Can ZK, Agglayer and CDK help Polygon to rise from the ashes?

Author: Saurabh Deshpande & Siddharth, Decentralised.co; Translation: Golden Finance xiaozou

Back to March 2020. At that time, the market had just experienced a black swan event, and the COVID-19 pandemic triggered a global lockdown. "Unprecedented" is one of the words we hear most frequently. Just as global finance began to emerge from the shadow of the COVID-19 pandemic, the Federal Reserve made a massive bearish move. In this environment, BTC, ETH, and a few other tokens experienced their life cycle. But beyond the price, a huge technological change changed the way Ethereum scales.

Ethereum was far from solving its scaling problem in 2020. Polygon (then Matic Network) was launched at this time, which was one of the ways to scale applications using the Ethereum Virtual Machine (EVM). From 2020 to early 2021, Polygon was one of the few solutions that offered the same quality applications on Ethereum (like Aave) with low fees. This made Polygon stand out from other Ethereum scaling solutions.

From 2021 to 2023, Ethereum scaling competition has intensified significantly. Optimistic rollup (OR) launched a viable product before zero-knowledge rollup (ZKR). OR is designed to be simpler than ZKR. High-performance ZKR that is fully compatible with the EVM is considered to be a few years away. Stay with me; I will discuss OR, ZKR, and the differences between them later in this article. While OR is often considered an intermediate scaling option for scaling, they have accumulated a large number of users and capital. In comparison, ZKR has been mediocre. This can be seen by the total locked value (TVL) of the two solutions.

OR has locked about $35 billion in value, while ZKR has locked only $3.7 billion in value. As OR gains popularity with incentives and new narratives, more and more users are moving their assets to these new chains. Polygon is one of the first solutions to run as a sidechain, expanding its focus to long-term ZK solutions. Just like other ZK and scaling solutions, the network ceded ground to OR. It took time for all ZKRs to come online. Naturally, incentives were delayed. By the time ZKRs were launched, ORs were already mature and successfully attracted user attention.

Also, once ZKRs were released, they were almost indistinguishable from ORs in terms of user experience. It was an uphill battle for ZKRs to attract user attention. To do this, ZKRs needed to be unique to attract users. In addition, all ORs (and the new ZKRs) offer incentives for users and developers.

Polygon Labs has a variety of solutions, such as a PoS chain, multiple upcoming ZKR implementations, and a development toolkit. Looking at Polygon from the outside is confusing. To me, it seems like they have tried everything.

However, after digging deeper, I realized how the pieces line up.

This article will describe the evolution of the Polygon ecosystem and where it will develop in the coming months.

The Need for Speed

Everyone remembers the Crypto Kitties era: a harmless experiment that brought a sense of community to Ethereum users by allowing them to raise and trade unique digital cats. In December 2017, some kitties were sold for over $100,000, accounting for more than 10% of Ethereum’s gas consumption. The craze grew so intense that even the BBC had to write an article about it. Apparently, with high prices and high demand, Ethereum became unusable for regular users due to high gas fees.

Gas can be thought of like this: Imagine a city with a limited fuel resource and a free market. When citizens know that the supply is limited and commuting is inevitable, their bids for fuel increase, driving up prices. Just like traveling consumes fuel, all operations on Ethereum consume gas. Fuel is denominated in fiat currencies such as dirhams, Indian rupees, and US dollars, while gas is denominated in gwei (1 nano ETH). During times of network congestion, more people want to access the limited block space, and they are willing to pay a higher price for gas.

In 2017, it became clear that Ethereum, the world computer, needed a massive overhaul to scale so that everyone could use it, and it was a major research topic. A natural solution emerged by considering the following question: If one chain is processing 12 transactions per second, can we split that chain into multiple independent chains? If there are 100 chains, they will all produce 12 transactions per second, which will produce a total of 1,200 transactions per second. As the number of chains increases, so do the possibilities for scaling.

This is the general idea of ​​"sharding" the base chain. A shard is basically a small chain that runs in parallel with other small chains. However, making these independent shards part of the whole Ethereum by ensuring seamless interoperability is as difficult as scaling itself. For example, when a user needs to perform a transaction involving applications on different shards, it is very important how these chains interact with each other. This means breaking up the validator set into multiple parts to validate different chains.

While sharding is the ultimate solution, Ethereum will take several necessary intermediate measures to serve as building blocks of the sharding architecture. These intermediate measures are state channels, Plasma, and so on.

At the same time, a different school of thought began to form. What if we don’t break up the validator set, but reduce their computational burden? This is exactly what rollup proposes. Rollup uses Ethereum resources (gas) to publish transaction packages instead of using it for every transaction.

Therefore, the calculations required to make state updates (think of Ethereum’s state as the balance of each account, smart contract, and external account) are performed on a different layer from Ethereum, saving Ethereum’s resources. Ethereum now only needs to deal with a small number of rollups that interact with millions of users, without having to interact directly with these millions of consumers. Rollup helps Ethereum go from B2C to B2B.

Of course, this is not an easy task. When Ethereum validators no longer perform computations, how do users know that the people who perform computations are honest? When you and I use Ethereum, we are trusting Ethereum validators. Sure, we could run our own nodes to check that the validators executed our transactions correctly, but we don't. So, we ultimately trust the validators.

When you transfer an asset or exchange it for another, the validators are the ones who change the state of Ethereum, such as increasing or decreasing the balance of an account. When this computation is performed off-chain, users are essentially trusting the operators of that layer. Now, if we say that these layers are just extensions of Ethereum, then users should not be forced to trust anyone except Ethereum validators. This layer has the responsibility to prove that its operations comply with Ethereum's rules in some way.

How different rollups perform computations and prove to Ethereum that they have performed the computations correctly largely determines the type of rollup. ORs provide Ethereum with the results of their computations and the data needed to replay the transactions (they publish the results on Ethereum). Anything submitted by ORs is considered correct unless someone questions its execution, hence the name optimistic rollup.

The verifier typically has 7 days to dispute the result. Readers should note that as of June 2024, no other OR has implemented fraud proofs other than Optimism. Optimism has stage 1 fault OR fraud proofs, meaning that the training wheels are still intact and the Council can intervene if the fault proof system fails for any reason.

The other major category is ZKR. Zero-knowledge techniques allow us to prove anything without revealing the details of what we are trying to prove. For example, let's say Sid wants to prove to Joel that he knows the combination to the safe Joel bought for them. However, he doesn't want to reveal the combination because he's worried that their communications might be intercepted. How can he achieve his goal?

Joel can put something in the safe that Sid doesn't know (such as information written on a piece of paper). Later, if the information Sid gives can be matched with what Joel put in the safe, then Joel can confirm that Sid knows the combination without Sid revealing the combination itself. In broad strokes, this is how zero-knowledge proofs work. Instead of publishing all the data to validators to be able to replay all transactions, they submit proof of execution to Ethereum.

Anchors to Ethereum, L2 or Scaling Layer

Ethereum, as we know it today, has evolved along with the protocol and applications. Some projects have adapted and evolved as Ethereum has grown, while others have been left far behind. The story of Matic Network (now Polygon) is a great example of this. As the sun shines on Ethereum, the Polygon planet thrives.

The crypto asset and blockchain landscape has changed a lot since Ethereum launched in early 2015. Ethereum's scaling plans took a major turn in late 2020, when Vitalik wrote a rollup-centric Ethereum article, specifically mentioning that Ethereum's trajectory can be divided into two eras: before rollups and after rollups. If Ethereum is your anchor, you have to follow it. Polygon makes sure it adapts as the Ethereum roadmap changes.

It is clear that Ethereum needs to scale massively to become the world computer. Before understanding how Ethereum's path to scaling has evolved, we should review the basic meaning of scaling. Scaling is about the security guarantees of scaling Ethereum. Whatever approach we take, we should rely on the security of Ethereum to some extent. That is, Ethereum L1 should be able to have the final say over the state of the scaling layer.

Several approaches have been proposed, such as state channels, plasma, sidechains, and sharding. They were in different stages of development before Ethereum decided to support rollups.

Plasma and sidechains are similar approaches to some extent. Plasma is a separate chain where transactions are executed and compressed data is periodically published to Ethereum. Plasma chains pose challenges to data availability.

Data availability (DA) solutions typically separate consensus data from transaction data. As the size of a blockchain grows, storing and processing state becomes a challenge. Data availability solutions solve the scaling problem by separating the consensus layer from the data layer. The consensus layer handles the ordering and integrity of transactions, while the data layer stores transaction data and state updates.

All historical data of the Plasma chain is only available to the plasma operator and not to the Ethereum full node. The full node only knows compressed data. Therefore, users must trust the operator to maintain data availability. The security of the Plasma chain depends on the security of the root chain (Ethereum). Fraud proofs and challenges are resolved according to the rules of the root chain.

Sidechains are independent chains with their own consensus and validator set. They publish data on Ethereum regularly. The key difference between the two is that there is a separate validator set based on different consensus. Users must trust the sidechain validators to maintain the integrity of their transactions.

OR is superior to Plasma and sidechains in the following aspects:

1. Unlike Plasma, they avoid data availability issues by publishing all data on Ethereum.

2. Unlike Plasma and sidechains, users do not have to expand to a larger trust assumption; that is, they do not have to trust a new set of operators or validators.

This is why rollups are considered a superior form of expansion. Some might say they are an improved version of Plasma.

The state channel is a solution similar to the Bitcoin Lightning Network. Here is an analogy about the state channel. Suppose Sid and Joel are friends who run a sandwich shop and a coffee shop, respectively, next to each other. They liked the concept of cross-selling and decided to merge their menus because their customers often wanted something from both stores. So, when a customer ordered a sandwich at Joel's store, Joel gave the order to Sid, who served the sandwich.

However, customers only pay where they eat, even though their order may have come from another restaurant. Sid and Joel both keep a record of how much the other store's customers ordered from their own store. Instead of settling the bill immediately after receiving the customer's money, they settle the bill at the end of the day.

Sid and Joel both keep a bill for the sandwiches and coffee they served at the other store, which is equivalent to keeping a status document. Throughout the day, if Joel serves $200 worth of coffee to Sid's customers and Sid serves $250 worth of sandwiches to Joel's customers, then at the end of the day, Joel pays Sid $50 and the bill is settled. This is much more efficient than settling the proceeds after each cross-sale. The slips Sid and Joel open to each other are like channels between two nodes or accounts.

At a high level, two users or applications can open an off-chain channel, perform transactions, and settle on-chain when the channel is closed. This approach requires opening multiple channels between users (opening and closing channels are on-chain transactions) and is difficult to scale. As of June 2024, the Lightning Network has a capacity of only about 5K BTC. Roughly speaking, this means that it cannot handle more than 5K BTC of buy and sell transactions at the same time.

Polygon is one of the early scaling solutions to launch a mainnet. The development of Polygon, both in technology and in the ecosystem, has gone through four periods:

1. Matic Network

2. Polygon expansion

3. Embrace ZK

4. Aggregate all

Matic Network

Matic Network is a combination of Plasma and sidechain methods. Validators use MATIC tokens as collateral to verify transactions and protect the security of the chain. As an additional security measure, checkpoints (snapshots of the chain's state) are submitted to Ethereum. Therefore, once a checkpoint on Ethereum is finalized, that state is frozen on the Matic Network. After this point, blocks cannot be scrambled or reorganized.

In 2021, the Matic Network was rebranded as Polygon, but it was more than just a name change. The Matic Network is a single-chain effort to scale Ethereum, while Polygon has moved to a multi-chain ecosystem. In order to address the scaling problem from multiple angles, Polygon launched a software development kit (SDK) that allows developers to easily port their applications to Polygon.

In April 2021, a few months after Aave was deployed on Polygon, TVL jumped from about $150 million to nearly $10 billion. At the time, Polygon surpassed most blockchains in metrics such as active users and transaction volume. Even by June 2024, Polygon PoS still dominates in terms of daily active users. Readers should take this with a grain of salt, as there is no way to know the true number of active users. Data vendors typically track active addresses. One address does not necessarily mean one user, as a user may (and almost always does) have multiple addresses.

What exactly does an SDK do? SDKs provide building blocks for larger pieces of software (in this case, different types of chains). The Polygon SDK provides tools for developing two types of chains: 1. Independent chains with their own validator sets 2. Chains that rely on Ethereum security (L2) Sidechains and enterprise chains need more control over how they operate (who can participate, who can run nodes, etc.), and they will choose the first option. In contrast, emerging projects that lack resources or are satisfied with Ethereum's security and consensus rules will choose the latter. Embrace ZK As Polygon's PoS chain grows and attracts more and more users, Polygon Labs explores more ways to scale Ethereum. In 2021, when ZKR was still largely in the development stage, Polygon Labs allocated $1 billion in funds for ZK development. They acquired Hermez Network, Miden, and Mir Protocol. Although all of these teams operate under the ZK umbrella, they each have special purposes.

Hermez is focused on building a live zkEVM, and Mir is focused on building industry-leading verification technology, used by many other ZK teams to create a zkVM rollup with client-side verification - ZK in your pocket.

When Polygon Labs went all in on ZK development, many believed that ZK technology would take another 3 to 5 years to mature. On the other hand, despite the lack of fraud proofs, OR production is just around the corner. This begs the question, why would Polygon Labs pursue something that would take longer, rather than deploying an OR solution first and then doing ZK development in parallel?

The answer can be divided into two parts:

1. OR will be an incremental solution that is superior to Polygon PoS in terms of scalability and security.

2. ZKR is seen as the ultimate solution to win OR.

Yes, as long as ORs have fraud proofs, their security guarantees are better than sidechains (such as Polygon PoS), but the cost has not changed much for end users. It is important to note that fraud proofs are invalid for any OR except Optimism. In March 2024, Optimism began testing fraud proofs. Therefore, there is still time before all ORs have fraud proofs on their respective mainnets. Polygon PoS has already processed millions of transactions per day.

So if you think about a barbell strategy, where risk is typically distributed across very high-risk and very low-risk instruments in a portfolio, you’ll understand that this is what Polygon technology looks like.

Recall the difference between OR and ZKR, and how the former must submit all transaction data on Ethereum. As the volume of transactions on OR increases, the amount of data they must publish on Ethereum grows almost linearly. However, the size of ZK proofs grows quasi-linearly. Therefore, as the volume of transactions increases, ZKR is significantly more efficient than OR.

This makes ZKR more advantageous than OR. However, the number of people who fully understand ZK technology and can create an infrastructure layer that can handle hundreds of billions of dollars may be only in the three digits. ZK technology needs time to mature. Acquiring the ZK development team gives Polygon Labs a tactical advantage that few in the industry can enjoy.

(1) Rollup and Train

The most important Polygon technology is zkEVM. Why? Let's make an analogy. Old blockchains are like old engines and trains. They are slow and have low capacity, so they are expensive. But because they have been around for a while, a network of tracks has been built in many areas. Think of the EVM as a network of tracks; it conforms to the most widely adopted standards, so there are tools to facilitate its use. It is impossible to continue using these trains because they are too slow and too expensive.

OR is like an improved version of this train, using the same tracks as the earlier trains but 10x to 100x faster. However, this is ultimately not enough. We also need several orders of magnitude more speed and capacity to ensure fast and low-cost travel. ZK aims to achieve this. But the problem is that the trains no longer use the old network of tracks; they need some modifications. zkEVM allows ZK rollup to be used with existing EVM tooling.

From a security perspective, ORs cannot prevent accidents. They operate on the assumption that accidents will not happen. Fraud proofs are like Nolan's movies. They cannot prevent accidents, but they can allow the system to go back in time and solve the problem before the accident happens. On the other hand, ZK technology can prevent accidents from happening.

(2) EVM equivalence problem

Let's take a deeper look at the whole zkEVM business. The train track metaphor explains why we need to be compatible with the EVM. However, this compatibility is not 0 and 1, but can be seen as a spectrum. The prover is a key component of the ZK machine. It proves that an event occurred without revealing the content of the event. For example, if the protocol wants to confirm whether a user has certain wealth, a ZK prover can be seen as the first choice to do this without revealing the user's wealth.

Why talk about ZK? SNARK or STARK technology allows chains to create cryptographic proofs. Both technologies are ways to generate easily verifiable proofs. These proofs can be used to prove that transactions occurred on a certain chain. If we want to scale Ethereum, we can use this technology to prove that Ethereum-like transactions occurred on certain layers. These layers are rollups, and ZK technology allows rollups to compress transaction data by orders of magnitude, thereby scaling Ethereum. If the goal is to scale Ethereum, then the goal of zkEVM is to prove execution in a way that the Ethereum execution layer can verify.

When rollup is completely equivalent to Ethereum, it can reuse things such as Ethereum's existing clients. Full Ethereum equivalence means that the rollup remains fully compatible with Ethereum smart contracts and the entire Ethereum ecosystem. For example, the addresses are the same, wallets like MetaMask can be used on rollups, and so on.

Making proofs in a way that Ethereum can understand is challenging. ZK-friendliness was not one of the considerations when Ethereum was designed. This is why some parts of Ethereum are computationally intensive for ZK proofs. This means that the time and cost required to generate these proofs increases. Therefore, if a proof system must use Ethereum, then the proof system must be large. On the other hand, a proof system can be relatively lightweight, but it must build its own components to adapt to Ethereum.

Thus, different zkEVMs make trade-offs between the ease of using existing tools and the cost and difficulty of proofs. Vitalik explored the existing zkEVMs along these lines in a blog post. I'll spare you more details (we'll discuss this in a future post), but there are various types of zkEVMs (or provers). Type 1 is the most compatible but least performant prover, and Type 4 is the least compatible but most performant prover.

Type 1: These zkEVMs are completely equivalent to Ethereum.

Type 2: They are EVM equivalent, but not Ethereum equivalent. This means that minor adjustments to Ethereum are required to make proof generation easier.

Type 2.5: Similar to Type 2 except for gas costs. When it comes to ZK proofs, not every operation has the same difficulty level. This type of zkEVM increases the gas cost of certain operations, suggesting that developers should avoid them.

Type 3: This type of zkEVM changes Ethereum to improve prover times, sacrificing exact equivalence in the process.

Type 4: This method compiles source code written in Solidity or Vyper (Ethereum language) into another language. This type of prover completely reduces Ethereum's overhead and makes the prover the lightest of all types. The downside is that it looks completely different from Ethereum. Starting from the address, everything is different. Did you notice that Starknet requires a different wallet (such as Argent). Even the address looks different from the Ethereum address.

Polygon Labs recently released an upgrade that introduces a new era of verification technology using Type 1 provers. Using Type 1 means that any EVM chain, whether newly created using Polygon CDK or an independent L1 chain, can become Ethereum's equivalent of ZK L2.

Aggregate All

No single EVM chain is ready to take on the load of the entire Internet. Not even close. That's why we're moving to L2. Now, there are several L2s on the market, but the number of users and capital are not growing at the same rate. Liquidity, users, locked value - almost everything that makes a chain valuable - is scattered across multiple L2s. In a way, L1 and L2 constitute a paradox: the base layer cannot scale, and multiple chains may dilute value.

One ​​way to solve this paradox is to provide a service that supports the seamless flow of assets and information between multiple L1s and L2s, but most importantly, there is no rent-seeking, no mining fees, and ensures that these chains retain their sovereignty.

AggLayer is designed to do this.

AggLayer is a solution that enables secure and fast cross-chain interoperability. Interconnected chains share liquidity and state. Before AggLayer, sending assets between chains either required trust assumptions and wrapped assets from a third-party bridging service, or a fee-intensive, poor user experience from L2 to Ethereum and then bridging to the target chain.

AggLayer removes this friction in cross-chain transactions and creates a network of interoperable chains. How? We will go into more detail about how AggLayer works in a future post, but here is just a high-level overview. Currently, L2s are various different contracts on Ethereum. Moving funds from one L2 to another involves three separate security zones - two L2 contracts and Ethereum.

In the case of cross-chain transfers, the security zones are part of the infrastructure where validators intersect. Validity checks and sending transactions happen on these nodes. The result of different security zones is that when you sign a transaction to transfer assets from one L2 to another, Ethereum is involved. Behind the scenes, assets are sent from the source L2 to Ethereum, claimed on Ethereum, and deposited in the target L2. These are three different instructions, transactions, or intentions.

With AggLayer, the entire transfer process can be completed with a single click. AggLayer has a unified bridge contract on Ethereum that any chain can connect to. Therefore, Ethereum sees one contract, but AggLayer sees many different chains. A ZK proof called a "pessimistic proof" keeps the total funds locked in a unified bridge and secures the funds by treating each associated chain with skepticism. In other words, a pessimistic proof is a secure cryptographic guarantee that means that one chain cannot deceive the entire bridge.

With AggLayer, Ethereum does not need to be involved when transferring assets from one L2 to another because all L2s share state and liquidity. The above three transactions or intentions can be combined into one.

The endgame of AggLayer is this:

Sid wants to buy some NFTs on chain A, but all his assets are on chain B. He connects his Polygon wallet, presses the buy button, and places the NFT into his wallet. Prior to the purchase, the bridging of assets from chain B to chain A is completely abstracted away.

The advantages of AggLayer are as follows:

1. It transforms the zero-sum game of liquidity and user fragmentation into a more collaborative approach between chains.

2. Each chain benefits from security and tools while maintaining its own sovereignty without the need to issue bonds on early models like Polkadot.

3. It allows chains to interact with each other with lower latency than Ethereum.

4. It brings substitutability to bridged assets and improves user experience. Everything happens in a bridge contract, so there is no need for different versions of wrapped assets.

5. Brings better user experience to users because the bridge is abstracted.

Currently, rollup and validum publish their respective chain states to Ethereum separately. AggLayer aggregates chain states and submits everything to Ethereum in a single proof, which helps save gas costs for the protocol.

Even research based on game theory shows that cooperation is almost always the best way to survive and thrive. AggLayer is a positive sum because it:

1. It has reliable neutrality (not biased towards any specific project; any chain can be connected)

2. It unifies liquidity and status, allowing new chains to guide users and the liquidity of any associated chains.

While other multi-chain ecosystems impose fees on chains (so these fees are ultimately passed on to downstream chain users), AggLayer is designed to be as minimal as possible while providing secure, low-latency cross-chain interoperability.

There has been a recent trend of apps launching app chains, and app chains are becoming more and more general purpose. Aevo, dYdX, and Osmosis are the main examples of this trend. Jon Charbonneau points out:

● Applications need flexibility and sovereignty, so they launch their own app chains.

● App chains show growth in users and activity, and want to capture more value by allowing others to build “on top of them”.

● Then, the app chain becomes a general purpose chain.

As Lanre said, the market seems to want applications to become application chains and then become general chains. If I extend this trend to the extreme, we will be left with only a few general chains. Although multiple chains can exist, liquidity and users remain the same and are shared between these chains. The greater the number of chains, the worse the overall crypto user experience.

As we said before, this is because liquidity and users are shared between multiple L2s, resulting in poor liquidity for many L2s. There has to be a solution to bring all of this together, and AggLayer is a step in the right direction. There are many reasons why applications need dedicated block space.

For example, a trading app should not be forced to compete for precious block space when there is a hot NFT minting on the same chain. Running a liquidation or closing a position should not be affected by other activities on the chain (in terms of fees or throughput). But if many applications are moving in the direction of application chains, they will face the risk of fragmentation.

Therefore, AggLayer integrates these different chains. It is a simple solution that allows game chains and DeFi chains to avoid direct competition for block space, but still achieve cross-chain interoperability.

On one hand, AggLayer can help unify cross-chain liquidity, and on the other hand, Polygon CDK can be used to launch chains.

Polygon CDK is a collection of open source technologies that have been evolving over the years. It started as an SDK and transitioned to a super network before taking on its current form. Polygon CDK allows developers to build two types of L2: rollup and validium.

The most important property of Polygon CDK is its flexibility. Developers building new chains (L2) can customize different options through four parameters: VM, mode, DA, and gas tokens.

● VM (Virtual Machine) is the environment in which transactions are executed. Polygon CDK will allow developers to choose from different VMs, such as zkEVM.

● Mode (mode) refers to choosing between validium or rollup. The difference between the two is what kind of data they publish on Ethereum. Rollup publishes compressed transaction data on Ethereum, providing more security for rollup mode. Validium, on the other hand, publishes this data on a separate layer, such as their own DA layer.

● DA (Data Availability) is a key aspect of scaling, where the consensus layer is separated from the data layer. Full nodes on chains like Ethereum and Bitcoin store all data so that they can independently verify all transactions. Polygon CDK allows blockchains to build their own custom DA committees or use DA solutions like Celestia.

●Gas token customization refers to the ability for a blockchain to charge gas fees denominated in the chosen token. For example, Polygon CDK lets developers let users pay for gas in their chain's native token instead of ETH.

●Collators, or operators that decide the order of transactions and execute them, are currently centralized. In the future, other teams or individuals may be able to run sorters.

In addition to this modularity and sovereignty, there are other advantages to building with CDK. Polygon CDK provides an opt-in feature for chains that allows them to use AggLayer's unified single bridge contract. This eliminates the need to have different versions of wrapped assets. This improves the user experience of CDK application chains.

Note that AggLayer’s unified bridge contract lends this capability to assets. Chains built with CDK must “opt in” to use this capability. They can choose to have their own bridges and maintain different assets. Other solutions, like Arbitrum, have USDC, USDC.e, and other variants of USDC. Typically, users must swap between these variants when bridging back to the mainnet.

For example, using Polygon CDK, appchains targeting lending and derivatives can choose rollup mode (all data is published on Ethereum), use Polygon zkEVM as the virtual machine (VM), and charge gas fees in its native token instead of ETH. However, a specific NFT appchain may adopt a validium mode, which can choose to publish data on Celestia or a separate Data Availability Committee (DAC), and use ETH as its gas token.

The sorter is currently centralized (as it is across all major ZK rollups). Eventually, CDK chains will be able to use a shared sorter if they so choose. It is important to note that aggregation is not inconsistent with modularity or sovereignty.

As of March 2024, 9 teams have built chains using Polygon CDK, and another 20 teams are in various stages of development. The CDK framework is completely open source and anyone can use it to build a chain.

It is critical that the MATIC token upgrade to POL. Currently, MATIC protects the security of the Polygon PoS chain. The proposed Staking Hub architecture has not yet been provided, but the proposal indicates that POL will play an integral role.

Ecosystem

Note that this is only a representation of the Polygon ecosystem. It is not exhaustive.

Developers are the lifeblood of any ecosystem. Developer activity is often a forerunner to on-chain user activity. Despite the market being in the doldrums for much of 2022 and 2023, the Polygon ecosystem is second only to Ethereum in terms of the number of new developers joining.

Source – Electric Capital

If developers are the leading indicator of the future, then users are the feedback loop of the blockchain. Polygon’s user activity remains high. The only EVM chain with higher user activity than Polygon is the BNB chain. Note that Polygon here only refers to Polygon PoS. As more blockchains connect to AggLayer and/or use CDK, this number could rise significantly in the future. Ultimately, developers want to customize the network to suit their needs. And this is exactly what Polygon optimizes for with CDK.



Data as of April 2024

Compared to other L2s or chains like Solana, Polygon's DEX activity is still low.

Interestingly, Quickswap is the leading DEX with about 60% of the volume. Generally, Uniswap dominates on the EVM chain.



Source – DefiLlama (data as of April 2024)

The chart below compares DEX transaction volumes on different EVM chains. Arbitrum is the leader, followed by Polygon. Since incentives drive everything in crypto, it’s worth noting that while Arbitrum offers trading incentives to DEX protocols and users, Polygon stopped offering incentives in 2022. Volumes have largely remained organic.



Data as of April 2024

Total value locked (TVL) is not a good indicator of whether a chain is successful because it doesn’t tell you the quality of the funding. That said, much of the money in crypto can be considered mercenaries. Capital flows to where there are incentives. Either the protocol is offering incentives or users are performing sybil operations for the sake of airdrops. Nevertheless, a long period of high or medium TVL means that users favor the chain or protocol in some form. The following chart shows the weekly TVL of different L2s.



Data as of April 2024

Most of the TVL in Polygon's lending applications comes from Aave. Aave accounts for 87% of Polygon's total lending TVL.



Data as of April 2024

In terms of NFT transaction volume, the leading chains are Bitcoin and Ethereum, mainly because NFTs are priced in their native assets (BTC and ETH), and the liquidity of these assets is almost always the highest in the industry. When we look at the number of transactions, Polygon is ahead of its EVM peers.



Data as of April 2024

Games are the main contributors to the growth of Polygon PoS. Since the beginning of 2024, the number of unique addresses interacting with games on Polygon has grown fivefold, from 80,000 to nearly 400,000, while Matr1x and Sunflower Land have attracted more than one million users during their lifetimes.

A major driver of this growth has been Polygon Labs’ partnership with Immutable. Immutable offers a suite of products for game developers, from NFT minting mechanisms to wallets to SDKs, everything a game developer needs. It also provides all blockchain-related support so that game developers can focus on the gaming side of things, without having to worry about the blockchain side of web3 gaming.

The ecosystem already has over 40 playable games, with several more in development. Immutable’s zkEVM, built using Polygon CDK, is live on mainnet for early access. At this stage, custom smart contract deployment is limited to a select group of game studios.

Beyond DeFi, Gaming, and NFTs

We often talk about cryptocurrencies not having a substantial impact on “normal” life. Decentralized Physical Infrastructure (DePIN) is one area that is slowly changing that perception. Blockchains excel at aligning incentives and ensuring those incentives are delivered according to pre-determined protocols.

DePIN projects sit at a critical intersection of the physical and digital realms. Typically, users help the network grow through some form of resources, while the network incentivizes users through inflationary tokens and user revenue. The sustainability of DePIN projects depends on whether they can attract paying users.

In terms of DePIN-related transactions, Polygon is significantly behind DePIN leader Solana. For context, in February, Solana supported over 4 million DePIN-related transactions; in comparison, Polygon only supported about 39,000.

DIMO, aka Digital Infrastructure for Moving Objects, leads Polygon in the DePIN adoption metric.



Data as of April 2024

It enables mobile objects to share data in a privacy-preserving manner. The first use case is cars, where drivers use DIMO devices and share data with stakeholders such as manufacturers and policy issuers. Currently, nearly 70,000 drivers use DIMO to share data with applications such as marketplaces, insurance, and peer-to-peer ridesharing. In return, they receive DIMO tokens.

Although DIMO’s applications began with cars, it can be extended to any moving object, including drones, and may find applications in areas such as supply chain management, smart mobility, and autonomous vehicles.

Other DePIN projects on Polygon include:

● Fleek Network is a decentralized hosting platform that serves websites and web applications through a globally distributed network of nodes, providing fast, secure, and redundant access.

● GEODNET aims to improve GPS accuracy by building a decentralized real-time kinematic network and token incentives.

● Space and Time, which aims to create a global transparent data warehouse that does not belong to a single entity.

● XNET, dedicated to improving mobile connectivity.

Right now, networks like Solana are leading the way in DePin. Part of what will incentivize developers to build on Polygon in the near future is its EVM compatibility. The ability for users to get paid in tokens and instantly access the number of applications built on the Ethereum network (and all of its chains) could be a powerful draw. That being said, it remains to be seen how this space will pan out for Polygon. It’s still early days.

Challenges

Of course, all of this change comes with its fair share of headaches. Like any growing and evolving ecosystem, Polygon faces some challenges. Here are some.

Low frequency of proof submission

Finality on Polygon zkEVM can be roughly divided into three phases -

1. Trusted state of transactions having finality on L2

2. Virtual state of Ethereum receiving transaction data from L2

3. Unified state of Ethereum receiving proofs verifying data

For practical purposes, users can continue to interact with L2 applications after the first phase. But if they want Ethereum’s assurance, they need to wait. Transactions on L2 will only be finalized on Ethereum after the third phase. Polygon zkEVM submits proofs to Ethereum approximately every 20 to 30 minutes, which means that users have to trust the Polygon zkEVM sequencer for 20 to 30 minutes between batches.

Why don’t they publish batches more frequently? Each batch has a fixed cost, spread over the number of transactions. Submitting batches more frequently means more fixed costs, which will be spread over the same number of transactions, increasing the cost of each transaction.

If Polygon zkEVM (and this also applies to other rollups) needs to submit proofs on Ethereum more frequently, then there must be more activity or the cost of submitting proofs needs to drop significantly. As ZK technology matures, the cost of proofs may decrease, but it is still high at present. Therefore, rollups need more users to submit proofs to Ethereum more frequently and keep transaction costs low.

Polygon PoS Reorganization

Polygon is notorious for its frequent reorganizations. Although the risk has been largely mitigated, it has not been completely solved. I will first explain why reorganizations are common on various chains, and then explain why Polygon encounters this problem more frequently than other chains.

For a blockchain like Bitcoin, many miners are racing to find new blocks. Sometimes, more than one miner may succeed. Suppose two miners find new blocks (#1000A and #1000B) at the same height of 1000. Due to propagation delays, some nodes will see block #1000A while other nodes will see block #1000B. Now, if a new block is found on top of block #1000B, the chain that block #1000B is on will become the longest chain, and block #1000A will be discarded or reorganized by the network.

Note that a third block #1000C may be found by another miner at the same height (1000), and two more blocks (#1001 and #1002) have been found by the same miner or other miners building on this one. In this case, both blocks #1000A and #1000B will be discarded, while #1000C will become part of the chain. Ethereum also faces reorganizations, but the depth is rarely more than 1 block.



Polygon reorganizations are more frequent because it uses two consensus protocols: Bor and Heimdall. Bor block producers sprinted to improve efficiency, producing 16 blocks at a time and delivering them to Heimdall for verification. It is not uncommon to miss a block from a previous producer or validator. When a validator misses a sprint from a previous block producer, up to 32 blocks (16 x 2) may be reorganized. Polygon PoS has a block time of about 2 seconds, so 32 blocks will be about 1 minute. Therefore, these reorganizations mean that applications should not (cannot) assume finality of transactions such as deposits within at least 1 minute.

Although Polygon has resolved the deeper reorganization issues, reorganizations of up to 32 blocks are still possible.

zkEVM Downtime

Like most EVMs, the Polygon zkEVM has only one collator. Any error can cause an unnecessary chain stop. On March 23, the Polygon zkEVM was down for about 10 hours between two batches 2001558 and 2001559. As of March 25, the team has not revealed the exact cause, but noted that the sorter encountered problems due to a reorganization on Ethereum L1. zk technology is still in its early stages, and Polygon zkEVM TVL is not high. However, if such a stop occurs at a later stage, it may cause capital to leave the chain.

What's next

In this post, we reviewed the past and present. We first looked at how Polygon came to dominate the EVM network and why it fell behind in multiple aspects. While writing this article, I was reminded of the Phoenix, a figure in Greek mythology known for rising from ashes, growing and burning. Over and over again. Many technological advances go through similar cycles. We see new standards quickly emerge, be adopted, and become mainstream. People's attention tends to go to new and popular things until the mainstream uses its existing resources to innovate.

Throughout 2022, Polygon may be seen as the boss. Its positioning was safe and comfortable given the advantages it had throughout the DeFi summer. However, as Optimism and Arbitrum entered the market, developers had other options. Once the meme coins on Solana became popular, it gradually became a “safe” choice for developers looking for niche use cases - a bit like IBM, but for blockchain. During our research for this article, we interacted with Polygon Labs staff many times and raised these concerns.

Through our interactions, we learned how standards evolve. When a standard is in the development stage, the motivation for all participants is to maximize the adoption of the standard. Polygon Labs has done this through its BD work in 2021. The largest companies and enterprises are building on Polygon. As competition increases, the motivation for networks like Polygon shifts in the other direction, which is to develop new solutions to help more developers onboard.

This is exactly what Polygon has been focusing on over the past year, with a focus on AggLayer and the related CDK. Markets tend not to price in technological change until it is implemented and operational at scale. The chart we started this post with reflects this.

While AggLayer and CDK help unify chains on Ethereum, Polygon needs some breakthrough applications to prove the viability of the network at this point. For Solana, it’s Jupiter and Tensor. Users using Jupiter (trading memes) or Tensor (trading NFTs) can get a taste of the network.

Applications in a retail setting using CDK (scalability) are still being built, as the underlying infrastructure (AggLayer) is always evolving. So you have multiple moving parts. If these breakthrough applications emerge, attention will turn back to Polygon. Then, like a phoenix, its rise will be obvious.

There is continuity in the evolution of the Phoenix. Polygon has learned the lessons of scaling networks with Aave and Uniswap. It pays close attention to developer needs. However, its implementation will take time, and that’s where we are now.

The story is different in traditional industries like computers. Apple pioneered the computer revolution but lost out to IBM and Windows in the 1980s. It took a decade, some corporate restructuring, and the return of Steve Jobs for Apple to become a dominant force again.

In a market where attention is constantly chasing the hot new thing, the evolution of Polygon may fly under the radar. But if the technology works, it's only a matter of time before it's back in the conversation. Until then, we'll see how the transition plays out.