Title: “Aggregation, Settlement, and Execution: Unleashing Innovation in Modular Stacks”
Written by: Bridget Harris
Translated by: Chris, Techub News
When it comes to attention and innovation, different parts of the modular stack are not created equal. While there have been many projects focused on innovation in the data availability (DA) and sorting layers, it is only recently that the execution and settlement layers have started to gain attention as part of the modular stack.
In the realm of shared sorters, there is fierce competition with projects like Espresso, Astria, Radius, Rome, and Madara vying for market share. Additionally, there are RaaS (Rollup-as-a-Service) providers like Caldera and Conduit, which offer shared sorters for building on top of their platforms. These RaaS providers can offer more favorable fees for Rollup because their underlying business models do not solely rely on sorting revenue. Many Rollup options also choose to run their own sorters to capture the fees generated.
Compared to the data availability (DA) space, the sorter market is unique. The DA space is dominated by a few major players, namely Celestia, Avail, and EigenDA. This makes it difficult for smaller newcomers to disrupt the space, as they either leverage existing choices (like Ethereum) or choose one of the mature DA layers based on their own technical stack and consistency. While using a DA layer can save a significant amount of costs, outsourcing the sorter portion is not an obvious choice from a cost perspective (rather than security) due to the opportunity cost of giving up sorter revenue. Many still believe that DA will become a commodity, but we see in the world of cryptocurrencies that a strong liquidity moat combined with unique (hard-to-replicate) underlying technology makes commoditizing a layer in the stack extremely challenging. Despite these debates, there are many DA and sorter products launching. In short, “there are multiple competitors for each service in some modular stacks.”
I believe the execution and settlement (as well as aggregation) layers have yet to be fully explored, but they are starting to iterate in new ways to better align with the rest of the modular stack.
Execution and settlement are closely intertwined, with the settlement layer acting as the place to define states and execute final results. The settlement layer also has the ability to enhance the functionality and security of the execution layer’s outcomes. In practical applications, this means the settlement layer can play multiple roles, such as resolving fraud disputes in the execution layer, verifying evidence, and connecting other execution layer environments.
It is worth noting that some teams choose to directly support the development of custom execution environments in their native protocol environments. For example, Repyh Labs is building an L1 called Delta. This is essentially a reverse design of the modular stack but still offers flexibility and the advantage of technical compatibility, as the team does not need to spend time manually integrating each part of the modular stack. Of course, the downside is being isolated from a liquidity perspective and unable to choose the modular layers that best suit your design, as well as the high cost.
Other teams choose to build L1s specifically for core functionalities or applications. Hyperliquid is an example, as they have built a dedicated L1 for their flagship native application (a perpetual contract trading platform). While their users need to perform cross-chain operations through Arbitrum, their core architecture does not rely on Cosmos SDK or other frameworks, allowing for iterative customization and optimization for their primary use cases.
Progress in the execution layer
In the previous cycle, generalized alternative Layer1s (alt-L1s) only surpassed Ethereum in terms of higher throughput. This meant that if projects wanted significant performance improvements, they essentially had to build their own Layer1 from scratch, primarily because Ethereum itself did not possess this technology. Historically, this simply meant embedding efficiency mechanisms directly into the general protocol. In the current cycle, these performance improvements are achieved through modular design and implemented on major smart contract platforms like Ethereum. This allows both existing and new projects to leverage the new execution layer infrastructure without sacrificing Ethereum’s liquidity, security, and community moat.
Currently, we are also seeing an increasing number of mixed and matched virtual machines (VMs) as part of a shared network, providing developers with flexibility and better customization at the execution layer. For example, Layer N allows developers to run general Rollup nodes (such as SolanaVM, MoveVM, etc., as execution environments) and application-specific Rollup nodes (such as perpetual DEX and order book DEX) on top of its shared state machine. They are also working towards achieving full composability and shared liquidity among these different VM architectures, which is a historically challenging on-chain engineering problem to solve at scale. Each application on Layer N can asynchronously pass messages in terms of consensus without delays, which is typically the “communication overhead” problem in cryptocurrencies. Each xVM can also use different database architectures, whether it’s RocksDB, LevelDB, or a custom synchronous/asynchronous database created from scratch. The interoperability part works through a “snapshot system” (an algorithm similar to the Chandy-Lamport algorithm), where chains can transition to new blocks asynchronously without system pauses. In terms of security, fraud proofs can be submitted if state transitions are incorrect. With this design, their goal is to minimize execution time while maximizing overall network throughput.
Move language is being utilized by Movement Labs to drive customization progress in the execution layer/VM. The Move language was originally designed by Facebook and used in networks like Aptos and Sui. Compared to other frameworks, Move has structural advantages, particularly in terms of security and developer flexibility. Historically, two main issues in building on-chain applications using existing technologies were security and development flexibility. Importantly, developers can also write in Solidity and deploy on Movement to achieve this. Movement has created a fully-compatible bytecode EVM runtime to enable this, which can be used alongside the Move stack. Their Rollup M2 utilizes BlockSTM parallelization, allowing for higher throughput while still having access to Ethereum’s liquidity moat (historically, BlockSTM was only used in alt-L1s like Aptos, which lacked EVM compatibility).
MegaETH is also driving progress in the execution layer space, particularly through its parallelization engine and in-memory database, where the entire state can be stored in memory. In terms of architecture, they leverage:
Native code compilation for better L2 performance (programs can achieve significant acceleration if the contract is more computationally intensive, and still achieve over 2x acceleration if not highly computationally intensive).
Relatively centralized block production, but decentralized block verification and confirmation.
Efficient state synchronization, where full nodes do not need to re-execute transactions but need to know the state deltas to apply them to their local databases.
Merkle tree update structures, where their approach is a new trie data structure that is highly memory and disk efficient. In-memory computation allows them to compress the chain state into memory, so during transaction execution, they do not need to access the disk, only memory.
As part of the modular stack, another design that has been recently explored and iterated on is proof aggregation, defined as a prover that creates a single succinct proof from multiple succinct proofs. Let’s take a holistic look at the aggregation layer, its historical context, and current trends in the crypto field.
The value of the aggregation layer
Historically, in non-crypto markets, aggregators have had a smaller market share compared to platforms. While I’m not sure if this applies to all cases in the crypto space, it still holds true for decentralized exchanges, cross-chain bridges, and lending protocols.
For example, the total market value of 1inch and 0x (two major DEX aggregators) is around $1 billion, which is only a small fraction of Uniswap’s market value of around $7.6 billion. The same goes for cross-chain bridges: bridge aggregators like Li.Fi and Socket/Bungee have a smaller market share compared to platforms like Across. While Socket supports 15 different cross-chain bridges, their total cross-chain transaction volume is actually similar to Across (Socket – $2.2 billion, Across – $1.7 billion), with Across only accounting for a small portion of Socket/Bungee’s recent transaction volume.
In the lending space, Yearn Finance is the first decentralized lending yield aggregator protocol, with a current market value of around $250 million. In comparison, platforms like Aave (around $1.4 billion) and Compound (around $560 million) have higher valuations.
The same situation can be observed in traditional financial markets. For example, the market value of Intercontinental Exchange (ICE) and Chicago Mercantile Exchange Group (CME) is around $75 billion each, while aggregators like J.P. Morgan and Robinhood have market values of around $132 billion and $15 billion, respectively. In J.P. Morgan, which routes trades through various venues, the proportion of traded volume routed through it is disproportionate to its market value share. Robinhood handles approximately 119 million options contracts per month, compared to ICE’s approximately 35 million contracts – and options contracts are not even the core part of Robinhood’s business model. Despite this, ICE has a valuation that is roughly five times higher than Robinhood’s on the public market. Therefore, aggregators like J.P. Morgan and Robinhood, as application-level aggregation interfaces, route customer order flow to various venues, while having significant trading volumes, do not have valuations as high as ICE and CME.
As consumers, we place less value on aggregators.
This may not hold true if the aggregation layer is embedded within the product/platform/chain in crypto. If aggregators are directly integrated tightly into the chain, it is obviously a different architecture, and I’m curious to see how it develops. An example is Polygon’s AggLayer, where developers can easily connect their L1s and L2s into one network that can aggregate proofs and achieve a unified liquidity layer across chains using CDK.
In this model, products like Astria act as the #1 → #2 flow (unordered transactions → ordered blocks), execution layer/Rollup nodes are the #2 → #3 flow, and protocols like Nebra act as the last mile #3 → #4 (executed blocks → succinct proofs). Nebra could also be theoretically seen as a fifth step, where proofs are aggregated and then verified. Sovereign Labs is also exploring a concept similar to the last step, where cross-chain bridges based on proof aggregation are at the core of their architecture.
Overall, some application layers are starting to have control over the underlying infrastructure, partly because if they don’t control the stack, simply having the upper-layer application may bring incentive problems and high user adoption costs. On the other hand, as competition and technological advancements continue to drive down infrastructure costs, the cost of integrating applications/chains with modular components becomes more affordable. I believe this dynamic will become even more powerful, at least for now.
With all these innovations (execution layer, settlement layer, aggregation layer), higher efficiency, easier integration, stronger interoperability, and lower costs become possible. All of this ultimately leads to better applications for users and a better development experience for developers. It’s a successful combination that can bring more innovation and faster innovation speed.
