of sequencer abuses. These strategies significantly cause network congestion, especially for L2s that adopt priority transaction fee auctions (PGA) like OP Mainnet and Base. The result is not only network congestion, but also wasted block space due to rolled back transactions and transaction fees paid by MEV seekers. This situation reflects the state of Ethereum before the emergence of Flashbots, but unlike it, there is no sandwich attack situation on L2 due to the current lack of a memory pool.
3) How big is the MEV on L2?
Gaining insight into MEV activity on L2 is critical. However, to date, there is no consensus figure for L2 MEV verified by multiple sources and robust methods. In addition, real-time monitoring data similar to Ethereum (e.g. mev-inspect, libmev, eigenphi 2) is also lacking in terms of MEV transaction volume and seeker profits on L2.
So far, some datasets and studies on L2 MEV include:
Open source datasets built by hildobby on Dune Analytics (inspiration links: Sandwiched 1 | Sandwiches | Atomic Arb 3).
A research paper funded by Flashbots, Quantifying MEV On Layer 2 Networks 1, by Arthur Bagourd, Luca Georges Francois, quantified MEV on Polygon, OP Mainnet, and Arbitrum using the mev-inspect implementation.
The research paper, Rolling in the Shadows: Analyzing the Extraction of MEV Across Layer-2 Rollups 3 , by Christof Ferreira Torres, Albin Mamuti, Ben Weintraub, Cristina Nita-Rotaru, and Shweta Shinde, quantifies the activity on L2 and discusses a novel MEV strategy that exploits the sequencer role and its L2 batch confirmation latency.
In addition to the above resources, Sorella Labs will soon release their MEV data indexing tool Brontes, which will be an open source repository available for Ethereum mainnet and L2. Flashbots and the Uniswap Foundation are seeking grants to expand the classification and quantification of L2 MEV. If you have done work in this area or are interested in collaborating, please contact the Flashbots market research team (@tesa_fb on Telegram)!
While further validation is still necessary, hildobbys dataset on Dune Analytics serves as a valuable initial benchmark:
Over the past year, atomic arbitrage MEV volume on the six major L2 networks (Arbitrum, OP Mainnet, Base, Zora, Scroll, and zkSync) has reached over $3.6 billion, accounting for 1% to 6% of all DEX volume on each chain. This MEV volume is mainly concentrated in Arbitrum and OP Mainnet, but has recently shifted to Base and zkSync.
Compared to Ethereum, sandwich transactions on L2 are significantly lower, with atomic arbitrage transactions being four times higher. This difference is due to L2s single sequencer setup, which inherently does not introduce a mempool, so searchers will not be able to exploit sandwich MEVs that observe user transactions from the mempool (unless there is a mempool leak or sandwiches from a single sequencer). Instead, strategies like atomic arbitrage, blind rollbacks, statistical arbitrage, and liquidations are the most viable options for searchers on L2.
3. Evaluate the MEV market size: How much MEV revenue is left on L2?
Although it is very difficult to accurately quantify the MEV market, we can refer to the data of other ecosystems with MEV solutions for size comparison:
On Ethereum L1, annual validator revenue from MEV-boost blocks is approximately $968 million (estimated using an ETH price of $3,500); and the median value of a MEV-boost block is 4 times higher than the value of a normal validator block.
On Solana, the additional MEV revenue collected by validators through Jito’s bundling service, based on an expected 50,000 SOL per week, is approximately $338 million (estimated using a SO L0 price of $130).
While exact figures for Base’s MEV trading volume are not yet available, the market size can be estimated by analyzing the revenue of the BananaGun Telegram Bot, one of the most active bots in this space. The bot’s trading volume on Base L2 is comparable to its trading volume on Solana, steadily generating over $1 million in daily trading volume, and therefore over $10,000 in daily fees on each chain.
Note that there may be significant differences in the market share of Banana Gun Bot on Solana and Base. For example, Solana has several other important Telegram bots, such as Sol Trading Bot and BonkBot, while there may be fewer Telegram bots supporting Base. Therefore, Banana Guns trading volume cannot be calculated in proportion to their revenue on Solana to Bases total MEV revenue.
However, consider another way of estimating: in March alone, the Banana Gun Telegram Bot paid over $23 million to Ethereum builders and validators! When comparing its volume on different chains, its volume on Base actually surpassed Ethereum during the weeks of March 26th and April 1st (as seen in the peaks in the chart above), indicating significant MEV earning potential on Base.
Of course, there are significant differences between the MEV ecosystems of Base and Ethereum. Compared to Ethereum, the MEV competition on Base may be milder, which means that bots need to bid lower to validators. However, Memecoin trading bots mainly operate through blind buying and arbitrage, which is still feasible within Base’s sequencer setting.
4. Summary
1) Calling for attention to MEV
Ethereum has built a complex MEV ecosystem where infrastructure tools serve participants at different levels of the supply chain. At the protocol level, MEV-boost allows validators to outsource the block building process through auctions. For seekers, bundling services similar to Jito Labs on Solana and FastLanes on Polygon, provided by Ethereums block builders, enable seekers to propose MEV strategies with rollback protection.
These services ensure that builders simulate transactions and only process those that will not be rolled back. In addition, private RPC services like Flashbots Protect provide retail users with a way to avoid public memory pools and avoid being sandwiched. The current form of L2 still requires considerable progress in developing a similar mature MEV infrastructure.
2) Why should we consider MEV solutions for L2?
Even without a memory pool, MEV still exists. MEV strategies such as statistical arbitrage (CEX-DEX arbitrage), atomic arbitrage (DEX-DEX arbitrage), and liquidations play a role in maintaining market efficiency, clearing out stale liquidity in AMM and lending markets.
However, in the absence of mature MEV infrastructure like bundling services, negative externalities emerge. Without a memory pool, most MEV strategies default to spamming strategies, leading to:
Increased rollback rates in the network;
High gas fees, leading to network congestion.
By introducing bundling services and shifting the pressure of MEV competition from the chain to the sidechain, users can be protected from the high gas fees caused by MEV robot racing. Seekers can also get higher profits through rollback protection because the cost of failure can be reduced.
For L2s that wish to adopt a shared sequencer, most solutions today require users to submit their transactions to a public mempool, reintroducing sandwich attacks. In this case, a private RPC like Flashbots Protect could provide protection to users by sending user transactions directly to block builders to prevent sandwich attacks, and even provide refunds of MEV or priority fees to provide users with better execution and better prices.
However, there are still open challenges for more complex MEV infrastructures:
First, the economics of search change as more value is paid to the sequencer, reducing the marginal profit of the searcher over time. This also raises the question of the sustainability of highly competitive search strategies in the long term. We expect market forces to be at play here, with common search strategies paying most but not all of the value to the sequencer, and uncommon search strategies paying less.
Furthermore, the order flow dynamics of existing MEV infrastructure like Ethereum’s block construction market are still evolving rapidly. At the time of writing, they have contributed significantly to the centralization of the block construction market and the rise of private memory pools on Ethereum L1. How to ensure a competitive and fair block construction market remains an open challenge.
Finally, MEV solutions on L2 may also differ from those currently on Ethereum due to their faster block times, cheaper block space, and relatively more centralized governance. It is unclear whether fast block times, such as Arbitrum’s 250 ms blocks, are compatible with the current performance and requirements of existing MEV infrastructure. Moreover, the abundant and cheap block space provided by L2 changes the dynamics of search, making the spam problem more prominent and potentially requiring new solutions. More importantly, L2 is relatively centralized relative to other setups, such as Ethereum L1. In this case, it may be possible to impose additional requirements on MEV service providers, such as requiring block builders not to perform sandwich attacks on users, in order to achieve fair market outcomes.
This article is sourced from the internet: L2 status and challenges: Dynamic analysis of MEV after Dencun upgrade
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