Plasma ethereum roadmap

The eth2 roadmap offers scalability, and the earlier phases of eth2 are approaching quickly, but base-layer scalability for applications is only coming as the last major phase of eth2, which is still years away. These facts taken together lead to a particular conclusion: the Ethereum ecosystem is likely to be all-in on rollups plus some plasma and channels as a scaling strategy for the near and mid-term future.

If we start from this premise, we can see that it leads to some particular conclusions about what the priorities of Ethereum core development and ecosystem development should be, conclusions that are in some cases different from the current path.

But what are some of these conclusions? The Short Term: Advancing Eth1 for Rollups In the short term, one major outcome of this is that Ethereum base-layer scaling would primarily be focused on scaling how much data blocks can hold, and not efficiency of on-chain computation or IO operations.

Eth1 clients could be repurposed as optimistic rollup clients. Optimism , then existing code could be repurposed to run these full nodes. Note in particular that this implies that projects like TurboGeth are still very important, except it would be high-throughput rollup clients, rather than base-layer eth1 clients, that would benefit the most from them.

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. The main goal of scalability is to increase transaction speed faster finality , and transaction throughput high transactions per second , without sacrificing decentralization or security more on the Ethereum vision.

On the layer 1 Ethereum blockchain, high demand leads to slower transactions and nonviable gas prices. Increasing the network capacity in terms of speed and throughput is fundamental to the meaningful and mass adoption of Ethereum. While speed and throughput are important, it is essential that scaling solutions enabling these goals remain decentralized and secure. Keeping the barrier to entry low for node operators is critical in preventing a progression towards centralized and insecure computing power.

Conceptually we first categorize scaling as either on-chain scaling or off-chain scaling. Prerequisites You should have a good understanding of all the foundational topics. Implementing scaling solutions is advanced as the technology is less battle-tested, and continues to be researched and developed. On-Chain scaling This method of scaling requires changes to the Ethereum protocol layer 1 Mainnet.

Sharding is currently the main focus for this method of scaling. Sharding Sharding is the process of splitting a database horizontally to spread the load. Learn more about sharding. Off-chain scaling Off-chain solutions are implemented separately from layer 1 Mainnet - they require no changes to the existing Ethereum protocol.

Some solutions, known as "layer 2" solutions, derive their security directly from layer 1 Ethereum consensus, such as optimistic rollups , zero-knowledge rollups or state channels. Other solutions involve the creation of new chains in various forms that derive their security separately from Mainnet, such as sidechains , validiums , or plasma chains.

These solutions communicate with Mainnet, but derive their security differently to obtain a variety of goals. Layer 2 scaling This category of off-chain solutions derives its security from Mainnet Ethereum. Layer 2 is a collective term for solutions designed to help scale your application by handling transactions off the Ethereum Mainnet layer 1 while taking advantage of the robust decentralized security model of Mainnet.

Transaction speed suffers when the network is busy, making the user experience poor for certain types of dapps. And as the network gets busier, gas prices increase as transaction senders aim to outbid each other. This can make using Ethereum very expensive. Most layer 2 solutions are centered around a server or cluster of servers, each of which may be referred to as a node, validator, operator, sequencer, block producer, or similar term.

Depending on the implementation, these layer 2 nodes may be run by the individuals, businesses or entities that use them, or by a 3rd party operator, or by a large group of individuals similar to Mainnet. Generally speaking, transactions are submitted to these layer 2 nodes instead of being submitted directly to layer 1 Mainnet. For some solutions the layer 2 instance then batches them into groups before anchoring them to layer 1, after which they are secured by layer 1 and cannot be altered.

The details of how this is done vary significantly between different layer 2 technologies and implementations. A specific layer 2 instance may be open and shared by many applications, or may be deployed by one project and dedicated to supporting only their application. Why is layer 2 needed? Increased transactions per second greatly improves user experience, and reduces network congestion on Mainnet Ethereum.

Transactions are rolled up into a single transaction to Mainnet Ethereum, reducing gas fees for users making Ethereum more inclusive and accessible for people everywhere. Any updates to scalability should not be at the expense of decentralization or security — layer 2 builds on top of Ethereum.

Theme bitcoin blockchain stocks something

Hence, new blocks come every 12 seconds unless a selected proposer fails to deliver a block leading to an empty slot, in which case the next block would be expected to arrive 24 seconds after the previous block. Every validator is placed on one beacon committee per epoch, and each beacon committee is randomly assigned to a particular slot and required to attest to their view of the chain head block during their assigned slot.

By dividing validators into beacon committees, the network cuts down on messaging requirements, allowing for individual attestations to be aggregated in parallel and gossiped at the committee level. In fact, each slot has multiple beacon committees of validators, all attesting to the same information in that particular slot, so the number of aggregated attestations per slot will align with the number of committees per slot in an idealized example.

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 These puzzles get harder over time and requires a lot of energy and computing power. This means that a few mining companies control the hashrate of Bitcoin. As of right now, As the cryptographic puzzles become more challenging, it requires more hardware and energy which is also very expensive.

This makes it harder for anyone to mine, which further centralizes to a few mining pools. Why is this bad? The attackers would be able to prevent new transactions from gaining confirmations, allowing them to halt payments between users. An event like this could possibly even legitimize a different blockchain such as Bitcoin Cash. If the block gets appended, you will get a reward proportional to your stake.

If you bet on the wrong block, your stake will be taken away. Proof-of-stake also helps solves some of the problems with proof-of-work. It helps achieve decentralization, energy efficiency, and helps Ethereum scale. There are two version of Casper. These stakers will be rewarded through an annual dividend of ether. So, the more ETH you stake, the larger your dividends will be. In PoS, no matters what happens, you will always win and have nothing to lose.

The only way to lose your stake is if you maliciously validate wrong blocks. Casper secures it further. How Ethereum Scales Casper will pave the way for scaling Ethereum to achieve mainstream adoption. In order to do this, Ethereum needs to handle large volumes of transactions. Otherwise, costs skyrocket and it takes longer for transaction to go through. Ethereum founder Vitalik recently proposed a plan to help scale Ethereum through sharding.

Rather than have transactions run in linear order, sharding allows blocks to happen in parallel. Think of this as the difference between downloading one song from a friend vs using a Torrent to download the same file from thousands of people. Sharding Intro from MongoDB Sharding is also the process of splitting up the chain data, so that every node only has to worry about a small portion of the chain.

This will allow Ethereum to process thousands of transactions per second — all on the same chain. Plasma Similar to Bitcoin, Ethereum has a scaling problem with rising smart contract fees that slow down transaction times, especially during ICOs. Plasma is an update which fixes the scaling issues with Ethereum.

According to Vitalik Buterin , there are four major problems that need to be solved to push Ethereum to the next level: privacy, consensus safety, smart contract safety, and the biggest challenge to solve — scalability. Ethereum is still a nascent technology but there are many promising scaling features that will allow to reach mainstream.

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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. In short, MEV is a measure of profit that a miner or validator can extract from block production beyond the block reward and gas fees by including, excluding, and changing the order of transactions in a block.

While miners are in a prime position to identify and capitalize on such transactions, as they control which transactions are included and in what order, the majority of MEV is extracted by independent third parties called searchers that use sophisticated trading strategies to capture MEV. MEV extraction is a fundamentally different skill set than participating in network consensus, and companies such as Flashbots have been created to illuminate, democratize, and redistribute MEV by serving as a neutral, public, open-source infrastructure for permissionless MEV extraction, allowing independent MEV searchers to communicate their bid and granular transaction order preference to mining pools to execute their ordered bundle of transaction.

Competition between searchers to extract MEV results in much of the gains accruing to the block proposer in a competitive bidding process. PBS, as the name implies, separates block builders from block proposers at the protocol level. The validator that is selected to propose the next block in the chain is known as the block proposer, and they outsource block construction transaction selection and ordering to a dedicated market of block builders.

Under this model, dedicated block builders search for MEV opportunities to build the most profitable block and submit bids to block proposers to propose their block. This eases the job of validators by selling the computationally difficult optimization problem to a more specialized entity and allowing validators to fulfill their responsibilities with materially lower hardware specifications.

Additionally, PBS should redistribute the profit attributable to MEV, as multiple builders compete against each other in an auction, eroding their margins and returning most of the profit to validators. Perhaps ironically, the set-up somewhat resembles the scale economies inherent in proof-of-work.

This results in more centralized block production, but validation is still trustless and should be even more decentralized since block building responsibilities are delegated elsewhere. While the specification details of in-protocol PBS are not fully decided at this point, censorship resistance is an explicitly categorized area of focus on the roadmap. The PBS implementation will include a censorship-resistance list crLists that the proposer publishes to display their view of censored transactions in the mempool.

Another notable upgrade in The Splurge is account abstraction, with the most prominent proposal being EIP This proposal lets users employ smart contract wallets as their primary Ethereum account instead of an externally-owned account EOA , and it does so by leveraging a higher-layer account abstraction approach that avoids any Ethereum protocol changes.

Specifically, EIP creates a separate mempool consisting of a higher-order transaction-like object called a UserOperation. A special set of users known as bundlers would aggregate UserOperations into a transaction that would directly communicate with a particular smart contract, and that transaction would then be included in a block on mainnet.

This improves user experience by atomically batching operations into a single transaction that would otherwise require multiple different transactions to execute on mainnet. Account abstraction would further provide user flexibility to deviate from the ECDSA digital signature algorithm and employ any arbitrary verification logic, such as a quantum-resistant signature scheme.

It also simplifies the use of multisigs and social recovery wallets. Lastly, it introduces a form of gas abstraction where gas fees can be paid in ERC tokens, and applications can subsidize the gas fees of their users. Conclusion In just 15 days, we will likely witness one of the most significant events in blockchain history, as the first and apex smart contract blockchain attempts a nearly impossible feat — to change its consensus mechanism mid-flight.

In just 15 days, the Beacon Chain will merge with Ethereum mainnet, as proof-of-work is switched off and proof-of-stake takes over. Validators will immediately begin proposing and attesting to blocks, as beacon committees are formed and disbanded at every epoch. Validators, following Gasper, will attest to both checkpoints and chain heads, identifying the canonical chain and introducing the notion of economic finality.

And when all is said and done, energy consumption will plummet, finality guarantees will strengthen, ETH issuance will fall, and staking yields will rise, all upon reaching that fateful terminal total difficulty level. Ethereum, however, is equipped with a thoughtful and well-defined roadmap, and its developers have been hard at work perfecting the various upgrades to bring about their many benefits.

Through Danksharding, with its data blobs and data availability sampling, The Surge will make data availability cheaper and distribute the job of checking data availability amongst nodes, providing material scalability benefits on L2. The Purge will introduce history expiration and state expiry, archiving history data, pruning untouched state, and generally simplifying the protocol.

Footnotes: Notably, validators are attesting to their view of the chain head block for LMD GHOST during their slot, which is generally but not necessarily the block proposed in their slot. However, if a block proposer does not deliver a block in their assigned slot, the validators in that slot would attest to their view of the chain head block, which would likely be the same chain head that validators in the previous slot attested to. In aggregate, validators are delivering one attestation per epoch, but that attestation includes three items: 1 a vote on the source checkpoint, 2 a vote on the target checkpoint, and 3 a vote for the chain head block.

Notably, the chain head vote uniquely determines the source and target vote, so strictly speaking, voting on all three is redundant and unnecessary, but it simplifies processing. Bitcoin and Ethereum today use a rule that selects the longest chain, or more precisely, the chain with the most cumulative chainwork.

Gasper, however, follows the chain containing the justified checkpoint that has the greatest block height without ever reverting a finalized block. From here, it essentially counts the accumulated votes from validators for blocks and their descendent blocks the economically heaviest chain. Checkpoints are known as epoch boundary blocks in other literature, which may help with intuition.

Checkpoints are identified by their block root hash and an epoch number. A block can theoretically serve as the checkpoint for multiple epochs if the slots throughout remain empty. Since checkpoint finalization requires a two-thirds supermajority, the finalization of two competing checkpoints would require attestations from at least four-thirds of the total stake weight, guaranteeing at least one-third of the total stake attested to two different checkpoints for the same epoch.

Imagine an attacker has two-thirds of the total network stake, and honest validators possess the other one-third. Assuming honest validators all attest to the same checkpoint, the attacker could finalize this checkpoint by attesting with half of their stake, or one-third of the total network stake equivalently.

The attacker could then unilaterally finalize a competing checkpoint by attesting to it with the entirety of their two-thirds stake, but as guaranteed by the first sentence in this footnote, this would result in them having one-third of the total network stake slashed as this would require them to maliciously reuse one-third of the total network stake that they already used to attest to the first checkpoint. Despite this attack requiring two-thirds of the stake to conduct, only half of the stake was required to attest to competing checkpoints, and this is the only provably malicious act that the protocol can detect, so the one-third is all that can be slashed.

It could easily be argued that this attack should warrant the malicious actor being slashed the full two-thirds, but this is not detectable in protocol and would require social slashing through a user-activated soft fork. It may be possible to revert a finalized block with less than two-thirds stake in the event that honest validators are partitioned on their view of the canonical chain, but regardless, any attacker is always guaranteed to be slashed one-third of the total network stake under all circumstances which seems to be a sufficiently large distinctive.

Notably though, block times will be a constant 12 seconds if a block is proposed in each slot. Therefore they have to make a deposit of exactly 32 Ether, for example. When validators deposit into the smart contract, they put it on the beacon chain. So maybe they become active validators and will take part in the proof-of-stake protocol.

The beacon chain will randomly select validators for block proposal and votings. This random sampling in the beacon chain is important. As a result, it stops validators colluding and influencing the system. Learn everything about Beacon Chain. Aggregate Signatures If each vote was a transaction, the blockchain would have to process all the votes step by step within a tight time period.

This puts a limit on the number of validators that can take part. The more validators that can participate the better because it improves security. Aggregate signatures work like a petition. So the petition is sent to each validator, who applies their signature in support. To reduce the load on the main chain these petitions are sent off-chain and only fully built-in the blockchain when the petition has enough support.

Learn all about Ethereum Validator. Sharding Sharding is also part of Ethereum 2. It can realize the performance gains necessary to scale. So every PC that runs on the Ethereum blockchain has to process the transactions in a special order. Despite the fact that the network runs on thousands of PCs, different transactions cannot be processed at the same time. For example, the current Ethereum blockchain is one big single chain of blocks that have to process all transactions step by step.

Sharding is like adding new chains to process more transactions. So each shard is a separate blockchain with its own state and transaction history. But all shards also share the same proof-of-stake consensus with the beacon chain. The registered validators on the beacon chain will then become a global pool of validators.

Thus, they validate blocks on the beacon chain and the shards. But this is just a simple explanation, learn everything about Sharding in detail eWASM Smart-contracts are one of the most interesting parts of Ethereum. With them, you can create great DApps and even more. As a result, every node executes this code. So the faster the EVM can execute the code the better. But this leads to a lot of problems. Thus, this change will make a huge difference in how many transactions can be processed and added to a block.

Therefore, eWASM can increase transaction throughput. As a result, the network will also be more secure, supports more languages and can be portable. Learn everything about eWASM. What is Ethereum Serenity?