Ethereum plasma roadmap
Published 19.08.2021 в Play free online betting games for final four
These channels allow for deposits and withdrawals of funds with state transitions enforced by fraud proofs, such that the accounts of the child chains match the accounts of the root chain. In other words, transactions can be processed on Plasma child chains and enforced on the root chain in the event of invalid blocks, thereby increasing scalability by reducing the amount of computation necessary for the root chain.
This is accomplished without involving custodial trust in 3rd parties and while maintaining high Byzantine fault tolerance. Overview of How Plasma Works Depending on their complexity, smart contracts can require significant amounts of computation per transaction relative to a basic cryptocurrency transactions.
The idea of Plasma is to perform more complex operations with heavy computation off-chain i. This works by first reframing all blockchain computation into a set of MapReduce functions. MapReduce is a programming model invented by Jeffrey Dean and Sanjay Ghemawat of Google and first published in an academic paper in All of this is going to have to change. We would need to adapt to a world where users have their primary accounts, balances, assets, etc entirely inside an L2.
There are a few things that follow from this: ENS needs to support names being registered and transferred on L2; see here for one possible proposal of how to do this. Layer 2 protocols should be built into the wallet, not webpage-like dapps. We ideally want to make L2s part of the wallet itself metamask, status, etc so that we can keep the current trust model.
This support should be standardized, so that an application that supports zksync payments would immediately support zksync-inside-Metamask, zksync-inside-Status, etc. We need more work on cross-L2 transfers, making the experience of moving assets between different L2s as close to instant and seamless as possible.
More explicitly standardize on Yul or something similar as an intermediate compiling language. To allow an ecosystem with different compiling targets, but at the same time avoid a Solidity monoculture and admit multiple languages, it may make sense to more explicitly standardize on something like Yul as an intermediate language that all HLLs would compile to, and which can be compiled into EVM or OVM.
We could also consider a more explicitly formal-verification-friendly intermediate language that deals with concepts like variables and ensures basic invariants, making formal verification easier for any HLLs that compile to it. Some of this can be covered by common public-good-funding entities such as Gitcoin Grants or the Ethereum Foundation, but the scale of these mechanisms is just not sufficient to cover this level of funding.
However, layer 2 projects launching their own token is sufficient - provided, of course, that the token is backed by genuine economic value ie. Leaving open this space can thus be a good strategic move for the long-term economic sustainability of Ethereum as a whole. In addition to the funding issues, the most creative researchers and developers often want to be in a position of great influence on their own little island, and not in a position of little influence arguing with everyone else on the future of the Ethereum protocol as a whole.
Furthermore, there are many already existing projects trying to create platforms of various kinds. A rollup-centric roadmap offers a clear opportunity for all of these projects to become part of the Ethereum ecosystem while still maintaining a high degree of local economic and technical autonomy. It seems very plausible to me that when phase 2 finally comes, essentially no one will care about it.
Everyone will have already adapted to a rollup-centric world whether we like it or not, and by that point it will be easier to continue down that path than to try to bring everyone back to the base chain for no clear benefit and a x reduction in scalability. This may actually be a better position for eth2 to be in, because sharding data availability is much safer than sharding EVM computation.
For example Ethereum is currently able to make transactions per seconds.
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Reversing a finalized block would require malicious action by two-thirds of the total validator stake, and resultantly, the protocol guarantees they would be slashed at least one-third of the total network stake4. This is referred to as economic finality — while a finalized Beacon Chain block can be reversed at a later date, unlike a protocol that achieves absolute finality such as Tendermint, it is impossible to do so without having a prohibitively large amount of stake slashed.
Note that the checkpoint block illustrated in the graphic represents the source checkpoint. Additionally, proof-of-stake has an asymmetric cost advantage that should disincentivize chain reorgs even more so than proof-of-work. The cost to a miner of attempting a chain reorganization and failing under proof-of-work is the electricity cost of their hashrate and the opportunity cost of coins that could have been mined on the canonical chain. The proof-of-stake reorganization equivalent requires a malicious validator to front as much as two-thirds of the total Ethereum stake, understanding that they will be slashed at least one-third of the total network stake after reorganizing a finalized block.
Whether the impediment is from validators being offline due to a client issue or a fork caused by a consensus disagreement, the inactivity leak is designed to penalize validators that impede finality by failing to attest to the chain, and it will eventually allow for the chain s to finalize as the impeding party accrues quadratically growing penalties until a supermajority is reclaimed.
Rewards and penalties are aggregated across slots and paid to validators every epoch. Rewards issued for validating the chain are dynamic and depend on the total amount of ETH staked in the network. Specifically, the total ETH issued to validators in aggregate is proportional to the square root of the number of validators. This mechanism incentivizes validators with larger issuance rewards when there are fewer validators participating in consensus, and it decreases the incentive as the validator set grows and attracting additional validators becomes less essential.
However, the average yield from issuance would fall to about 3. Note that these numbers simply show the total issuance over the total stake or the average yield paid across all validators, but individual validators will achieve different yields based on their performance, as well as other uncontrollable factors.
The ETH issuance illustrated assumes the Beacon Chain is running optimally, validators are performing their duties perfectly, and all validators have a 32 ETH effective balance. Actual issuance will be lower than illustrated as validators do not behave optimally in practice, but data since the launch of the Beacon Chain has indicated that live validator performance is only a few percentage points below optimal.
A substantial portion of validator rewards are derived from attestations, as every validator will make one attestation during each epoch. Attesting too slowly or incorrectly will result in rewards turning into penalties. In addition, the rewards realized by individual validators will further vary as incremental rewards accrue to the randomly selected block proposers and sync committee participants.
In short, this essentially means that validators with a balance below 32 ETH due to penalties for going offline or being slashed for malicious behavior will have their rewards scaled downward versus validators with a 32 ETH balance. Bellatrix will occur on September 6th, and it gives the Beacon Chain logic to be aware that The Merge is coming, while Paris is the actual Merge itself, where the consensus mechanism is switched in real-time.
The Merge will be triggered when the chain reaches a pre-specified terminal total difficulty TTD level, which is a measure of the total cumulative mining power used to build the proof-of-work chain since genesis. Once a proof-of-work block is added to the chain that crosses the preset TTD threshold, no additional proof-of-work blocks will be produced from this point on. Upon hitting TTD, Ethereum EL clients will toggle off mining and cease their gossip-based communication about blocks, with similar responsibilities now being assumed by CL clients.
The two distinct blockchains that were historically running in parallel will have merged into the Beacon Chain, and new blocks will be proposed and extend the Beacon Chain as usual, but with transaction data that was historically included in proof-of-work blocks. Annotations by GSR. We would recommend this post to those interested in a very precise series of events. One notable challenge associated with The Merge is the sheer number of pairwise combinations between consensus and execution layer clients.
Unlike Bitcoin, which has a single reference implementation in Bitcoin Core, post-Merge Ethereum nodes must run an execution client and a consensus client paired together, with the implementations chosen at the discretion of the node operator. Further, Ethereum has multiple distinct client teams independently developing and implementing the EL and CL protocol specifications. Ignoring client implementations with less than one percent of the user base, there are four EL client implementations and four CL client implementations, according to clientdiversity.
This creates 16 distinct pairs of EL and CL client implementations that all need to interoperate seamlessly. The inactivity leak further punishes correlated failures that impede finality. Building the Beacon Chain specification and battle-testing the client implementations is no small feat, and Ethereum developers have run through a large number of tests aiming to simulate The Merge in a controlled environment. Around 20 shadow forks, which are simply copies of the state of a network used for testing purposes, have been executed across mainnet and Goerli, allowing developers to trial The Merge through a large suite of live network conditions.
Shadow forks work by coordinating a small number of nodes to fork off the canonical chain by pulling their Merge implementation timeline ahead of the live network. Based on the Ethereum hashrate mining currently, The Merge is likely to occur on September 15th, but the expected date can be monitored in real-time here.
While The Merge is expected to be minimally disruptive to most participants of the Ethereum network, there are a few important changes to be aware of. Importantly and as discussed above, the upgrade will now require full nodes to run an EL client and a CL client.
In contrast, transactions and blocks could previously be received, validated, and propagated with a single EL client. Moving forward, both EL and CL clients will have a unique peer-to-peer p2p network. The CL client will gossip blocks, attestations, and slashings while the EL client will continue to gossip transactions, handle execution, and maintain state.
The two clients will leverage the Engine API to communicate with each other, forming a full post-Merge Ethereum node in tandem. In addition, Ethereum applications are not expected to be materially affected by The Merge, but certain changes like a marginally decreased block time and the removal of proof-of-work-related opcodes like difficulty could impact a subset of smart contracts.
Moreover, net issuance may be deflationary, as gas fees burned under EIP may more than offset the new, lower issuance schedule. As a result, all new ETH issuance will be illiquid as it will accrue to validator accounts where it cannot be withdrawn or transferred until after the next upgrade. And even then, there are validator exit limits in place to prevent a simultaneous run to the exits after staked ETH becomes liquid.
All told, a successful Merge will result in many changes and positive benefits. The Surge Another major upgrade is The Surge, which refers to the set of upgrades commonly referred to as sharding that are designed to help Ethereum scale transaction throughput.
For traditional databases, sharding is the process of partitioning a database horizontally to spread the load, and in earlier Ethereum roadmaps, it aimed to scale throughput on the base layer by splitting execution into 64 shard chains to support parallel computation, with each shard chain having its own validator set and state. However, as layer two L2 scaling technologies developed, Vitalik Buterin proposed a rollup-centric scaling roadmap for Ethereum in October , simplifying the long-term Ethereum roadmap by deemphasizing scaling at the base layer and prioritizing data sharding over execution sharding.
The updated roadmap aims to achieve network scalability by moving virtually all computation i. Simply put, computation is already very cheap on L2s, and the majority of L2 transaction fees today are driven by the cost of posting the computed data back to mainnet.
Currently, rollups post their state roots back to Ethereum using calldata for storage. While a full primer on rollups is beyond the scope of this piece, rollups do not need permanent data storage but only require that the data is temporarily available for a short period of time.
More precisely, they require data availability guarantees ensuring that data was made publicly available and not withheld or censored by a malicious actor. Hence, despite calldata being the cheapest data solution available today, it is not optimized for rollups or scalable enough for their data availability needs. However, instituting full Danksharding is complex, leading the community to support an intermediate upgrade offering a subset of the DS features known as Proto-Danksharding PDS; EIP to achieve meaningful scaling benefits more quickly.
This new transaction type will materially increase the amount of data available for rollups to interpret since each blob, which is roughly kB, is larger than an entire Ethereum block on average. Blobs are purely introduced for data availability purposes, and the EVM cannot access blob data, but it can only prove its existence.
The full blob content is propagated separately alongside a block as a sidecar. This segregated fee market should yield efficiencies by separating the cost of data availability from the cost of execution, allowing the individual components to be priced independently based on their respective demand i. Further, data blobs are expected to be pruned from nodes after a month or so, making them a great data solution for rollups without overburdening node operators with extreme storage requirements.
Despite PDS making progress in the DS roadmap, the name is perhaps a misnomer given each validator is still required to download every data blob to verify that they are indeed available, and actual data sharding will not occur until the introduction of DS. The PDS proposal is simply a step in the direction of the future DS implementation, and expectations are for PDS to be fully compatible with DS while increasing the current throughput of rollups by an order of magnitude.
Rollups will be required to adjust to this new transaction type, but the forward compatibility will ensure another adjustment is not required once DS is ready to be implemented. While the implementation details of DS are not set in stone, the general idea is simple to understand: DS distributes the job of checking data availability amongst validators.
To do so, DS uses a process known as data availability sampling, where it encodes shard data using erasure coding, extending the dataset in a way that mathematically guarantees the availability of the full data set as long as some fixed threshold of samples is available6. DS splits up data into blobs or shards, and every validator will be required to attest to the availability of their assigned shards of data once per epoch, splitting the load amongst them.
As long as the majority of validators honestly attest to their data being available, there will be a sufficient number of samples available, and the original data can be reconstructed. In the longer run, private random sampling is expected to allow an individual to guarantee data availability on their own without any validator trust assumptions, but this is challenging to implement and is not expected to be included initially.
DS further plans to increase the number of target shards to , with a maximum of shards per block, materially increasing the target blob storage per block from 1 MB to 16 MBs. This increase in validator requirements would be detrimental to the diversity of the network, so an important upgrade from The Splurge, known as Proposer-Builder Separation PBS , will need to be completed first.
However, many still misconstrue sharding as scaling Ethereum execution at the base layer, which is no longer the medium-term objective. The sharding roadmap prioritizes making data availability cheaper and leaning into the computational strengths of rollups to achieve scalability on L2. Many have highlighted DS as the upgrade that could invert the scalability trilemma as a highly decentralized validator set will allow for data to be sharded into smaller pieces while statistically preserving data availability guarantees, improving scalability without sacrificing security.
And in the current design, Ethereum nodes must store the state to validate blocks and ensure that the network transitions between states correctly. This growing storage requirement increases the hardware specifications to run a full node over time, which could have a centralizing effect on the validator set. The permanence of state also creates a unique scenario as a user pays a one-time gas fee to send a transaction in exchange for an ongoing cost to the network via permanent node storage requirements.
The Verge aims to alleviate the burden of state on the network by replacing the current Merkle-Patricia state tree with a Verkle Tree, a newer data structure first described in However, Verkle proofs are much more efficient in proof size compared to Merkle proofs. Unlike a Merkle-Patricia Tree, which requires more hashes as the tree widens with more children, Verkle Trees use vector commitments that allow the tree width to expand without expanding the witness size.
The transition to Verkle Trees will allow stateless clients to proliferate as smaller witnesses enable direct block inclusion. Stateless clients will enable fresh nodes to immediately validate blocks without ever syncing the state as they would simply request the required block information and proof from a peer.
Enabling nodes to validate the network primarily with RAM will increase validator decentralization. The Purge The Purge refers to a series of upgrades aimed at simplifying the protocol by reducing historical data storage and technical debt. Most prominently, it aims to introduce history expiration EIP which could potentially come in the months following The Merge.
Importantly, once a node is fully synced to the head of the chain, validators do not require historical data to verify incremental blocks. Hence, historical data is only used at the protocol level when an explicit request is made via JSON-RPC or when a peer attempts to sync the chain.
After EIP, new nodes will leverage a different syncing mechanism, like checkpoint sync, which will sync the chain from the most recently finalized checkpoint block instead of the genesis block. The deletion of history data is primarily a concern for individual Ethereum-based applications that require historical transaction data to show information about past user behaviors. History storage is viewed as a problem that would be best handled outside of the scope of the Ethereum protocol moving forward, but clients would still offer the ability to import this data from external sources.
Removing history data from Ethereum would significantly reduce the hard disk requirements for node operators, and it would allow for client simplification by removing the need for code that processes different versions of historical blocks. In addition to history expiration, The Purge includes state expiry, which prunes state that has not been touched in some defined amount of time, such as one year into a distinct tree structure, removed from the Ethereum protocol.
State expiry is the furthest out of all the upgrades outlined in the roadmap and only becomes feasible after the introduction of Verkle Trees. The letter S in the wordplay on Merge refers to Sharding: the parallel existence of 64 blockchains or shards. This divides the huge data load that Ethereum will face and already faces. All this data can of course not be crammed onto a single blockchain, because no one would be able to run an Ethereum node anymore. So to avoid throwing decentralization out of the window, Ethereum has to divide and conquer.
Of all 64 shards, the Beacon Chain — as the name suggests — will be the one that other shards rely on. The Beacon chain is often compared to the highway and the other shards to side roads. But this comparison misses the point that the shards will most likely not process transactions. Instead, they are used to store transaction data. This is where so-called Danksharding comes in. The Ethereum Roadmap Phase 3 — Danksharding A few technical approaches have been suggested to take data load away from the Beacon chain.
The details still have to be fleshed out. Rollups, like sidechains, take the pressure off Ethereum by performing transactions on a separate, layer 2 chain. Merkle trees are a tool for ensuring reliable encryption by turning blocks of information into long strings of code. By adding all transactions in a block and creating a fingerprint of the entire set, it allows you to verify whether a transaction is included in the block.
Verkle trees, in other words, make it possible to store a large amount of data by showing a short proof of any piece of that data. So they make the process of proof efficient. In this way, Verkle trees are a powerful upgrade to Merkle proofs. They will allow users to be network validators without having to store large amounts of data on their hard drives. Keep it decentralized! Again, this will alleviate the data storage requirements for users who want to be validators but who do not have hundreds of Terabytes available.
After the Purge, Ethereum clients will discard data older than a year. This should minimize chain clogging and allow many more transactions to be processed. Buterin expects Ethereum to process , transactions per second after the implementation of The Purge. Ethereum devs will still have to figure out where all those old blockchain data will go.
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On the note of staked ETH, The Merge will not release all staked ETH at once as it will happen after the Shanghai update, which is estimated to be introduced about six months after transitioning to PoS. Once the Shanghai update is implemented, all validators will be incentivized to withdraw their staked ETH below the 32ETH threshold as those will not earn additional yield and will be otherwise locked for no reason.
It all comes down to the withdrawal mechanism allowing only six validators to exit per epoch every 6. This rate limit prevents a mass exodus of funds from flooding the market. Also, such a mechanism prevents a potential attacker from committing an offence and exiting his stake in the same epoch before having it slashed as a penalty.
In short, it is unknown who will produce the next block, so a potential hacker cannot specify which validator to attack with malicious intent. It is crucial to point out that The Surge sets up the scaffolding and most of the logic needed to implement sharding but does not introduce a sharding mechanism per se. After Sharding is shipped, Layer 1 of Ethereum will only have to interpret the data, not compute it. But what is the sharding mechanism, you might ask?
In short, data stays on-chain while the computation and storage go off-chain, increasing the bandwidth of Rollup up to, from mathematical POV, , transactions per second. Additionally, we might think of sharding as the process of splitting a database horizontally to spread the load by distributing the burden of handling the large amount of data needed by rollups over the entire network.
It does not only increase the bandwidth of transactions but also helps decentralize the whole blockchain. Along with the introduction of Availability Sampling, which is a part of the Sharding upgrade, even minor Ethereum users will be able to become guardians of the Ethereum City by becoming Validators. Such price dynamic will shift the growth of the Ethereum ecosystem from building on Layer 1 to building on Layer 2 projects like Arbitrum, Optimism, StarkNet or zkSync, which does not have to be seen as something negative.
It would rather resemble the restructuring of an ecosystem similar to the situation when grown-up children are taking more responsibilities from a parent. To clarify the nomenclature used, we need to understand who is, or will be, a Builder and who is a Proposer in the Ethereum blockchain. Block Proposer serves the same role as a Miner on the PoW chain. Being a Block Proposer allows you to pick and choose which transactions to include in the block by specifying transactions that are the most profitable to you, taking the advantage of Miner Extractable Value MEV mechanism.
It all comes down to the issue of packing as much as possible in the most profitable way. Data is robust, while block storage is limited. Builders are a new class of actors who are given the list of transactions, from the Block Proposers, in the form of a crList. The list states which transactions builders MUST include limiting their capability of block manipulation. Such a mechanism will nullify one of the most negative aspects of MEV, which is the god-like power to censor and exclude users' transactions.
PBS aims to maximize the advantages and profitability of MEV to the Ethereum ecosystem, at the same time neutralizing its hindrances for users. It's a win-win scenario. The Verge — Changing Trees The data structure is often presented and referred to as a Tree of a particular kind. One of the most prominent examples of data trees are Merkle Trees and Verkle Trees. The difference between the two can be described in the following way — In a Merkle Tree, a parent node is the hash of its children.
In a Verkle Tree, a parent node is the Vector Commitment of its children. Merkle Tree containing all Sister-Nodes to provide a proof. Verkle Trees, on the other hand, do not need to provide all Sister-Nodes. Instead, you have to provide the Path from the given node to the Root-Note along the Parent-Nodes, with a small proof validating the Path. Verkle Tree containing a single Node along the Path. The advantage of using Verkle Trees is in producing lighter proof sizes by about times compared to Merkle Trees, and by times smaller compared to Merkle Patricia Trees Ethereum uses today.
The switch to Verkle trees will be, without a doubt, a great cryptographic challenge as those have been introduced by John Kuszmaul in It is not a long time to learn how to use the full potential of a given technology. Nonetheless, if everything goes well, it will be a tremendous upgrade to the efficiency of the Ethereum blockchain. The Verge is also bringing lots of good things for decentralization with Stateless Clients allowing running Light Nodes on Ethereum.
A light node contains only the chain of block headers without the execution of any transactions or associated states of the chain it validates. When a node comes online, it will be fully stateless since it will hold zero information regarding the state of the chain. You can think of a light node as an individual verifying the titles of top-secret files without the need to know and process the contents. To proceed, we have to clarify who or what an Ethereum client is.
An Ethereum client is the software needed to allow Ethereum nodes to read blocks on the Ethereum blockchain and Ethereum-based smart contracts. What will EIP introduce? It will abolish the need for clients to store and download historical data — older than one year, as stated in the EIP description.
Each beacon committee makes a single attestation per epoch before being disbanded and the process restarting anew in the next epoch. A small set of validators are also chosen at random to join sync committees which are different from the aforementioned beacon committees , which pay additional rewards to validators and help light clients sync up and determine the head of the chain.
Sync committees are particularly lucrative as participating validators receive a reward for each slot, and the selection lasts for epochs, or 8, slots before a new committee is selected. The Beacon Chain employs a proof-of-stake consensus protocol named Gasper, which the Ethereum team designed internally. By doing so, Gasper combines the low overhead benefits that allow for a high number of participants to support decentralization seen in longest chain systems with the finality benefits of a pBFT-inspired system.
Alternative approaches favoring safety like Tendermint will not allow for forks safety , but they cease block production and halt when finality thresholds are not met. Gasper uses a system of checkpoint attestations of prior blocks, which requires a supermajority of attestation votes and increases the cost of reorganizing the blockchain prior to such checkpoints. Every epoch has one checkpoint, and that checkpoint is a hash identifying the latest block at the start of that epoch3.
Validators attest to their view of two checkpoints every epoch, and the validator also runs the LMD GHOST fork-choice rule to attest to their view of the chain head block. The two checkpoint blocks are known as a source and a target, where the source is the earlier of the two checkpoint blocks. If more than two-thirds of the total validator stake vote to link two adjacent checkpoint blocks, then there is a supermajority link between these checkpoints, and they both achieve an increased level of security.
Reversing a finalized block would require malicious action by two-thirds of the total validator stake, and resultantly, the protocol guarantees they would be slashed at least one-third of the total network stake4. This is referred to as economic finality — while a finalized Beacon Chain block can be reversed at a later date, unlike a protocol that achieves absolute finality such as Tendermint, it is impossible to do so without having a prohibitively large amount of stake slashed.
Note that the checkpoint block illustrated in the graphic represents the source checkpoint. Additionally, proof-of-stake has an asymmetric cost advantage that should disincentivize chain reorgs even more so than proof-of-work. The cost to a miner of attempting a chain reorganization and failing under proof-of-work is the electricity cost of their hashrate and the opportunity cost of coins that could have been mined on the canonical chain.
The proof-of-stake reorganization equivalent requires a malicious validator to front as much as two-thirds of the total Ethereum stake, understanding that they will be slashed at least one-third of the total network stake after reorganizing a finalized block. Whether the impediment is from validators being offline due to a client issue or a fork caused by a consensus disagreement, the inactivity leak is designed to penalize validators that impede finality by failing to attest to the chain, and it will eventually allow for the chain s to finalize as the impeding party accrues quadratically growing penalties until a supermajority is reclaimed.
Rewards and penalties are aggregated across slots and paid to validators every epoch. Rewards issued for validating the chain are dynamic and depend on the total amount of ETH staked in the network. Specifically, the total ETH issued to validators in aggregate is proportional to the square root of the number of validators. This mechanism incentivizes validators with larger issuance rewards when there are fewer validators participating in consensus, and it decreases the incentive as the validator set grows and attracting additional validators becomes less essential.
However, the average yield from issuance would fall to about 3. Note that these numbers simply show the total issuance over the total stake or the average yield paid across all validators, but individual validators will achieve different yields based on their performance, as well as other uncontrollable factors. The ETH issuance illustrated assumes the Beacon Chain is running optimally, validators are performing their duties perfectly, and all validators have a 32 ETH effective balance.
Actual issuance will be lower than illustrated as validators do not behave optimally in practice, but data since the launch of the Beacon Chain has indicated that live validator performance is only a few percentage points below optimal. A substantial portion of validator rewards are derived from attestations, as every validator will make one attestation during each epoch.
Attesting too slowly or incorrectly will result in rewards turning into penalties. In addition, the rewards realized by individual validators will further vary as incremental rewards accrue to the randomly selected block proposers and sync committee participants. In short, this essentially means that validators with a balance below 32 ETH due to penalties for going offline or being slashed for malicious behavior will have their rewards scaled downward versus validators with a 32 ETH balance.
Bellatrix will occur on September 6th, and it gives the Beacon Chain logic to be aware that The Merge is coming, while Paris is the actual Merge itself, where the consensus mechanism is switched in real-time. The Merge will be triggered when the chain reaches a pre-specified terminal total difficulty TTD level, which is a measure of the total cumulative mining power used to build the proof-of-work chain since genesis.
Once a proof-of-work block is added to the chain that crosses the preset TTD threshold, no additional proof-of-work blocks will be produced from this point on. Upon hitting TTD, Ethereum EL clients will toggle off mining and cease their gossip-based communication about blocks, with similar responsibilities now being assumed by CL clients. The two distinct blockchains that were historically running in parallel will have merged into the Beacon Chain, and new blocks will be proposed and extend the Beacon Chain as usual, but with transaction data that was historically included in proof-of-work blocks.
Annotations by GSR. We would recommend this post to those interested in a very precise series of events. One notable challenge associated with The Merge is the sheer number of pairwise combinations between consensus and execution layer clients. Unlike Bitcoin, which has a single reference implementation in Bitcoin Core, post-Merge Ethereum nodes must run an execution client and a consensus client paired together, with the implementations chosen at the discretion of the node operator.
Further, Ethereum has multiple distinct client teams independently developing and implementing the EL and CL protocol specifications. Ignoring client implementations with less than one percent of the user base, there are four EL client implementations and four CL client implementations, according to clientdiversity.
This creates 16 distinct pairs of EL and CL client implementations that all need to interoperate seamlessly. The inactivity leak further punishes correlated failures that impede finality. Building the Beacon Chain specification and battle-testing the client implementations is no small feat, and Ethereum developers have run through a large number of tests aiming to simulate The Merge in a controlled environment.
Around 20 shadow forks, which are simply copies of the state of a network used for testing purposes, have been executed across mainnet and Goerli, allowing developers to trial The Merge through a large suite of live network conditions. Shadow forks work by coordinating a small number of nodes to fork off the canonical chain by pulling their Merge implementation timeline ahead of the live network. Based on the Ethereum hashrate mining currently, The Merge is likely to occur on September 15th, but the expected date can be monitored in real-time here.
While The Merge is expected to be minimally disruptive to most participants of the Ethereum network, there are a few important changes to be aware of. Importantly and as discussed above, the upgrade will now require full nodes to run an EL client and a CL client. In contrast, transactions and blocks could previously be received, validated, and propagated with a single EL client. Moving forward, both EL and CL clients will have a unique peer-to-peer p2p network.
The CL client will gossip blocks, attestations, and slashings while the EL client will continue to gossip transactions, handle execution, and maintain state. The two clients will leverage the Engine API to communicate with each other, forming a full post-Merge Ethereum node in tandem.
In addition, Ethereum applications are not expected to be materially affected by The Merge, but certain changes like a marginally decreased block time and the removal of proof-of-work-related opcodes like difficulty could impact a subset of smart contracts. Moreover, net issuance may be deflationary, as gas fees burned under EIP may more than offset the new, lower issuance schedule. As a result, all new ETH issuance will be illiquid as it will accrue to validator accounts where it cannot be withdrawn or transferred until after the next upgrade.
And even then, there are validator exit limits in place to prevent a simultaneous run to the exits after staked ETH becomes liquid. All told, a successful Merge will result in many changes and positive benefits. The Surge Another major upgrade is The Surge, which refers to the set of upgrades commonly referred to as sharding that are designed to help Ethereum scale transaction throughput.
For traditional databases, sharding is the process of partitioning a database horizontally to spread the load, and in earlier Ethereum roadmaps, it aimed to scale throughput on the base layer by splitting execution into 64 shard chains to support parallel computation, with each shard chain having its own validator set and state. However, as layer two L2 scaling technologies developed, Vitalik Buterin proposed a rollup-centric scaling roadmap for Ethereum in October , simplifying the long-term Ethereum roadmap by deemphasizing scaling at the base layer and prioritizing data sharding over execution sharding.
The updated roadmap aims to achieve network scalability by moving virtually all computation i. Simply put, computation is already very cheap on L2s, and the majority of L2 transaction fees today are driven by the cost of posting the computed data back to mainnet. Currently, rollups post their state roots back to Ethereum using calldata for storage.
While a full primer on rollups is beyond the scope of this piece, rollups do not need permanent data storage but only require that the data is temporarily available for a short period of time. More precisely, they require data availability guarantees ensuring that data was made publicly available and not withheld or censored by a malicious actor. Hence, despite calldata being the cheapest data solution available today, it is not optimized for rollups or scalable enough for their data availability needs.
However, instituting full Danksharding is complex, leading the community to support an intermediate upgrade offering a subset of the DS features known as Proto-Danksharding PDS; EIP to achieve meaningful scaling benefits more quickly. This new transaction type will materially increase the amount of data available for rollups to interpret since each blob, which is roughly kB, is larger than an entire Ethereum block on average. Blobs are purely introduced for data availability purposes, and the EVM cannot access blob data, but it can only prove its existence.
The full blob content is propagated separately alongside a block as a sidecar. This segregated fee market should yield efficiencies by separating the cost of data availability from the cost of execution, allowing the individual components to be priced independently based on their respective demand i.
Further, data blobs are expected to be pruned from nodes after a month or so, making them a great data solution for rollups without overburdening node operators with extreme storage requirements. Despite PDS making progress in the DS roadmap, the name is perhaps a misnomer given each validator is still required to download every data blob to verify that they are indeed available, and actual data sharding will not occur until the introduction of DS.
The PDS proposal is simply a step in the direction of the future DS implementation, and expectations are for PDS to be fully compatible with DS while increasing the current throughput of rollups by an order of magnitude. Rollups will be required to adjust to this new transaction type, but the forward compatibility will ensure another adjustment is not required once DS is ready to be implemented.
While the implementation details of DS are not set in stone, the general idea is simple to understand: DS distributes the job of checking data availability amongst validators. To do so, DS uses a process known as data availability sampling, where it encodes shard data using erasure coding, extending the dataset in a way that mathematically guarantees the availability of the full data set as long as some fixed threshold of samples is available6.
DS splits up data into blobs or shards, and every validator will be required to attest to the availability of their assigned shards of data once per epoch, splitting the load amongst them. As long as the majority of validators honestly attest to their data being available, there will be a sufficient number of samples available, and the original data can be reconstructed.
In the longer run, private random sampling is expected to allow an individual to guarantee data availability on their own without any validator trust assumptions, but this is challenging to implement and is not expected to be included initially. DS further plans to increase the number of target shards to , with a maximum of shards per block, materially increasing the target blob storage per block from 1 MB to 16 MBs.
This increase in validator requirements would be detrimental to the diversity of the network, so an important upgrade from The Splurge, known as Proposer-Builder Separation PBS , will need to be completed first. However, many still misconstrue sharding as scaling Ethereum execution at the base layer, which is no longer the medium-term objective.
The sharding roadmap prioritizes making data availability cheaper and leaning into the computational strengths of rollups to achieve scalability on L2. Many have highlighted DS as the upgrade that could invert the scalability trilemma as a highly decentralized validator set will allow for data to be sharded into smaller pieces while statistically preserving data availability guarantees, improving scalability without sacrificing security.
And in the current design, Ethereum nodes must store the state to validate blocks and ensure that the network transitions between states correctly. This growing storage requirement increases the hardware specifications to run a full node over time, which could have a centralizing effect on the validator set. The permanence of state also creates a unique scenario as a user pays a one-time gas fee to send a transaction in exchange for an ongoing cost to the network via permanent node storage requirements.
The Verge aims to alleviate the burden of state on the network by replacing the current Merkle-Patricia state tree with a Verkle Tree, a newer data structure first described in However, Verkle proofs are much more efficient in proof size compared to Merkle proofs. Unlike a Merkle-Patricia Tree, which requires more hashes as the tree widens with more children, Verkle Trees use vector commitments that allow the tree width to expand without expanding the witness size. The transition to Verkle Trees will allow stateless clients to proliferate as smaller witnesses enable direct block inclusion.
Stateless clients will enable fresh nodes to immediately validate blocks without ever syncing the state as they would simply request the required block information and proof from a peer.
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A Better Mental Model for Rollups, Plasma, and Validating BridgesOther materials on the topic
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