What changes have occurred in the Rollup ecosystem from Economics 1.0 to 2.0?

Original author: DavideCrapis

Original source: notion

Original title: RollupsareReal—RollupEconomics2.0

Translation: Yvonne, MarsBit

In February 2022, Barnabé proposed a Rollup economics framework for thinking about resource pricing and value flow in economies relying on L1. This framework introduces some key concepts to think about the interaction of MEV, L1 and L2 costs, and operator revenue and costs in L2. It is a simple framework for a simple world: a centralized Rollup running on independent auxiliary chains. Many things have changed in the past 18 months: shared ordering, decentralization, proof/data aggregation, Rollup alliances, governance.

We present a new framework that will help people understand this new world where Rollup projects are ready to scale. There are still many experiments going on, but several patterns are emerging. We will analyze the main patterns in the hope of providing a tool to help understand the direction of development and to help identify/answer open questions. This is the first article in the “Rollups are Real” series. Subsequent articles in this series will delve into aggregation and interoperability, decentralization and MEV elasticity, governance and resource allocation.

Returning to Basics: Revisiting Rollup Economics 1.0

The initial Rollup economics framework had three entities: users, Rollup operators, and the base layer. It also had a similar simplified view of value flow: L2 fees and MEV, operator costs, and data publishing costs. This is a simple framework, but it is useful to anchor from here because things will quickly become more interesting and complex.

Rollup economics flowing in the original framework

In the basic flow, one can measure the surplus of the Rollup protocol and infer related concepts such as MEV extraction and distribution, L2 issuance, L2 congestion fee distribution, and the time range in which the Rollup *maintains a balanced budget* or *operates with a surplus budget* (the L2 ecosystem is a growing economy, and it may find it useful to have a surplus budget to be allocated by the community to public goods funds, development, and growth).

Accumulated protocol surplus = L2 fees – operating costs – data costs

The Rollup protocol can control L2 fees (including congestion fees and MEV) and operating costs (including issuance and rewards to operators). Whether the protocol aims for a balanced or surplus target, L2 operations require coordination techniques that allow (1) *optimal setting of L2 congestion fees*, (2) *MEV extraction and redistribution*, and (3) *reducing data costs through optimization and strategic publishing*. These are the main economic design choices that different L2 ecosystems are experimenting with. In the future, protocols may want to reduce the uncertainty of data costs, for example, by using block space derivatives.

In the past 18 months, there has been a major change. Similar to building blocks in L1, we have seen the decomposition of the role of Rollup operators into more specialized roles. As the economy grows, it naturally becomes more specialized, which is a good thing because if we can design around it, separating concerns will bring a more resilient system. But now the design space is much larger, so we need a new map to guide us through this process.

Rollup is developing

As Rollup matures and auxiliary rounds begin, the complexity within each Rollup and between Rollups of the same type is increasing, which we call “Rollup federation.” The shared Rollup architecture between Rollups of the same type aims to improve “security” (through shared governance and community consistency), “efficiency” (through shared functionality and economies of scale), and “user experience” (through better interoperability and less fragmentation). At the same time, independent providers are developing infrastructure to offer one or more of these benefits to any combination of services that choose them, regardless of their type. We call them “Rollup coops”. We will start with an update on individual Rollup economics and delve into these models.

Independent Rollup

Individual Rollups are removing auxiliary rounds to increase security and decentralization. From an operational/economic perspective, the main cost areas include:

– Ordering: This increases operational costs and (when decentralized) economic costs to incentivize sorters.

– Data Availability (DA): Rollups must publish data on the base layer, resulting in data costs, which are the main cost item discussed in the original framework.

– State Verification (SV): This directly increases the operational costs of zk Rollup through proof costs.

In all these cost areas, single Rollup operations face a significant trade-off between security and efficiency. For example, they may choose to use a lower security data availability layer at lower cost. Data publishing costs (which we simply call data costs, although they include L1 computing costs associated with publishing) have historically been the highest item. With the launch of EIP-4844 on Ethereum soon, this will be significantly reduced, followed by complete Danksharding, which will provide the cost efficiency required for Rollup to scale and enable new use cases. In the long run, the efficiency of data costs and related services may be achieved through “aggregation” of off-chain innovation, unlocking economies of scale.

Specific examples of aggregation include: shared ordering services; for optimisticRollup, an interesting idea is “shared batch publishing,” which can provide significantly faster batch compression benefits, especially for smaller players, by offering lower costs and higher security through fast data publishing; for zk Rollup, sharing proofs by aggregating many snarks into a larger proof before publishing to L1 is one of the most exciting extensions, especially because they can be recursively aggregated, providing huge benefits in the efficient utilization of the L1 data market, but at the cost of more off-chain computation. It seems clear that companies will eventually choose to adopt shared services as part of a federation or economic alliance.

One possible direction for the Rollup ecosystem is to have more independent Rollups that are closely integrated with L1. We haven’t seen many implementations yet, but there are at least two interesting architectures. One is the “base Rollup,” which delegates block ordering to L1, allowing for MEV extraction using the transaction supply network of L1, but still retains an agency to set L2 congestion fees. The other more extreme case is where the Ethereum protocol itself specifies the Rollup. In discussing the elasticity and decentralization of Rollup MEV, we will delve into the economics of these patterns.

Rollup Cooperatives

The first type of integration between two groups is pure economic integration, such as economic cooperation.

“A cooperative is an entity that shares or works together to achieve common goals, such as economic benefits or savings.” (From Wikipedia)

In its simplest form, these combinations have some “joint purchasing agreements” for services. Assuming there is a shared batch publishing service, a Rollup can subscribe to this service and obtain lower data publishing costs. There can also be deeper economic integration, such as a “shared ordering service” that provides cost-effectiveness and makes atomic settlement of transactions between Rollups easier, thereby reducing trade barriers between Rollups. This mental model is an economic alliance, like the European Economic Community (the precursor to the European Union) or other similar common market alliances.

Economic flow of Rollup communities using shared services (ShS)

We can use intermediaries (such as shared sorters, posters, or even validators) to extend the simple model of the independent Rollup economy (when it does not operate on a shared bridge, see the next section). In this case, there are two new economic impacts on the Rollup ecosystem.

– Rollup cost structure: The costs for the Rollup operator now include operational costs, service costs, and data publishing costs.

– Shared service economy: The new entity needs to achieve budget balance.

Shared service surplus = Rollup service costs + Rollup B service costs – operational costs ShS – data costs ShS

Examples of such services include the Espresso sequencer, which is a shared service for sorting and publishing, either for shared batch publishing or shared proof. In all these cases, shared services bring two important economic issues.

1) Cost sharing of services on L2: The total service costs need to be shared among the clusters adopting shared services in an economic and fair manner.

2) Decentralization of ShS: Achieving an appropriate balance between performance and robustness based on services. The threshold is lower than the base layer, but it includes incentives and MEV management.

We will delve into these and related open issues in the following articles.

Rollup Federations

Rollup federations differ from economic organizations in that they have both economic integration and some form of political integration. Their mindset is that of a national alliance.

Technically, political integration is achieved through shared bridges, but it also requires a shared governance system (the central governing body of the federation). Here, we will set aside considerations of politics and governance and assume the existence of shared bridges, focusing instead on the implied economic relationships. This federated aggregation architecture appears in all major aggregation systems, which are becoming platforms for deploying interoperable peer aggregations (as opposed to subordinate aggregations, see RaaS and L3 in the next section).

The emerging architecture of major L2 ecosystems

For example, Optimism Superchain, Polygon 2.0, StarkWare SHARP, zkSync Hyperchains, and other related projects share similar patterns in their architectures. We have distilled it into the diagram below. To isolate the impact, we have made a realistic assumption that the federated Rollup automatically selects shared services and does not incur direct data publishing costs.

Federated Rollup shared services and bridging to the base layer

The existence of shared bridges introduces additional economic variables. In particular, native L2 tokens, such as OP in the Optimism ecosystem, provide important decision-making power through governance, enabling the allocation of resources, roles, and economic flows within the ecosystem (e.g., OP governance is a governance experiment based on hybrid token identities). Once the Rollup technology stack matures and primary security concerns are addressed, the secondary concern is robustness, which may involve some degree of decentralization.

When Rollups consider building decentralized services (for ordering, proving, or verifying), they will need to run consensus protocols. At this point, ecosystems with sufficient scale see an opportunity to “upgrade” their native tokens into productive assets, as demonstrated by Polygon 2.0’s plan for POL. This is not the only way to achieve decentralized L2 services, as Ethereum L1 can leverage better security properties to do so. However, using native tokens may be an attractive direction for larger ecosystems that wish to retain more internal control/governance, as well as related reward/incentive mechanisms.

Native token value change = change in demand – net issuance

Native tokens are important economic tools that help guide the L2 ecosystem/economy. Issuance can be used to reward service operators and provide funding for ecosystem support projects or public goods. However, when native tokens support decentralization through some form of native proof-of-stake protocol, security may be diluted. Even if native tokens are used only for governance, excessive dilution can lead to more budget-constrained holders selling, potentially resulting in ownership concentration. Therefore, having a symbolic issuance plan that aligns with demand growth seems important. Finally, another important consideration is that making the L2 economy more dependent on native tokens (vs. ETH) would also reduce its robustness to certain failure modes, as exiting L1 may not be an option. In extreme cases, L2 is still protected by Ethereum but loses the security provided by ETH as an external currency.

More Layers

Another area of active development is centered around application-specific or custom execution environments, which ultimately (if not directly) depend on the underlying layer. These applications are typically aimed at low-cost and easy-to-deploy applications that are willing to sacrifice security. Think games, social media, and NFT products that don’t need to bootstrap their own service economy or attract/ensure a large amount of liquidity.

There are different styles, including L3, validums, and Rollup-as-a-service (RaaS) platforms. For example, Arbitrum Orbit is a platform that allows L3 chains to stay on Arbitrum L2 (One or Nova) and has some configurability, such as the choice of an Arbitrum-authenticated data availability committee (DAC) instead of Ethereum L1 as the data availability layer. StarkNet and other zk Rollup projects have also been trying to enable L3. An extreme example in terms of ease of deployment is AltLayer or Caldera, which have codeless solutions to deploy “customizable” Rollups and delegate the trade-offs of security and efficiency to the users themselves.

We focus on L3 systems. This is actually an additional layer on top of L2. From the perspective of L2 Rollup, this is an additional source of L2 fees. L3 is a new entity in the Rollup ecosystem and has its own budgetary constraints:

1) L3 revenue may come from fees and subscriptions for games, or other mechanisms such as revenue sharing for NFTs.

2) L3 costs include the operational costs of the system plus the computation/data fees of L2. These costs can be borne directly by L3 or, in the case of hosted services, paid by the RaaS platform. Another service provider that must balance the budget.

This is another example of economic specialization in the Rollup ecosystem. In the following articles, we will delve into how these solutions actually provide economic efficiency and usability, thereby contributing to the scalability of Ethereum.

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