Layer 2 Scaling Fundamental
Last updated
Last updated
Blockchain technology faces significant scalability limitations, affecting its performance and widespread adoption. Layer 2 scaling solutions have emerged to address these issues by offloading transactions from the main blockchain (Layer 1) and processing them in parallel, thereby improving throughput and reducing fees. This paper reviews the current state of Layer 2 solutions, specifically focusing on three prominent frameworks: Lightning Network, Plasma, and Rollups. Each solution is examined across five critical aspects: scalability, security, decentralization, privacy, and micropayment efficiency. While all Layer 2 solutions enhance scalability, none universally excels across all dimensions, meaning the choice of framework depends on specific application requirements. The results highlight that Layer 2 scaling significantly boosts blockchain's efficiency, but careful consideration is required to balance trade-offs between performance and other key factors.
Blockchain technology, while revolutionary in its ability to enable decentralized, secure, and transparent transactions, faces a significant challenge in terms of scalability. Scalability refers to the system's capacity to handle a growing number of transactions or an increase in its user base without compromising performance. Current blockchain networks, particularly those like Bitcoin and Ethereum, suffer from limitations in transaction throughput, high fees, and network congestion during peak times. These limitations stem from the fundamental design of blockchains, which prioritize security and decentralization, often at the cost of transaction speed and efficiency.
For blockchain to achieve mass adoption and support large-scale applications such as decentralized finance (DeFi), supply chain management, and global payment systems, overcoming scalability is critical. Without addressing this issue, blockchains cannot compete with traditional centralized systems, which offer higher transaction speeds and lower costs. The scalability problem has spurred the development of Layer 2 solutions, which aim to extend blockchain functionality by processing transactions off-chain or in parallel, thus reducing the load on the base Layer 1 blockchain while maintaining its core security and decentralization principles.
Layer 2 solutions, such as the Lightning Network, Plasma, and various Rollup technologies, represent the most promising approaches to resolving blockchain's scalability challenges. These solutions are designed to increase throughput, reduce transaction fees, and improve overall performance, enabling blockchain technology to scale to meet global demand. This paper explores these Layer 2 frameworks in depth, analyzing their impact on key aspects like scalability, security, and decentralization.
What is Blockchain Scalability: Blockchain scalability refers to a blockchain network's capacity to process a large number of transactions efficiently and quickly. It's essentially a measure of how well a blockchain can handle growth and increased usage
Importance: For blockchain technology to achieve widespread adoption and compete with traditional payment systems, it must be able to process transactions at a high speed.
At the moment of writing, scalability is considered the bottleneck of the blockchain infrastructure. The afore- mentioned could potentially compete with the largest electronic payment circuits. However, it is limited by being able to handle few transactions per second (TPS). To clarify the problem, it is sufficient to report the two best-known blockchains as an example: Bitcoin processes 4.6 TPS and Ethereum processes around 14.3 TPS (slightly variable values), while one of the largest electronic payment circuits, Visa, processes around 1,736 TPS (and has been able to reach peaks of 47,000 TPS). Currently, the Bitcoin blockchain generates a new block every about 10 minutes (Time Block generation, TB) and, the block size (B) in the chain is 1MB (1,048,576 Bytes). The average transaction size is 380 Bytes. Therefore, the number of transactions that fit into a Bitcoin block (TPB) is:
Contrary to what one might think, the scalability problem cannot be solved by simply modeling its parameters: B and TB. As a matter of fact, considering the parameters modeling, it is necessary to make an important clarification: when gen- erating a new block in the blockchain, a crucial factor to be taken into account is the relay time (TR) needed to broadcast the new block to every node on the network. Therefore, this fact imposes a lower limit on TB, below which it is impossible to go. This TR threshold allows to keep all the nodes in the network constantly updated. Additionally, another problem related to the TR arises when expanding the block size (B). Consequently, an increased quantity of information has to be broadcasted to the network.
Again, a practical example from Bitcoin blockchain is considered in the discussion for simplicity of presentation: in January 2021, around 10,000 nodes were estimated in the Bitcoin network. The average time to propagate a block to 99% of the network is approximately 14 seconds. Thus, TB cannot fall below the 14 seconds threshold. Otherwise, a new block would be generated before an old block would be received by most of the nodes in the network. The problem related to the size of the block becomes evident when increasing it: 14 seconds as Time Relay would no longer be enough.
In 2017, Segregated Witness’s (SegWit) soft fork helped to improve block size (scaled up theoretically to 4MB, practically around 2MB) without changes to the core code. Nevertheless, it still does not improve TPS in a scalable manner.
Blockchain's scalability problem stems from its decentralized nature, requiring transactions to be broadcasted and validated by the entire network. Layer 2 solutions aim to address this issue by offloading transactions from the main chain (Layer 1) to secondary frameworks, reducing the load and enhancing transaction speed while attempting to maintain security and decentralization. These solutions must navigate the "scalability trilemma," where improvements in scalability often lead to trade-offs in security or decentralization.
Layer 2 solutions generally follow the principle of processing transactions off-chain while only reporting essential information or summaries back to Layer 1. The key types of Layer 2 frameworks include:
Channels: Channels, such as Bitcoin’s Lightning Network and Ethereum’s Raiden Network, enable direct or indirect off-chain communication between nodes. In these systems, transactions between connected nodes are handled off-chain, with only two transactions recorded on-chain: the opening and closing of the channel. This significantly reduces the on-chain transaction load.
Sidechains: Sidechains run in parallel to the main chain and process transactions independently. These "child" blockchains anchor to the main chain but are less decentralized, making them faster. Plasma, a variant of sidechains, adds more security and decentralization guarantees. Sidechains report only the opening and closing of a batch of transactions to the main chain, similar to channels.
Rollups: Rollups process transactions off-chain but report the relevant data about each transaction back to the main chain. Unlike channels and sidechains, rollups continuously broadcast smaller amounts of transaction data for off-chain state updates, making them a more integrated scaling solution. Examples include zk-Rollups and Optimistic Rollups.
Layer 2 solutions provide faster transaction speeds, lower fees, and are particularly suited for micropayments. They operate independently of the Layer 1 blockchain but still depend on it for securing and summarizing transactions. Unlike Layer 1 solutions, such as sharding, Layer 2 does not alter the underlying blockchain's structure but builds atop it for scalability improvements. Combining various Layer 2 protocols can maximize scalability benefits without sacrificing the core principles of blockchain technology.
The Lightning Network (LN) is a Layer 2 scaling solution designed to enable fast, low-cost peer-to-peer transactions by creating off-chain communication channels between nodes. LN operates atop the Bitcoin blockchain but has also been integrated into other blockchains like Litecoin. Its primary function is to reduce the load on the main blockchain by allowing transactions between two nodes to occur off-chain. These transactions are only recorded on the blockchain when the channel is opened or closed, minimizing the number of on-chain transactions.
LN relies on state channels, which allow users to establish a direct or indirect off-chain link. Once a channel is opened, parties can exchange multiple payments privately without broadcasting each individual transaction to the main chain. Instead, only the final channel state is submitted to the blockchain when the channel closes. This significantly improves transaction speed, reduces fees, and enhances the blockchain's scalability, as it only has to handle two on-chain transactions (the channel opening and closing).
Similarly, the Raiden Network (RN) is an Ethereum-based counterpart to LN. While LN was initially developed for Bitcoin, RN provides a similar off-chain payment framework for Ethereum. Both networks aim to address scalability concerns by offloading transaction processing to secondary layers, reducing the computational burden on the primary blockchain.
LN and RN are powerful tools for enabling fast, off-chain micropayments, reducing congestion, and improving scalability while maintaining the security and trust of the underlying blockchain. They are particularly suited for applications like everyday payments, where high transaction throughput and low fees are crucial.
To clearly understand the use of the channel, let’s imagine two users, Alice and Bob, who opened one. Each of them put 3 BTC in a “contract” with the counterparty. After ten transactions, a possible scenario might be: Alice has 5 BTC on her side, and Bob has 1 BTC on his side.
At any time, either party can publish the current state on the blockchain. At that point, the balances on each side of the channel are allocated to their respective parties on-chain. In Lightning Network, this implies the closure of the channel; in Raiden Network, instead, it is also possible for a user to “withdraw tokens from a channel without closing it (having his/her counterparty’s signature as well).
Transactions in the channel are not subject to fees except for the channel opening and closing ones. As a consequence, a substantial advance of LN is that it allows micropayments. In particular, since transactions in the channel have no fees (without considering payment routing, described in the following sections), users can be encouraged to send even small amounts of money. Thus, it is now possible to transact the smallest unit currently available, 0.00000001 BTC (one satoshi).
Another relevant feature of LN is the privacy it gives to users. Except for the first and last transactions, nobody outside the channel can see what happens inside it
Multisignature addresses & HTLC
A multisignature (multisig) address is one that multiple private keys can spend from. When creating the channel, the number of private keys that can spend funds and how many of those keys are required to sign a transaction are specified. For instance, a 2-of-4 scheme would indicate that, on four possible keys, any two of them are required to authorize a transaction (signing it). It is substantial to point out that, when the multisig needs more than a single key to authorize a transaction, single users cannot move funds without other users agreeing.
A simple example: Alice (A) and Bob (B) lock up 5 BTC each into a 2-of-2 scheme. This scheme is composed of only two private keys capable of signing, and both are needed to move money. Supposing that A ends up with 9 BTC and Bob with 1 BTC, this scenario might lead Bob not to cooperate, locking his and Alice’s funds in the multisig address (note that Alice needs Bob agreeing to unlock her funds). A mechanism that prevents the problem that might occur when one of the parties decides not to cooperate goes under the name of Hash TimeLock Contract (HTLC). In the Security section that follows shortly, the process by which Lightning Network prevents cheating is explained in detail.
Routing payments
A substantial part of the usefulness of LN is due to the connection between channels. The existence of different paths allows payments between users even if those are not directly connected. For instance, if Alice (A) opens a channel with Bob (B), and Bob already has one with Carol (C), Bob can act as intermediary by routing payments between A and C.
Intermediaries receive coins in the channel with the sender. Then, they effectively spend their funds in the route toward the receiver. A significant clarification is that the overall amount of money in a channel remains the same. The following representation extends the example above, with Bob routing a payment between Alice and Carol. The reported scenario shows a channel between Alice with a 5 BTC balance and Bob with a 2 BTC balance; the second channel, between Bob with 3 BTC and Carol with 1 BTC, is reported too. Supposing Alice wants to send 2 BTC to Carol, she should send 2 BTC to Bob; then, Bob, from the other channel, should send 2 BTC to Carol. The final scenario would be: Alice 3 BTC, Bob 4 BTC (Alice side), Bob 1 BTC (Carol side), Carol 3 BTC.
The importance of routing payments in state channels Layer 2 solutions is exem- plified by the fact that in Raiden Network, for instance, every payment, under the implementation point of view, is seen as a multi-hop transaction with N intermedi- aries; if the channel supporting it is direct, then N=0.
A criticism of routing payments is that it is impossible to spend more than the fund locked in a channel. Therefore, a considerable problem might occur when, considering the same example as before, Alice wants to send all her funds (5 BTC) to Carol. This transaction cannot be performed with Bob as an intermediary because Bob has just 3 BTC (Carol’s side), which correspond to the maximum amount of money Alice can send to Carol via Bob.
A relevant aspect to note is that, even if it is not mandatory, intermediaries usually ask for fees to route transactions. In particular, since they effectively spend their funds in involved channels, they ask senders to pay a fee (a small fee compared to that of the main chain) for having their payments routed to the recipient. This aspect might imply relevant consequences for the possibility of micropayments in a not fully decentralized solution, as it is further detailed in Decentralization and Fees and micropayments sections.
The Lightning Network (LN) significantly improves Bitcoin's scalability by increasing its transaction throughput from around 5 transactions per second (TPS) to a theoretical capacity of billions of transactions per day, with estimates of at least 11,000 TPS. LN allows instant, secure, and decentralized transactions while preserving the core qualities of blockchain such as privacy.
However, there are two scenarios where using LN may not be ideal:
Routing Issues: If a payment route contains a node without enough funds in its channel, the payment will fail, requiring the sender to find another route, potentially causing delays.
Uncooperative Users: When closing a channel, if one party refuses to sign the final transaction, the other party must wait for a time lock to expire before accessing their funds.
For the first issue, splitting larger payments into smaller ones can help find available routes. However, the second problem has no workaround as it is tied to the high-security standards of the Lightning Network.
The Lightning Network (LN) uses a Hash TimeLock Contract (HTLC) to enhance security and protect against uncooperative behavior in payment channels. HTLCs rely on two mechanisms: hashlocks and timelocks.
Hashlock: This condition ensures that funds can only be spent if the recipient knows a secret, which is hashed and included in the transaction. The recipient must provide the secret that matches the hash to access the funds.
Timelock: This condition prevents funds from being spent until a certain time has passed. If the recipient does not provide the secret within this time, the sender can reclaim the funds.
Here's a simple example:
Bob generates a secret and shares the hash with Alice.
Alice creates a transaction that can be claimed by Bob if he provides the secret before the timelock expires.
If Bob doesn't provide the secret within the time limit, Alice can reclaim her funds.
HTLCs prevent cheating by ensuring that older transactions, where the secret has been shared, cannot be broadcast by a malicious party. In the rare case where one party is offline and the other tries to cheat by broadcasting an old transaction, the system's reliance on time-based conditions ensures that the counterparty will eventually receive their funds.
In the Raiden Network (Ethereum's counterpart to LN), this issue is further mitigated by introducing a Monitoring Service. A node that goes offline can rely on other nodes to monitor the channel, and these nodes are incentivized to disclose cheating behavior. While this adds a layer of security, it slightly reduces the privacy of the Raiden Network.
This layered approach in both LN and RN balances security, ensuring that funds are protected and uncooperative behavior is minimized.
Given its peer-to-peer architecture, Lightning Network can certainly be considered as a decentralized framework, at least from a theoretical perspective. In fact, no entity or node manages or regulates off-chain transactions, which are directly performed over the peer network in a single-hop or multi-hop way.
However, even if decentralization is fully guaranteed under the theoretical point of view, the real structure of the network actually has scale-free properties: the majority of LN nodes has active channels (of limited capacity) with few peers, while a limited numberofhubs isconnectedtoahighnumberofnodes. Itisinterestingtounderstand thatthishub and spoke architectureisquitelikelytobe“fed” bysingleusers’decisions: suppose, for instance, that Alice (A) and Bob (B) enter Lightning Network in order to establish a payment channel; their idea is that of starting transacting between themselves,butalsobecomingactiveusersofLNbylaterexchangingcryptocurrencies with other users, too. The structure of LN, for this example, is imagined to be the following:
Alice and Bob have basically two choices: creating a direct channel between them- selves or creating an indirect one. Of course, a direct channel would ensure no fees for all the transactions between A and B, except for the fees payed on the main chain; on the other hand, if any of the two also liked to transact with Carol (C), Gwen (G) and James (J), he/she would necessarily have to open other channels. The indirect channel, instead, would add LN fees for transactions between Alice and Bob, but would require no other channel for transacting with C, G, J.
Since off-chain fees are sensibly lower than main chain fees, and given the fact that many nodes are likely to enter LN and keep channels active in order to transact with more than one other peer, most of them decide to open a state channel with a hub (instead of multiple ones with “target” nodes); in the previous example, at least one between Alice and Bob (if not both) are likely to open their channel with David. In reality, the presented concept is just a general idea, because also channels’ capacities play a key role in the evolution of LN architecture; in any case, several studies have shown that scale-free properties have been emerging in Lightning Network, and that users tend to prefer setting channels with reliable and well-established central nodes, so to pay the smallest amount of fees (few hops with approximately every other peer, without the necessity to open various channels, which has a considerable on-chain cost) and be connected with the majority of nodes.
So, Lightning Network certainly has the idea of preserving decentralization as its core: in fact, it is implemented as a peer-to-peer network. However, the real structure of this L2 solution tends to be less distributed than one might think. This aspect can not be considered an unbalanced step towards centralization of the blockchain, since, in any case, the architecture is still P2P and final summaries of transactions are reported on-chain. However, it is also important to take into consideration the real structure of LN, in order to better understand possible issues for robustness (in a scale-free network, if one or more hubs are offline there might be problems, since they constitute the “core” for connectivity), fee policy and privacy. Moreover, another aspect should be underlined: hubs are not only central nodes, but tend to be also the only nodes which can route substantially high-value payments (in fact, most of users have only low capacity active channels); this fact is not a huge issue since LN is mainly a network of micropayments (low fees make it possible to spread a transaction into a set of smaller ones), but it is certainly another considerable part in the overall analysis.
Privacy in state channel Layer 2 solutions like the Lightning Network (LN) is assessed from two key perspectives: transaction confidentiality and routing privacy.
Transaction Confidentiality: LN allows users to conduct multiple transactions off-chain, only broadcasting the opening and closing channel transactions on the blockchain. This limits the exposure of transaction details, providing a high level of privacy between the participating nodes. The only public information is the initial and final balances of the channel, ensuring that the exact nature of individual transactions remains hidden from the public.
Routing Privacy: LN uses a routing protocol that requires sharing the IP addresses of nodes and the capacities of active channels. While the capacity of a channel is public (as it is locked at the channel's creation), the balance of the channel, which reflects the dynamic movement of funds between nodes, is kept private. This enhances the confidentiality of state channels but may lead to inefficiencies when routing payments since the exact balance of the channel is unknown. As a result, more than one attempt may be needed to complete a payment.
For multi-hop payments (transactions routed through several nodes), LN employs an onion-routing protocol. Each intermediate node only knows its immediate predecessor and successor, thus ensuring that even though the nodes are involved in the payment process, they do not have full visibility of the transaction’s details or final destination. The longer the routing path, the higher the level of privacy.
However, if a payment is routed through only one intermediate node, the privacy level decreases, as the node is aware of the payment's size and direction. Still, due to the onion-routing technique, the node cannot determine if it is handling the complete transaction or just part of a longer path.
LN’s privacy is robust, particularly for direct channels or longer routing paths. Some privacy limitations stem from the network’s scale-free topology, where many payments are routed through a small number of key hubs, resulting in shorter paths and a lower degree of privacy.
Raiden Network similarly prioritizes privacy but sacrifices some of it to incorporate a Monitoring Service that improves security. This service monitors channels for cheating behavior, offering better protection at the cost of slightly reduced privacy.
In the Lightning Network (LN), fees are structured differently depending on whether the transaction occurs in a direct channel or is routed through intermediate nodes.
No Fees for Direct Transactions: When two parties have a direct channel, transactions between them are not subject to fees. This is because no intermediate routing or extra computational effort is needed to process these payments.
Fees for Routed Transactions: For multi-hop payments, where the transaction passes through intermediate nodes, small fees are typically applied by the nodes that route the payments. However, these fees are minimal compared to on-chain fees due to the low computational effort required for LN transactions. Fees in LN are mainly an incentive for nodes that temporarily unbalance their channels by forwarding payments.
Fee Structure: LN fees generally have two components:
A variable fee: Proportional to the size of the payment being routed. Larger payments cause greater channel imbalances, and thus higher fees.
A fixed fee: Charged regardless of the payment size.
Fee Market Evolution: The LN fee market is still in its early stages and remains very low, similar to early blockchain networks. However, fees are influenced by LN’s free-scale topology, where larger hubs may dominate payment routing. If the network becomes more centralized, these hubs could potentially raise fees, particularly for micropayments.
Micropayments and Fee Implications: Micropayments could face challenges in a more centralized network. For example, if Alice wants to send a small payment to Bob but does not have a direct channel, she has two options: either open a new channel (which involves an on-chain transaction with fees) or route the payment through existing channels. If LN becomes centralized with key hubs controlling much of the routing, Alice might be forced to accept higher fees when routing through these hubs, even for small payments.
Currently, LN fees remain low, reflecting the network’s goal of providing cost-efficient, off-chain transactions. However, as the network evolves, the fee structure may change, potentially affecting the ease of handling micropayments.
Plasma is a Layer 2 scalability solution proposed by Joseph Poon and Vitalik Buterin in 2017 for Ethereum. It aims to enhance blockchain scalability by creating a system of child chains (Plasma chains) that offload transactions from the main Ethereum chain (Layer 1), reducing transaction latency and cost.
Plasma proposal’s goal is to solve this problem by publishing each sidechain’s block header to the L1 chain (the root chain), therefore minimizing trust but at the same time allowing verifiable fraud proofs and enforcible state, given that the root chain is secure and constantly available. This could lead to move a huge amount of load in terms of transactions, from the root chain (L1) to Plasma chains (L2), with only periodic commitments on the root chain. Moreover, Plasma reduces the storage needed in the root chain, by compacting several state transitions in a single merkle root commitment.
Sidechains and Asset Transfers: Plasma extends the concept of sidechains, where users deposit assets into a contract on the Layer 1 (L1) chain (e.g., Ethereum) and the sidechain operator credits these assets to users on the sidechain. This setup increases transaction throughput using different consensus mechanisms, such as Proof-of-Authority, which provides fast block times and low fees.
Scalability and Centralization Trade-off: Standard sidechains face a trade-off between scalability and centralization. For instance, in Proof-of-Authority chains, the central operator could halt block production or block withdrawal requests, making them vulnerable to trust-related issues. Plasma addresses this by minimizing trust requirements through periodic commitments of sidechain block headers to the root chain, enabling fraud proofs to ensure security and enforceable states.
Minimizing Trust with Fraud Proofs: Plasma publishes each child chain's block header to the root chain, which minimizes trust by allowing the root chain to verify fraud proofs and enforce state transitions. This approach enhances security, offloads transaction volume from the root chain, and reduces storage demands by committing multiple state transitions into a single Merkle root.
Multiple Use Case Plasma Chains: Plasma allows for multiple child chains, each serving a specific use case, such as handling decentralized exchange (DEX) transactions or micropayments. These chains can form a hierarchical structure, where higher-level chains can resolve disputes from lower-level chains.
Fraud Proofs and Dispute Resolution: Plasma uses an Unspent Transaction Output (UTXO) model for fraud proof verification. Validators propose blocks for Plasma child chains, and any malicious block can be rolled back if another actor provides a Merkleized fraud proof. If a fraudulent block is detected, the proposer of the invalid block is penalized.
Withdrawal requests are protected by a dispute mediation process. Users submit a withdrawal request with a Merkle proof on the root chain. However, since the root chain cannot verify if the asset has been spent on the child chain, a challenge period is required to allow others to submit fraud proofs, ensuring the withdrawal’s legitimacy.
Deposits and Withdrawals:
Deposits: Users initiate deposits by sending funds to a contract on the root chain. The child chain then commits these funds in a block, which the depositor signs to acknowledge.
Withdrawals: A withdrawal involves the user sending a transaction to the root chain with the entire unspent output. A bond is also staked to discourage invalid withdrawal attempts. If a valid fraud proof is submitted during the challenge period, the withdrawal is canceled, and the bond is forfeited. If no fraud proofs are provided, the user can redeem the funds.
The challenge period (often 7 days) protects against fraudulent withdrawals but slows down the process. To overcome this, fast withdrawals can be facilitated by liquidity providers (LPs), who offer users a quicker exit by validating the child chain’s state and charging a fee for their services.
Plasma aims to achieve high scalability with minimal trust, allowing transactions to be offloaded from Layer 1 to multiple Plasma child chains.
Fraud proofs and dispute resolution mechanisms protect against malicious behavior and ensure that funds can be withdrawn securely.
Although Plasma provides significant scalability benefits, the user experience can be hindered by long withdrawal times, which can be mitigated using liquidity providers offering fast withdrawal services.
In terms of scalability, a Plasma chain can claim the same performance improvements achieved by standard sidechains. Obviously, the transaction throughput and latency that can be obtained ultimately depend on the consensus mechanism that the Plasma chain exploits. Usually, we can expect child chains to use a consensus algorithm other than proof-of-work, such as proof-of-stake (PoS) or proof-of-authority (PoA), which allow for faster block times and a higher number of transactions per second (TPS).
As an example, Polygon (formerly known as Matic Network), a commercial-adapted implementation of Plasma exploiting PoS as a consensus mechanism for the Plasma sidechain, can be considered. Polygon claims to have reached a peek of 7,200 TPS on its internal testnet; at the moment of writing, Polygon mainnet has an average block time of 2.1 seconds and a gas limit per block of 20 million. Using current available data, simple statistics can be computed, to get the current average gas consumed for each Ethereum mainnet transaction:
The obtained result is a good improvement (about 11 times) over Ethereum mainnet current thought, but still far from what is needed in order to envision mass adoption of the technology and handle, for example, the load implied by global retail transactions. However, it is interesting to notice that the approximation adopted here is quite conservative: blockchains with similar consensus mechanisms (not necessarily implementing Plasma) exploit a greater block gas limit and, potentially, a lower block time: this could lead to further improvements in terms of throughput. Moreover, this type of construction implies that other additional Plasma sidechains can always be added, therefore enabling horizontal scaling of blockchains.
Security on a Plasma chain is ultimately achieved by merkle proofs submitted to the root chain, which prevent the child chain’s validator Byzantine behaviors and invalid attempts to withdraw outputs (such as those already spent).
Most of the security concerns in this context are related to data availability and block withholding attacks (BWA), which happen when validators refuse to publish new blocks. Users of a Plasma chain must constantly monitor the chain and, in the case of BWA, they need to perform a mass exit. In addition to the fact that the need to constantly monitor the child chain (liveness assumption) creates usability issues, one of the main challenges in Plasma is to make mass exits compact and efficient. Mass exits cannot be performed as fast withdrawals since, in this case, the chain is assumed to be Byzantine and liquidity providers would not have the interest in processing this kind of withdrawals. Even if it is theoretically possible to use the simple withdrawal process described in the previous section, a dedicated procedure has to be designed to mitigate data availability issues as much as possible.
The mass withdrawal interactive game proposed by Buterin and Poon is based on a mass exit operator, which verifies the Plasma chain up to the point in which the BWA started. An exit transaction is created with an attached massive bond and users sign of the mass withdrawal. The operator will then sign and broadcast the mass exit initiation transaction (MEIT) to the destination chain, optionally charging a fee to every user who is participating in the process. The operator also publishes a full bitmap of the state involved in the exit: this let observers of the Plasma chain to understand what is being withdrawn and optionally challenge it; finalization of the MEIT may take a lot of time, in the order of weeks.
However, the described design leads to problems that are intrinsic to mass-exits: supposing a very popular Plasma chain with a very big number of users, a fraudulent event by validators could cause the root chain to be flooded by huge simultaneous mass-exit transactions. As a result, the L1 chain would likely be heavily congested.
Other possible security threats may include:
Smart Contract code vulnerabilities: smart contracts on the root chain are responsible for enforcing the state of the child Plasma chains. The security of the Plasma architecture is entirely reliant on complex on-chain smart contracts; the complexity needed in this context increases the risks of vulnerabilities
Redeem transactions may be too expensive on the root chain, thus making withdrawals unfeasible
State enforcement and execution of exit transactions might fail if a 51% attack is being performed on the root chain and blocks are being censored
From a strictly theoretical point of view, the level of decentralization offered by a Plasma chain exclusively depends on the exploited consensus mechanism of the chain itself. However, Plasma is by construction trying to let not fully decentralized sidechains (such as those using proof-of-authority) avoid the usual problems deriving from a centralized chain, through the use of Merkle proof commitments on the root chain. In practice, the effects of the decentralization level chosen for a Plasma chain depend on two factors:
As previously stated, the consensus mechanisms of the Plasma chain
When transactions are considered finalized
To avoid side effects deriving from an increased level of centralization, one should consider a transaction finalized only when the Merkle root of the block containing the transaction itself is committed to the root chain: doing this ensures that the state is being enforced by fraud proofs, and that the security is the same as L1 blockchain. To mitigate the need for waiting the commitment, the Plasma chain could make use of a proof-of-stake consensus mechanism, in order to find a balance between decentralization and achieved scalability: for this reason, Plasma Proof of Stake was proposed by Buterin and Poon, also trying to reduce the risk of block withholding attacks.
Although privacy issues are not a primary concern in Plasma design, some considerations regarding the consequences of the proposed solution can be made. Essentially, Plasma is based on the concept of avoiding broadcasting all transactions in the root ledger. The load on the L1 chain is reduced, and the resulting privacy is determined by the specific child chain design, which could also be focused on guaranteeing greater privacy properties with respect to public ledgers like Ethereum or Bitcoin. Theoretically, implementations for such a Plasma chain could be inspired by already existing designs that aim to provide an increased level of privacy, such as ZCash. A solution of this kind would widen the scope of this Layer 2 solution, allowing not only for scalable public blockchains but also to add privacy features to already existing public decentralized ledgers.
In Plasma sidechains, transaction fees are significantly reduced compared to Layer 1 (L1) blockchains. This is due to the less decentralized consensus models used, such as Proof-of-Authority (PoA), which remove the need for high fees driven by miners competing to process transactions. Users can always revert to the secure L1 if needed, which allows Plasma chains to operate with low fees while maintaining security.
Micropayments are a well-suited use case for Plasma, as low-value transactions can be processed on the Plasma chain without incurring high fees or using much storage on L1. For example, a coffee shop could use Plasma for customer payments, only interacting with the root chain periodically for withdrawals. Plasma chains can also send assets to users not yet participants in the network, a flexibility not offered by traditional state channels.
Several Plasma variants have been proposed to optimize for different use cases:
Plasma MVP (Minimum Viable Plasma): A simple UTXO-based chain designed for high-volume payments but not general smart contract execution. It uses PoA consensus and is suitable for private blockchains.
Plasma Cash: Represents user funds as NFTs, using sparse Merkle trees for scalability. It is ideal for handling off-chain NFTs but struggles with fractional transactions, making it less suitable for micropayments.
Plasma Debit: Solves the limitations of Plasma Cash by incorporating payment channels for fractional fund transfers, allowing users to transfer smaller amounts with operators acting as routers.
Payment channels and Plasma are usually considered “full” Layer 2 solutions, while Rollups, a framework for Ethereum proposed in 2018, is considered a “hybrid” solution between L1 and L2 scaling: this is due to the fact that, while Lightning Network and Plasma summarize many state transitions in one single commitment or channel closing, the Rollup proposal implies that some information on every single transaction sent on the L2 is posted on-chain. The idea of Rollup is that transactions are aggregated off-chain, causing a reduction in congestion and fees on the root chain.
The concept of Rollups is somehow similar to the one previously explained for Plasma: a smart contract deployed on the root chain keeps track of the current (most recent) merkle root of the state of the rollup (in practice, this could be the L2 chain). The computation of the new state is performed off-chain, and the root chain is used for data availability (by posting a piece of data for each transaction). The described design allows to avoid data withholding issues because all the information is always retrievable from the root chain, which is considered to be secure and always available. Any actor is able to publish a batch, which is a collection of compressed transactions with the previous merkle root and the new merkle root attached to it. At this point, the Rollup contract, before updating the state root with the new one, has to check (for security reasons) if the previous root corresponds to the current root (for a focus in the security analysis of the solution, refer to next discussions in the section). A peculiar feature of Rollup is that it allows to transact outside the Rollup contract itself: this is meant to support transactions whose input comes from outside or whose output is destined for outside. At the time of writing, there are mainly two types of Rollup solutions: ZK Rollups and Optimistic Rollups. They differ in how they perform verification on the submitted batch.
The ZK Rollups solution is based on the concept of validity proof and zero-knowledge proof. The idea behind ZKRollup is to bundle every batch with proof of their validity. The proof should be easy to check, proving the correctness of the batch content. ZK Rollup framework uses the SNARK proof, this kind of system allows observers to immediately prove the validity of an assertion. So, the main characteristic of this proof is that it is cheap to verify. However, computing it is expensive. Therefore, ZK Rollup is an appropriate system for transactions management, but it does not fit with complex contract execution.
Optimistic Rollups is an interactive approach. It is, in a sense, more similar to Plasma’s, since it involves the use of fraud proofs. In this kind of solution, new batches (and, therefore, new merkle roots) are published by operators, without being proved to be right by the Rollup smart contract. This mechanism is further detailed.
One of the key points of Rollups scaling is compression: in practice, every Rollup transaction (remember that information of every transaction is reported on-chain) may be compressed to occupy a total space of (down to) approximately 12 Bytes. This size, of course, varies with Rollup and transfer types: Optimistic Rollup transactions need more Bytes (information) for later verification (due to the absence of a SNARK proof); ETH transfers take fewer Bytes than more “complicated” transfers, as it normally happens on Ethereum blockchain. So, 12 Bytes lower-bound for a Rollup transaction refers to an ETH transfer performed using ZK Rollups.
To better understand the translation of this compression feature into throughput achievements, a best-case scenario can be considered: ZK Rollups for transferring ETH. Considering the current values, on the Ethereum blockchain, of:
Gas limit: 12.5 Million gas/block
Gas per Byte in L1 transaction: 16 gas/Byte
Average block time: 13 sec/block
Supposing to spend 1 Million gas for proof verification, the following calculations can be developed:
It is crucial to remember that this is a theoretical achievement for ETH transfer on ZK Rollups, considering that the whole on-chain transaction is composed of data coming from the Rollup itself. In any case, although further complications may be analyzed, 100x scalability improvement is a good approximate evaluation of ZK Rollups scalability with respect to Ethereum L1 throughput.
For what regards Optimistic Rollups, instead, considering a Rollup transaction size of 12 Bytes is not possible anymore, since further data must be committed on the main chain for verification; however, even considering a transaction size 6 times bigger than the one for ZK Rollups (which is a quite reasonable value), the obtained throughput is approximately more than 800 TPS: so, still substantially higher than Ethereum current throughput for token transfers. At the time of writing, one of the main features offered by Optimistic Rollups with respect to ZK Rollups is general computability (of smart contracts). In any case, also for complex contract interactions, the improvement measured as a ratio with respect to L1 scalability is reasonably the same as ETH transfers, since other contracts normally require more computation on the main chain too.
In addition to pure throughput analysis, it is important to analyze the withdrawal time: in fact, users’ purpose is not only to transact at high speed but to drop out fast too. For this purpose, the two Rollup solutions behave very differently, due to security verification diversity, while for ZK Rollups the withdrawal period is very fast (thanks to SNARK proof, waiting for the next batch is sufficient), in Optimistic Rollups this time goes up to 1 or 2 weeks, so to be compatible with fraud-proof challenge period.
When discussing security in Rollup systems, it's essential to differentiate between ZK Rollups and Optimistic Rollups.
ZK Rollups involve two user types: transactors, who perform transfers, and relayers, who stake bonds in the Rollup smart contract to bundle transactions. They utilize the SNARK proof system, with relayers generating SNARK proofs that represent the state changes on the blockchain. Once a batch of transactions is prepared, it is submitted to the root chain along with the SNARK proof, verifying that the new state was correctly derived from the previous state. This mechanism eliminates the need for fraud proofs, making ZK Rollups efficient for managing transactions and executing small contracts. However, they struggle with complex contract execution due to the intricacies of proof generation.
Optimistic Rollups, in contrast, utilize a fraud-proof mechanism similar to Plasma. They track the history of state updates and allow challengers to submit proof of incorrectness if they detect an invalid post-state root. The system verifies these proofs, restoring the last valid state if the assertion is indeed incorrect, which enables better management of complex contract execution.
Rollups are implemented on-chain via smart contracts, leading to a higher degree of centralization, especially as their usage grows. Unlike other Layer 2 solutions like state channels, Rollups publish all necessary data on-chain, maintaining a level of decentralization by enabling state reconstruction.
A key centralization concern for ZK Rollups is that SNARK proofs require a trusted initial condition, often controlled by a small group, which can centralize the system during its early phases. However, these concerns are more about potential mining security vulnerabilities than fundamental threats to Layer 2 centralization.
Rollups do not prioritize privacy, as they report transaction summaries on-chain, which reduces anonymity compared to solutions that only commit initial and final transactions. Optimistic Rollups could serve as a Layer 3 solution to enhance transaction privacy on existing Layer 2 solutions for Ethereum, though this introduces excessive fragmentation. Currently, the focus remains on improving throughput, security, and low fees rather than privacy.
Transaction fees in Rollups consist of both off-chain and on-chain components, influenced by the type of Rollup used (ZK or Optimistic). For instance, analyzing recent ZK Rollups for Ethereum transfers via zkSync shows on-chain fees ranging from 0.052 to 0.076 Ether for batches containing 129 to 206 transactions, resulting in an average on-chain cost per transaction of approximately 0.000461 ETH (around $1.12). However, actual transaction costs can vary based on the type of operations.
When comparing Rollup fees to Ethereum mainnet fees (around $1.23), Rollup transactions can be up to 11 times cheaper. While Rollups aim to further reduce costs, current scalability challenges limit their potential.
In terms of micropayments, the average cost of $0.11 per transaction remains high for small payments, such as coffee ($1). Nonetheless, Rollups have the capability to drastically reduce fees, making microtransactions feasible in the future.
ZK-EVM (Zero-Knowledge Ethereum Virtual Machine) is a Layer 2 scaling solution that combines the benefits of ZK Rollups with the functionality of Ethereum's EVM (Ethereum Virtual Machine). It's not a separate solution from ZK Rollups but rather an advanced form that leverages ZK Rollup technology to achieve compatibility with Ethereum smart contracts.
Key Points:
ZK Rollups Background: ZK Rollups use Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge (ZK-SNARKs) to bundle multiple transactions into a single proof. This proof is then verified on the Layer 1 chain (like Ethereum), reducing the computational and storage burden while ensuring security.
ZK-EVM and Ethereum Compatibility: The challenge with regular ZK Rollups is that they are excellent for simple transactions (like token transfers) but struggle with more complex smart contract execution. ZK-EVM solves this by supporting the full execution of Ethereum smart contracts off-chain while using zero-knowledge proofs to ensure security. This makes ZK-EVM compatible with the same smart contracts and decentralized applications (dApps) that run on Ethereum, which is a massive advantage for developers and users.
How ZK-EVM Works:
Like ZK Rollups, ZK-EVM batches transactions and generates a zero-knowledge proof.
However, unlike regular ZK Rollups that focus on basic transactions, ZK-EVM can process full EVM-compatible smart contracts, meaning complex logic and decentralized applications (DeFi, NFTs, DAOs, etc.) can operate seamlessly on Layer 2.
Once the batch of transactions is processed, the proof is submitted to the Ethereum mainnet for verification, ensuring the new state is accurate without overloading Ethereum’s Layer 1 with execution costs.
Advantages of ZK-EVM:
Scalability: ZK-EVM scales Ethereum by significantly reducing transaction costs and improving throughput while maintaining Ethereum's decentralization and security.
Security: ZK-SNARKs ensure cryptographic security for each transaction batch, eliminating the need for a fraud-proof mechanism like Optimistic Rollups.
Lower Fees: Due to efficient bundling and proof submission, ZK-EVM can reduce transaction fees, which makes it ideal for DeFi applications, NFT trading, and micropayments.
Fast Finality: ZK-EVM provides faster transaction finality compared to Optimistic Rollups, which rely on long fraud-detection windows.
ZK-EVM vs. ZK Rollups: ZK-EVM is an extension of ZK Rollups:
ZK Rollups are great for simple payments and token transfers but lack the ability to support complex smart contracts without significant overhead.
ZK-EVM solves this by making Ethereum’s full smart contract functionality available on Layer 2, making it more versatile for dApp development and use cases beyond payments.
Conclusion:
ZK-EVM is a Layer 2 solution based on ZK Rollup technology but is designed to run EVM-compatible smart contracts. It offers scalability, security, and lower transaction fees, making it a powerful tool for the Ethereum ecosystem. By combining ZK Rollups' efficiency with full compatibility with Ethereum’s smart contracts, ZK-EVM is an important step toward a scalable and secure Ethereum without sacrificing decentralization.
Here’s a comparative table between various Layer 2 scaling solutions such as ZK Rollups, Optimistic Rollups, State Channels, Plasma, and ZK-EVM:
Feature
ZK Rollups
Optimistic Rollups
State Channels
Plasma
ZK-EVM
Verification Method
Zero-Knowledge Proofs (ZK-SNARKs)
Fraud Proofs (Optimistic assumption)
Off-chain settlement, on-chain finalization
Fraud Proofs
ZK-SNARKs + EVM Compatibility
Transaction Finality
Fast finality, no challenge period
Delayed finality (1-2 weeks fraud-detection period)
Instant finality (but requires participants to stay online)
Delayed finality (due to exit period)
Fast finality, no challenge period
Smart Contract Support
Limited to basic contracts (complex proofs are slow)
Full EVM support
Complex smart contracts not ideal
Limited or no smart contract support
Full EVM support for complex smart contracts
Throughput
High (due to efficient batching)
Medium (slower finality due to fraud challenges)
Very high (as everything happens off-chain)
Medium to high
High (as efficient as ZK Rollups but with full EVM support)
Security Model
Inherits security from Ethereum, guaranteed by ZK proofs
Inherits security from Ethereum, depends on fraud proofs
Security relies on finalizing states on the main chain
Inherits security from Ethereum, but exit challenges add complexity
Inherits security from Ethereum, guaranteed by ZK proofs
Transaction Costs
Low (due to efficient proof aggregation)
Low, but higher than ZK Rollups due to fraud challenge period
Very low (mainly off-chain, only on-chain for settlement)
Low (but exit costs can be high)
Low (due to efficient proof aggregation)
Use Cases
Payments, token transfers, basic dApps
Full DeFi dApps, NFTs, complex smart contract interactions
Micropayments, fast transactions, peer-to-peer exchanges
Micropayments, high-frequency transactions, NFTs
Full DeFi dApps, NFTs, complex smart contract interactions
Decentralization
High, as all data is posted on-chain
High, but requires monitoring for fraud proofs
Medium to high (depends on participants staying online)
Medium (root chain is decentralized, but child chains can be centralized)
High, as all data and contract executions are posted on-chain
Privacy
Limited (data is posted on-chain in aggregated form)
Limited (fraud proofs require public data)
Moderate (off-chain state is private, but final state is public)
Limited (transactions recorded on the root chain)
Limited (data is posted on-chain in aggregated form)
Latency
Low (finality is quick)
Medium (due to fraud-proof challenge period)
Very low (instant finality, but requires interaction from both parties)
Medium (due to exit and challenge periods)
Low (finality is quick)
Exit Mechanism
No exit required (finality is guaranteed by ZK proofs)
Exit challenge period required to withdraw funds (fraud-proof)
No exit mechanism (channels are closed manually)
Requires exit challenges for withdrawing funds
No exit required (finality is guaranteed by ZK proofs)
ZK Rollups: Excellent for scalability and security but limited to simpler smart contracts. Great for payments and token transfers.
Optimistic Rollups: Supports complex smart contracts and dApps but has a delayed finality due to the fraud-proof mechanism.
State Channels: Ideal for high-frequency, low-latency interactions like micropayments. However, it’s not suited for complex DeFi applications.
Plasma: Focuses on off-chain scaling for high transaction volumes but has limited support for smart contracts and requires complex exit mechanisms.
ZK-EVM: Combines the scalability of ZK Rollups with full EVM compatibility, making it one of the most powerful solutions for scaling DeFi, dApps, and smart contracts.
This comparative table should give a clear overview of the strengths, weaknesses, and appropriate use cases for each Layer 2 scaling solution.
zkSync: A ZK Rollup platform designed to scale Ethereum by bundling transactions and using zero-knowledge proofs.
StarkNet: A decentralized ZK Rollup that uses STARK proofs to enable scalability for dApps.
Polygon Hermez: A ZK Rollup scaling solution integrated within the Polygon ecosystem.
Aztec: A privacy-focused ZK Rollup platform that offers private transactions on Ethereum.
Loopring: A ZK Rollup solution aimed at scaling decentralized exchanges (DEXes) and payments.
Scroll: A zkEVM-based ZK Rollup that is EVM-compatible for seamless deployment of Ethereum smart contracts.
Optimism: An Optimistic Rollup scaling solution that enhances Ethereum’s scalability while maintaining compatibility with Ethereum’s EVM.
Arbitrum: A leading Optimistic Rollup that scales Ethereum by reducing gas fees and supporting full smart contract functionality.
Boba Network: An Optimistic Rollup that focuses on enhancing transaction throughput and offers a hybrid compute feature for scaling dApps.
Polygon (formerly Matic Network): Offers a Plasma sidechain for scaling Ethereum along with support for other Layer 2 solutions like ZK Rollups and Optimistic Rollups.
OMG Network: A Plasma-based scaling solution that reduces transaction costs and increases throughput for Ethereum transactions.
Raiden Network: An off-chain state channel solution for fast, low-fee Ethereum token transfers.
Celer Network: A Layer 2 platform using state channels to scale dApps and micropayments with low latency.
Connext: A state channel solution designed for fast, trust-minimized cross-chain asset transfers.
Polygon PoS: A proof-of-stake (PoS) chain within the Polygon ecosystem that acts as a sidechain for Ethereum, offering fast and low-cost transactions.
Cartesi: A Layer 2 platform that uses optimistic rollups and off-chain computing to scale blockchain applications.
Fuel: A modular execution layer platform that enhances the performance of Ethereum through Optimistic Rollups.
Immutable X: A Layer 2 solution for NFTs built on ZK Rollups, designed for zero gas fees and instant trade confirmations.
zkSync Era: A ZK-EVM solution for fully compatible Ethereum scaling with smart contract functionality.
Polygon zkEVM: A ZK Rollup designed to scale Ethereum using EVM-compatible zero-knowledge proofs.
Scroll zkEVM: An Ethereum-compatible ZK Rollup that allows for smart contract deployment with ZK proofs.
These platforms are designed to increase throughput, reduce gas fees, and improve the user experience on Layer 1 blockchains like Ethereum. Each Layer 2 solution provides unique advantages depending on the use case—whether it's payments, DeFi, dApps, or NFTs.
Here’s a breakdown of some key Layer 2 use cases and how various solutions address them:
Problem: High transaction fees on Layer 1 blockchains like Ethereum make micropayments infeasible.
Layer 2 Solution: Platforms like zkSync, Loopring, and Celer Network enable micropayments with minimal fees, allowing fast, low-cost transfers suitable for everyday use cases like paying for a coffee or tipping in small amounts.
Problem: High gas fees and network congestion make DeFi protocols expensive and slow on Layer 1.
Layer 2 Solution: Optimism and Arbitrum scale Ethereum DeFi by offering lower transaction costs and higher throughput for dApps like decentralized exchanges (DEXs), lending protocols, and derivatives trading platforms.
Problem: High minting and transaction costs make NFTs expensive and inaccessible for smaller projects.
Layer 2 Solution: Platforms like Immutable X and Polygon zkEVM focus on NFTs, providing gas-free minting, instant transactions, and improved scalability for NFT marketplaces and games.
Problem: Slow settlement times and high transaction fees hinder trading efficiency on DEXs.
Layer 2 Solution: Loopring and dYdX use ZK Rollups to power fast, low-fee trading on decentralized exchanges, maintaining liquidity and reducing costs for traders.
Problem: Blockchain games and metaverse platforms need high-speed transactions and scalability to handle in-game asset transfers, rewards, and interactions.
Layer 2 Solution: Solutions like Polygon, Immutable X, and Celer Network enable faster transaction speeds and low-cost interactions, making it easier to onboard players and manage digital assets in real-time.
Problem: Transferring assets between blockchains is often slow and costly.
Layer 2 Solution: Platforms like Connext and Celer Network allow users to transfer assets between different blockchains efficiently by leveraging state channels and rollups.
Problem: Layer 1 blockchains are highly transparent, exposing transaction data to public view.
Layer 2 Solution: Platforms like Aztec (ZK Rollup) focus on enhancing transaction privacy, allowing users to make private transfers on Ethereum while benefiting from the security of Layer 1.
Problem: dApps experience bottlenecks due to the limitations of Layer 1 blockchains, resulting in poor user experience.
Layer 2 Solution: Platforms like Arbitrum, Optimism, and zkSync allow dApp developers to scale their applications, improving transaction speeds and reducing costs, while maintaining security.
Problem: Blockchains often struggle with the throughput needed for real-time tracking of supply chains.
Layer 2 Solution: Platforms like Polygon Hermez and Plasma Cash (a variant of Plasma) enable scalable tracking of assets and transactions, with reduced fees for real-world supply chain operations.
Problem: Simple token transfers on Layer 1 can be expensive due to gas fees.
Layer 2 Solution: Solutions like zkSync and Polygon make token transfers much more affordable, enabling fast and cost-effective movement of tokens like ERC-20 and ERC-721 between wallets.
Problem: Voting and decision-making in DAOs can be slow and costly due to high transaction fees.
Layer 2 Solution: Platforms like Optimism and StarkNet allow for cheaper and faster governance processes for decentralized autonomous organizations (DAOs), ensuring a more seamless decision-making process.
Problem: Running complex financial derivative contracts can be costly and slow on Layer 1 blockchains.
Layer 2 Solution: Solutions like Arbitrum and dYdX help execute high-speed derivative trades and manage complex financial products efficiently with reduced gas fees.
Problem: Security issues like fraud are a risk for Layer 1 blockchains.
Layer 2 Solution: Optimistic Rollups offer fraud-proof mechanisms, allowing for fraud detection and rollback in cases of invalid transactions, ensuring enhanced security.
Problem: Sending cross-border payments using blockchain technology can be slow and expensive.
Layer 2 Solution: State channels and Rollups (like those in zkSync or StarkNet) facilitate faster and more affordable cross-border payments, which is crucial for remittance use cases.
Problem: Web3 applications face bottlenecks on Layer 1 blockchains.
Layer 2 Solution: zkEVM solutions like Polygon zkEVM or Scroll zkEVM enhance scalability for Web3 applications, making them run efficiently and cost-effectively while maintaining compatibility with Ethereum’s EVM.
These use cases demonstrate how Layer 2 solutions help overcome the limitations of Layer 1 blockchains in terms of transaction speed, cost, scalability, and privacy, enabling a wide variety of applications across industries.
Layer 2 solutions are designed to enhance and complement Layer 1 blockchains, but fully “taking over” Layer 1 is unlikely because they serve distinct roles within the ecosystem. Here’s how they might coexist or shift in significance over time:
Scalability and Efficiency: Layer 2 solutions, like rollups on Ethereum or Lightning Network on Bitcoin, are highly efficient for handling large volumes of transactions. They reduce costs and improve transaction speeds, which could lead to more everyday users and applications moving to Layer 2. This might make Layer 1 chains primarily a base of record, ensuring security and decentralization while relying on Layer 2 for scalability.
Interoperability: Many Layer 2 networks aim to interoperate seamlessly with Layer 1s, offering a middle ground between decentralized security and practical transaction costs. Over time, we might see Layer 1s focusing primarily on validation, while the majority of transactions occur on Layer 2s.
Security Reliance: Layer 2s rely on Layer 1 for their security, anchoring their data on the base layer to inherit its decentralized trust. This dependence means that as long as Layer 1 remains secure and robust, Layer 2s will use it for finality and immutability.
User Experience and Adoption: Layer 2 solutions have gained popularity due to their cost-effectiveness and user experience, especially for consumer-facing applications like gaming, DeFi, and payments. If they continue evolving and improving, they may attract most end-users and developers, effectively handling the majority of user interactions, while Layer 1 becomes the underlying security infrastructure.
Layer 1 Upgrades: Layer 1s are also evolving (e.g., Ethereum’s move to Proof of Stake and potential sharding). With these upgrades, Layer 1s could enhance their scalability and lower fees, potentially challenging the need for Layer 2 in some areas. However, Layer 2s are likely to remain crucial for specific use cases requiring ultra-low fees or high throughput.
While Layer 2s are becoming increasingly prominent and essential, they complement rather than replace Layer 1s. A future where Layer 2 handles most user interactions, and Layer 1 focuses on security and final settlement, seems probable rather than a complete market takeover.
