A Look Under the Hood Into Ethereum Technology and Scaling Solutions

Below is simply an excerpt from a lengthier report which covers Ethereum more generally: its adoption, DeFi, token distribution, tokenomics, governance, vulnerabilities, roadmap, and more. So, if there are any pieces that feel incomplete or lack context, that may be why. Also, some metrics are outdated. This is because our report is for Premium members of CryptoEQ.io. For the full report and up-to-date metrics (for Ethereum and ~30 other top projects), sign up for just $10/month here.

Ethereum Technology

Consensus Mechanism
Ethereum utilizes an optimized version of Nakamoto Consensus, where Nakamoto Consensus is a specific block-leader selection implementation of Proof of Work (PoW) consensus that is used in Bitcoin to ensure all the participants agree on the state of the public ledger (blockchain) and solve for the “double spend” problem. Specialized computers across the globe are all responsible for updating and maintaining the Ethereum blockchain, thereby creating a distributed consensus system. Ethereum’s network is known as the Ethereum Virtual Machine (EVM) which is a set of thousands of public nodes running the client software that execute the computations (i.e., programs or transactions).

More specifically, these operations are collectively known as mining: a process by which transactions are verified and added to the public blockchain ledger (onto a block). These highly specialized supercomputers (miners) compile the transactions into the blocks and compete to solve computationally-intense puzzles. If they are successful in solving the puzzle, they are rewarded with a certain amount of ETH (currently 2 ETH). Upon solving the puzzle, the miner will broadcast their success to the other miners and thus prove that they have done the work (Proof of Work) and can be trusted. The significant costs (electricity to run the calculations) inherent to solving for a block make it cost-prohibitive for a bad actor to act dishonestly in the system. Trying to harm the blockchain would require the cost of acquiring 51% of the network computing power, and then, if successful, degrade the integrity of the ETH blockchain by creating false transactions. This attack would soon be realized by the network users and cause the price to plummet, leaving little to no reward for the attacker. PoW is thus so successful because of the application of game theory in the use of incentives. This will all change once the network transitions to a PoS model and thus the potential attack vectors and vulnerabilities will change too.

Ethereum optimizes this consensus mechanism by using the Ethash mining algorithm rather than Bitcoin’s SHA-256, and aiming for a block time of ~14 seconds as opposed to 10 minutes in Bitcoin’s case.

Ethereum also employs the use of gas (to measure computational effort) – a derivative of its native cryptocurrency Ether commonly denominated in gwei – for mitigating spam and allocating resources on the network. Ethereum's scalability on the base layer is limited by the block gas limit rather than the block size. There is an upper threshold on the amount of gas that can be expended in a block with 30 million gas being the absolute maximum.

Beginning in mid-2021, Ethereum introduced variable-size blocks (EIP-1559 discussed in detail later). Each Ethereum block targets a size of 15 million gas but the size of blocks will increase or decrease in response to network demand but will not surpass the 30 million limit.

Ethereum’s average block size was up ~30% in 2021 due to a network upgrade that increased the per-block gas limit. Ethereum’s block size is larger because of an increase in the gas limit, enabling more transactions to fit into a block. The average block at the time of writing is ~85 KB, compared to ~40 KB in 2020. Increasing the gas limit (and therefore the block size) allows for higher performance (the possibility of more transactions per second) but it also accelerates the amount of state stored on the mainchain, also sometimes called "chain bloat." The mainchain went up from 610 GB to 875 GB as of July 2021.

Scaling the Ethereum Network
On-chain scaling techniques are upgrades made to a blockchain’s base layer to improve scalability. Ethereum’s long-term, on-chain scaling solution is called sharding which actually splits the base layer into 64 chains with shared security ensured by the Beacon Chain.

Off-chain scaling refers to scaling solutions that use external execution layers rather than the base layer. These Layer 2s, or “L2s” are secondary layers that sit on top of the base layer, providing more transactional capacity for the blockchain overall. Ethereum is pursuing both off-chain and on-chain scaling strategies.

Ethereum’s eventual transition to Proof of Stake is a response to these challenges. It’s a massive upgrade to the entire Ethereum ecosystem to accommodate continued growth and an increasing workload, consume less electric power in its verification process, and to be more secure from attacks. In essence, the Ethereum upgrade will make the network more scalable, sustainable, and secure.

Any human enterprise which is highly successful early on will quickly have to address how to do more to keep up with demand. This is a good problem to have, but not an easy one to solve because scaling up often challenges the core values that made the enterprise successful.

Ethereum, as we know it today, won't scale. Meaning, the Ethereum L1 is designed to remain a highly decentralized, global settlement layer above all else. However, Ethereum's web of L2s will be responsible for scaling Ethereum and serving as its execution layer. These layers will absorb much of the existing value on Ethereum mainnet plus future inflows as Ethereum adoption grows. It's important to understand that Ethereum's web of L2s is a marketplace of independent projects competing with each other to help scale Ethereum.

The Scalability Trilemma
Ethereum’s ability to process transactions is (partially) constrained by the amount of computing power, bandwidth, and storage on the network. The scalability trilemma is a well-known issue among all blockchains.

The scalability trilemma, illustrated. Credits: Vitalik Buterin
The scalability trilemma, illustrated. Credits: Vitalik Buterin

A blockchain can achieve two of these traits but at the expense of the third. Many alternative layer 1 (L1) chains have chosen to sacrifice decentralization for scalability and security. However, it’s important to remember why decentralization is important. It provides the chain anti-fragility, robustness, reliability, and censorship resistance.
The goal is to increase the number of transactions while retaining sufficient decentralization. What are the decentralization sacrifices (tradeoffs) other smart contract L1s have made? Other chains typically make two sacrifices. They either design their network to be run/secured with high-powered, expensive nodes, which reduces the number of people that may participate in network consensus by pricing them out. Obviously, a network that can only be verified if you have X amount of dollars in computing budget is not an ideal, permissionless system.

Another tradeoff often considered is for the network to use fewer nodes to achieve consensus in les time. However, this makes the chain more vulnerable and centralized. It is easier to corrupt or destroy 10 nodes rather than 10,000 all over the globe. Although often discussed as such, blockchain scalability does not just pertain to TPS. Many L1s, like Binance Smart Chain (BSC), currently boast high TPS numbers but suffer from “chain bloat” and ever-increasing hardware requirements just to keep the chain running. L1s must be able to process more transactions without creating more problems down the road. A node in a technically sustainable blockchain has to do three things:

-Keep up with the tip of the chain (most recent block) while syncing with other nodes.

-Be able to sync from genesis in a reasonable time (days as opposed to weeks).

-Avoid state bloat.

Requirement 1 above is a physical limitation based on computing power (RAM, CPU, etc.) and bandwidth. These are bottlenecks for every node which means there are upper, finite limits to how far you can push the network.

One way for Ethereum to increase its workload could be to increase the size of the computers participating in the Ethereum network (participating computers are called “nodes”). But larger, more expensive, and fewer computers in the network (like Solana) is clearly a form of centralization. Having a small number of bigger players involved in maintaining Ethereum is not Ethereum’s goal.

Fewer computers in the network also creates security issues. A hacker attacking just a few computers, or a single central computer will have an easier time than attacking a huge number of computers all in agreement about the data they are using and creating. Just as with Bitcoin, more computers participating in the Ethereum network enhance the security and permanence of the data on the Ethereum blockchain.

Transitioning from PoW to PoS (“The Merge”)

The Merge is the term used for when Ethereum switches from Proof-of-Work (PoW) to a Proof-of-Stake (PoS) blockchain. This is slated to occur in Q2 2022 and bring with it many benefits that were not previously possible with PoW.

PoS removes the energy consumption often cited in the mainstream media. While PoW is not inherently a bad thing, it’s inarguable that the world is highly critical of energy consumption and now, with the transition to PoS, Ethereum will have eliminated this one enormous criticism. Estimates from Ethereum core developers hypothesize that Ethereum’s energy use will drop by up to ~99%. Without the need for so much physical mining hardware and infrastructure, Ethereum can become a more energy-efficient, geographically-distributed, and nimble blockchain.

Ethereum’s eventual transition from Proof of Work (PoW) to Proof of Stake (PoS) will represent the culmination of the original Ethereum protocol design, 5+ years of technical research and associated game theory design. It is designed, ultimately, for a simpler, more robust, stable, and secure base layer protocol with full lite client verifiability. After the full implementation is complete, the base layer can then “ossify” while leaving the flexibility for innovation on higher protocol levels like Layer 2. The Beacon Chain serves as the epicenter of the future architecture and network consensus. PoS aims to lower the cost of participating in securing the network by allowing anyone with ETH to stake rather than needing a giant million-dollar mining farm as is the case in most PoW networks.

With PoS, the Ethereum base layer will be managed by validators rather than PoW miners. A validator is a person or entity who locks up (stakes) 32 ETH in order to run a validating node and secure the Ethereum blockchain. This means rather than relying on energy/electricity for security as is the case in PoW, Ethereum security will rely upon capital instead. With PoS and staking rewards, ETH becomes a productive capital asset with yield as well as a the money underpinning network transactions and executing smart contracts.

Beacon Chain

Key takeaways from the early instantiations of the Beacon Chain are:

- Introducing the ETH Proof of Stake consensus layer;

-Tracks ETH validators and balances;

-One-way ETH deposit to stake on the Beacon Chain; and

-No state management (transactions, smart contracts).

The Beacon Chain will be the center of Ethereum’s new consensus mechanism, assuming the full transition goes ahead. The Beacon Chain will be responsible for the liveness, veracity, and consensus on the new chain. Future sharded layers (shards) will all connect back to the Beacon Chain with many validators across all 64 shards. The Beacon Chain will provide the foundation for hundreds of thousands of validators, distributed across thousands of nodes globally. It will organize validators into committees and apply the consensus rules that dictate the network.

A slot is when a block is added to the Beacon chain. Every 12 seconds there is a slot and 32 slots (6.4 min) are grouped into an epoch. Casper FFG decides on which blocks become part of the chain, finalizing an epoch. Every epoch, one validator is pseudo-randomly assigned by a beacon to a slot and shard. At least one committee, a group of validators (minimum of 128) is also chosen to attest the epoch.

Additionally, PoS is a predecessor for sharding, another critical Ethereum protocol change that will separate the chain into many concurrent threads (discussed more below).


Sharding is the term for horizontally partitioning a database and does not create more burden for the average user. In this sharding model, validators are assigned to specific shards and only process and validate transactions in that shard. In Ethereum's planned sharding model, validators are randomly selected. Every shard has a (pseudo) randomly-chosen committee of validators that ensures it is (nearly) impossible for an attacker controlling less than ⅓ of all validators to attack a single shard. ​​

After the switch to Proof-of-Stake, sharding is the next significant hard fork upgrade on Ethereum’s roadmap. Just like the Merge, the sharding plan has evolved over time and may continue to change between now and implementation.

Sharding is the partitioning of a database (or blockchain) into subsections. Rather than building layers atop one another (e.g. L2s or Bitcoin’s Lightning Network), sharding scales out or horizontally without a hierarchy or layered structure. Doing so does not create more burden for the average user.

Original diagram by Hsiao-wei Wang, design by Quantstamp
Original diagram by Hsiao-wei Wang, design by Quantstamp

Shards will be divided among nodes so that every individual node is doing less work. But collectively, all of the necessary work is getting done—and more quickly. More than one node will process each individual data unit, but no single node has to process all of the data anymore.

In Ethereum’s vision of a sharded chain, a (pseudo) randomly-chosen committee of validators are randomly selected and assigned to specific shards. This means they are only responsible for processing and validating transactions in those specific shards, not the entirety of the network. The randomness of the validator selection process ensures it’s (nearly) impossible for a nefarious actor to successfully attack the network. Initially, prior to the breakthrough in rollups, Ethereum’s plan was to do sharded computation. However, now with rollups providing the much-needed network scalability, sharding will focus on data availability to provide throughput for the rollups. This is because the bottleneck for rollup scalability is data availability capacity rather than execution capacity. This will give L2s more space to store the chain’s data and offer additional data capacity for rollups.

In a sense, shards will serve as data storage “buckets” for new network data storage demand from rollups. This enables tremendous scalability gains on the rollup execution layer. Just as significant, shards will also help avoid putting overly-onerous demand on full nodes, allowing the network to maintain decentralization.

Sharding will be released in a multi-step process to provide immediate data availability for rollups before releasing the ultimate but more complex vision. A small subset of data shards (four) will initially be released to keep complexity low, i.e. a slow, controlled rollout.

Earlier, we outlined one reason why Ethereum transaction fees were so high was due to all nodes in the network having to process all transactions and reach consensus. Sharding is the answer to the question, “What if each node did not have to process every operation at the same time?” What if, instead, the network was divided into subsections (shards), that operated semi-independently until finally reaching consensus through a central hub (Beacon Chain)?

Shard 1 could process one batch of transactions, while Shard B processes another batch. This would effectively double the transaction throughput of a blockchain, since our limit is now what can be processed by two nodes at the same time. If we can split a blockchain into many different sections, then we can increase the throughput of a blockchain by many multiples.

Ethereum will be split into different shards, each one independently processing transactions. Sharding is often referred to as a Layer 1 scaling solution because it’s implemented at the base-level protocol of Ethereum itself.

The launch of Ethereum’s Beacon Chain in December 2020 marked an enormous milestone that has been on the roadmap from the early stages of the project in 2015, and has already become the largest, most decentralized PoS blockchain with ~250,000 validators.

There are several different ways a user can stake ETH. The most autonomous and preferred method is to personally run a staking node. However, this requires at least 32 ETH plus some intermediate technical knowledge around the protocol, nodes, and computer hardware.

Another option is staking on centralized exchanges like Coinbase, Binance, Kraken, and others. These exchanges take custody of your ETH, stake them on the user's behalf, and take a cut of the profit. This abstracts away the difficulties of running your own validator but comes with the tradeoff of giving up custody and some of the profits. The top four staking entities include traditional centralized exchanges Kraken and Binance, liquid staking protocol Lido, and Staked.us. which make up 36.6% of total ETH deposits. Kraken holds 750,000+ ETH from 9,000 unique Ethereum accounts.

Eth2 depositors by type, January 2022. Source: CoinMetrics
Eth2 depositors by type, January 2022. Source: CoinMetrics
ETH staking metrics as of 2/15/21. Source
ETH staking metrics as of 2/15/21. Source

Decentralized solutions like Lido and Rocket Pool, which enables "liquid" staking are gaining traction. In the case of Lido, users stake ETH and, in return, get stakers tokens (stETH), essentially a derivative product of ETH that trades near 1-to-1 with ETH. This gives stakers more flexibility and liquidity since they can sell their stETH tokens on the open market or use the stETH tokens in other DeFi protocols. As of Q1 2022, Lido holds ~18% of all ETH staked. Staking derivatives are the most efficient route for holders of PoS tokens that want to maximize yields and utility in DeFi. Starting 2021with just ~17k ETH deposited, Lido’s staking pool has grown to ~1.64m ETH (as of Q1 2022). There are ~23.3k unique depositors, however, the top ~35 depositors are responsible for ~45% of all ETH staked, suggesting that a few large whales make up nearly half of the Lido stake.

EIP-1559 & Fee-Burning
Finally, the PoS upgrade will reduce Ethereum’s inflation rate from ~3.5% to near zero. Thanks to the implementation of EIP-1559 and its fee burning mechanism in mid-2021, Ethereum’s net issuance is expedited to become deflationary once the Merge is released. EIP-1559 changed Ethereum’s fee structure where transaction fees now have a base fee and a tip. The base fee is set by the protocol and adjusts every block based on network activity. The base fee no longer goes to miners but is instead burned. The tip is set by the market (can be zero in times of little congestion) and will go to the miners.As of Q1 2022, since EIP-1559’s successful roll-out in August of 2021, over 1.75M ETH have been burned.

All of these big changes are being made in an effort to provide increased scalability for the Ethereum chain which, since 2020, has regularly experienced periods of congestion and high network fees. The Merge, although important, is just one step in an enormous transformation for Ethereum.

This traditional monolithic, do-it-all blockchain faces unavoidable limitations due to the inefficient nature of decentralized consensus. These limitations lead to higher transaction costs for its users as the chain becomes more adopted and used. Full stop. This is because blocks and blockspace on the execution layer of a chain are scarce. There are only so many blocks that can be verified and added to the chain each second/minute. Once demand outstrips this finite resource, the only recourse users have left to ensure their transaction gets into a block (and executed) is to pay more than the market rate for transaction fees.

Side Chains
In the context of Ethereum, sidechains are separate, Ethereum-compatible blockchains. Sidechains can be independent EVM-compatible blockchains, but more likely, they are application-specific blockchains catering to Ethereum users and use cases like Polygon or Ronin.

Sidechains design themselves to be EVM-compatible so they can essentially copy and paste their code to easily interoperate with Ethereum and all of its infrastructure including wallets, block explorers, and more. Projects like Binance Smart Chain, Avalanche, Tron, Celo, Fantom, and more are all examples of competing L1 EVM chains except with their own token.

Users send their L1 funds by way of a cross chain transfer enabled by a two-way peg (2WP) protocol that locks the assets on the L1chain, then creates/mints an equal amount on the sidechain with a cryptographic proof that the lock was done correctly. If users had funds on a sidechain and the network went down (like Solana in Q4 2021), there is nothing a user can do and their funds are stuck until the chain is brought back online. However, rollups (the preferred scaling solution for Ethereum, discussed below) contain immutable “escape hatches” that always ensure a user can exit back to mainnet even if the rollup network is offline. Users can always manually submit transactions to the mainnet Ethereum rollup contract as you need, including exiting the rollup with your funds.

Some sidechains are purposely built to be complementary to Ethereum and offload some specific Ethereum use cases onto themselves. Because of this, sidechains increase the scalability of Ethereum by serving as external execution layers for L1 Ethereum. However, it's important to remember that sidechains do not provide the same amount of security as L1 Ethereum.

Second Layer Solutions

Source: @yasminekarimi_
Source: @yasminekarimi_

Layer 2 or second layer scaling is a general term for solutions that help with increasing the capabilities of the main chain by handling transactions off-chain (off Layer 1). L1 serves as the security and consensus layer that cryptographically secures and stores data transactions on the immutable blockchain ledger. L2s can extend the utility of Ethereum outwards, letting users have increased scalability off of the blockchain that can still refer back to the main chain if necessary. The two primary improvements Layer 2 can provide are transaction speed and transaction throughput. On top of that, Layer 2 solutions can greatly reduce gas fees.

Interoperability between siloed blockchains has been a known problem for years in the crypto ecosystem. Only beginning in 2021 have real solutions been brought forth, ranging from “bridge” to sidechains to competing Layer 1s (L1s). Alternative L1s are competing with Ethereum for liquidity and total value locked (TVL) while Ethereum gas prices remain prohibitively expensive for most use cases. A dashboard on Dune Analytics displays the current bridges to the Ethereum network like Polygon and rollups, Arbitrum and Optimism. As of Q1 2022, there is ~$28B in TVL bridged from Ethereum to other networks, presumably looking for cheaper fees and/or higher yield.

Source: Dune Analytics
Source: Dune Analytics

Rollups are a type of L2 scaling solution that enable exponential scalability without sacrificing security. The primary innovation of rollups is to move computation off-chain, while storing only the bare minimum of transaction data on-chain. The rollup chain handles all of the expensive and computationally-dense data processing, reducing the burden on the Ethereum blockchain. This removes the burden of data on Layer 1 while also allowing Layer 2 transaction data to be available on Layer 1 for validation. Rollups remove everything from being done on-chain (monolithic) to the Ethereum mainnet now serving as the settlement layer for off-chain L2 interactions (modular design). Rollups can be thought of as branches off of the main trunk of Ethereum that increase the computation surface area of Ethereum.

Ethereum scaling development is hyper-focused on rollups (plus some plasma and channels) as a scaling strategy for the near to mid-term future. In all likelihood, in the future, Ethereum users will primarily conduct their activity on a L2 rather than the L1 due to the cheap transaction fees and security guarantees. Meanwhile, the Ethereum mainnet will become a settlement layer for the L2 ecosystem.

Compared to sharding, which involves changing the L1 protocol and therefore presents greater risk to the ~$400 billion network, rollups are relatively low risk, available now, and possibly even more powerful. Optimistic rollups are a promising extant scaling technology that can be incorporated (and expanded upon) quickly.

In its simplest form, a rollup chain executes Ethereum transactions on its own chain, “rolls” them up into a batch, before Ethereum receives and stores the data. The Ethereum mainnet needs some way to verify that such (off-chain) transactions are valid. This is achieved via cryptographic proofs, like validity proofs for ZK-rollups (ZKRU) and fraud proofs for Optimistic rollups (OR). A rollup needs orders of magnitude less validators than L1 to maintain its security. As long as a single honest validator does its job, the network will remain secure.

Rollups offer similar capabilities as Plasma, but without suffering from the “data availability problem”. Rollups offer many-to-many transactions, smart-contract capabilities, and significantly reduced total L1 block space requirements all while extending Ethereum’s security assurance to the L2.

With rollups, Ethereum can go from ~25 to 3,000+ TPS without sacrificing security. What makes rollups such an attractive scalability technology is the fact that users' funds cannot be stolen or censored (as is the case on some sidechains) and that no one can prevent users from exiting the rollup whenever they wish. Users can always access data on L1 to safely exit the rollup chain with their funds.

There are two (primary) types of rollups: ZK-rollups (ZKRU) and Optimistic rollups (OR). ZK-rollups are (theoretically) faster and more efficient than Optimistic rollups, but they suffer from friction and compatibility issues when migrating smart contracts to Layer 2. ZK-rollups submit transactions to the mainnet using a cryptographic verification method called a zero-knowledge proof—more specifically—a zk-SNARK (Succinct Non-interactive Argument of Knowledge). zk-SNARKs allow someone to prove they have a particular piece of information without actually revealing the actual information itself. This zk-SNARK approach is also called using validity proofs, i.e. highly complex cryptography to ensure all L2 transactions are valid and correct. The proof is submitted and checked by an on-chain L1 contract.

ZK-rollups (ZKRU) are separate blockchains networks with very few specific nodes (called Provers). Where Provers are a select set of nodes in charge of computing all of the transactions and aggregating them into a zk-SNARK. Because of the complicated computations involved, the Provers run on dedicated hardware, making them more centralized and opaque. The good news is that because of the validity proof, it’s mathematically impossible for them to submit fraudulent data. The only trust involved is trust in cryptography/mathematics.

ZKRU that have a cryptographic proof that links them to Ethereum’s mainnet. This link prevents the rollup from censoring or stealing funds while maintaining the immutable properties of the Ethereum L1. This proof is called a validity proof, ensuring the validity of the off-chain transactions, making them instantly verifiable and removing the need for a withdrawal/challenge period.

ZKRUs improve scalability by moving computations and storage off-chain where computation is expensive. They separate the transaction execution from the consensus and data availability. To submit the transactions onto the consensus layer, ZKRUs then cryptographically prove every batch of executions on the rollup and send only the proof to the L1. Zero-knowledge cryptographic proofs reduce the computing and storage resources for validating the block by reducing the amount of data held in a transaction; zero knowledge of the entire data is needed. However, because every transaction in the rollup still stores its input data (calldata) on the L1, all L1 nodes have the information they need to verify the transactions, if needed.

Remember, rollups batch together large amounts of off-chain transactions, compress them into a single transaction, and eventually find their way to the Ethereum L1. Because ZKRU do not assume all transactions are valid, validity proofs must be sent with every ZK-rollup batch to cryptographically prove the validity of transactions. While a bit more technically cumbersome, this means that transactions are final once they are validated by the settlement layer. To describe the process in detail:

  • Highly-compressed batch of transactions are combined together with the current state root
  • Combination is sent to an off-chain Prover
  • Prover computes the transactions, generating a validity proof of the results
  • Prover then sends this to an on-chain Verifier (Ethereum nodes)
  • Verifier verifies the validity proof
  • Smart contract on Ethereum’s L1 that maintains the state of the Rollup is updated to the new state
Source: EatTheBlocks
Source: EatTheBlocks

On mainnet Ethereum, each transaction is executed by every node. With ZKRU, only one node needs to actually do the computation (the Provers) and then produces a zero-knowledge proof of it.

Then, every other node (Verifier) simply verifies this proof instead of having to do the full computation. The proof allows each node to verify the provided state is valid. Verifying the proof is much less intensive than actually computing it, which is where the scalability improvements are created. Therefore, Verifiers don’t need special high-end hardware to verify the proof. They simply use their existing hardware, creating no new stress or burden for current nodes. Only state transitions and a small amount of calldata need to be processed and stored by the nodes. With this system, nodes can easily agree on a common state and it puts the burden of execution on a single node instead of the whole network.

It is strictly not possible for operators to steal the funds or corrupt the rollup state. ZKRU relies on the censorship-resistance of L1 only for its liveness, not for its security. There is no need for anyone to monitor the ZKR. After a block is verified, user funds are always guaranteed to be eventually retrievable, even if operators refuse to cooperate. While validity proofs are complex and expensive (relative to Optimistic fraud proofs), verification by the L1 is simple, making them—even still—cheaper than a regular L1 transaction. However, due to the complex computation involved in the validity proofs, special-purpose hardware may be needed to run a node, creating a centralizing effect and less open network.

Optimistic Rollups, meanwhile, are not secured by cryptographic zero-knowledge validity proofs. Instead, ORs “optimistically” assume all transactions are valid with dispute resolutions, a withdrawal period, and crypto economic incentives to maintain the integrity of the data. Essentially, it’s an “innocent until proven guilty” model with watchdogs in place. If the watchdog can mathematically prove that fraud occurred by submitting the correct fraud proof, the rollup will revert the fraudulent transactions, penalize the fraud, and even reward the watcher.Anyone may submit a rollup block. However, all other nodes can execute the same transactions, essentially “checking the work” of the submitter. Only one honest actor is needed to submit the fraud proof and challenge any questionable block. This means fraud proofs are not sent with every batch of transactions. Instead, they’re only used when an entity wants to dispute a transaction—e.g. attempt to prove whether there are any fraudulent transactions in a rollup batch.

They sacrifice some scalability for increased compatibility with the Ethereum Virtual Machine. Optimistic rollups run an EVM-compatible Virtual Machine called OVM (Optimistic Virtual Machine) which removes the compatibility issues that exist in ZK-rollups. This is extremely critical as composability is paramount in the Ethereum ecosystem, especially in DeFi. By using a virtual machine called the Optimistic Virtual Machine (OVM), they allow developers to easily deploy code and projects on the secondary chains. On the other hand, there’s no cryptographic proof that the state transition submitted to the main chain is correct.

The drawback to this system is the delay when users move funds between the rollup and Ethereum and for transactions to be considered final. Because “watchers” need time to detect fraud, users’ funds typically take a week to be withdrawn and available for further use. ORs can only be considered safe with a ~one week challenge window. These dispute windows are expected to come down over time and, in fact, some third-party solutions (HOP, Connext) already exist to remove this delay entirely. When discussing rollups and any L2, users also have to consider how long it takes for their transaction on the rollup to be submitted and considered final on the L1. This is known as time to finality. When it comes to rollups, ZKRs post very complex proofs that can range from 500k-5M gas, whereas ORs are ~50k gas, or 10-100x smaller. Therefore, OR can provide faster L1 finality when compared to ZKRUs (for the same cost).

The Surge, a step on the Ethereum roadmap, consists of multiple upgrades that are designed to improve rollups like EIP-4488 or blob-carrying transactions. These will reduce transaction fees by ~5x. The final upgrade in The Surge roadmap is danksharding - a data layer built specifically to accelerate rollups. This integrates data availability sampling, meaning the more decentralized the network, the more capacity there is for rollups. As bandwidth improves and Ethereum decentralizes, capacity will continue to increase into the millions of TPS.

A general list of Ethereum Layer 2 scaling solution projects includes:

Since launching Optimism, Loopring, and Arbitrum One in 2021, variations of rollups, the total value locked (TVL) on L2 scaling solutions has more than tripled to $5.5B.

Source: L2Beat
Source: L2Beat

Privacy Tech
Ethereum has been researching zero-knowledge proof (ZKP) implementations for several years. Forms of ZKPs – such as Bulletproofs and zk-SNARKS – are employed in Monero and ZCash, respectively. Following the proliferation of ZKPs is the interest in zk-SNARKS. The interest centers not only on privacy, but also scaling, as transactions can be aggregated into batches using the technology.

zk-SNARKS are a method of obfuscating all of the details of a transaction (i.e., the amount transferred, sender identity, receiver identity) without compromising the ability to verify that the transaction is valid. The concept is predicated on extremely complex mathematics, but has shown such promising potential that even banks and governments are beginning to research their advantages.

In late 2018, a new zero-knowledge privacy protocol entitled AZTEC was introduced on the Ethereum mainnet. The new privacy technique keeps the values in a transaction encrypted and private from outsiders while still allowing the logic and validity of the transaction to be validated by all. While most Ethereum transactions do not utilize this technology currently, the AZTEC multi-purpose zero-knowledge exchange implementation has been released.

Privacy on Ethereum took many steps in 2019 with the launches of several privacy mixers, Ernst and Young’s release of “Nightfall” code, and the alph launch of the decentralized exchange Starkdex. Privacy is also inherent in bidirectional payment channels with Raiden, so users who transact off-chain can be assured a level of privacy not seen with other standard on-chain Ether transfers.

Beginning in 2020 and continuing into 2021, Tornado Cash, an Ethereum-based mixer, which obscures the on-chain tie between transaction recipient and sender gained sizable adoption. Tornado Cash remained Ethereum's primary privacy tool. Its TVL grew from ~$55 million to ~$700 million in 2021 as well as launched on Ethereum's L2, Arbitrum.

The sheer size and fluidity of developments on Ethereum can be somewhat confusing. Currently, privacy tech developments are secondary in priority to scaling improvements, but the eventual integration of zk-SNARKS into Ether transactions could effectively enhance both properties concurrently. Platforms built on Ethereum – such as Gnosis – are researching zk-SNARKS further, and it is likely that their implementation will happen at an isolated level before launching network-wide.

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