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I would like to share our thoughts on moving native token between shards, which are close to the solutions 2 and 5 with the following features:. A BP node of shard j is a light-client of shard i and full node of the root chain similar to beacon chain in ETH2. The Merkle root hashes of cross-shard receipts from all shards are included in the root chain in a deterministic order.
A shard block contains a hash pointer to root block and a cursor :. A user generates a cross-shard transaction from shard i to shard j, and the tx is included in shard i block A. The receipts of all txs of the block are generated and its Merkle root is included in a future root block. At target shard j, upon observing a new root block and creating a new shard block, the BP of shard j create a pre-block unprocessed receipt queue by electing to include the root block or not in the shard block and :.
When creating a shard block, the consensus forces that a valid block must process the receipts in the pre-block unprocessed receipt queue until the queue is empty or a pre-set cross-shard transaction gas limit is exhausted. The pseudo-code looks like:. According to A2 and A3, as long as the receipt queue is deterministically ordered, the delivery is also ordered.
To ensure guaranteed delivery, i. The generating of the receipt at source shard and the processing of the receipt at target shard is a partial order. Moving ETH between shards: the problem statement Sharding.
At EE internal state level: In the top-level state: For transfers within a shard, there are no challenges: transfers within a shard purely affect the internal accounting of an EE instance on some shard, they do not affect the total balance. Solutions 1 Every shard crosslink publishes to the beacon chain all cross-shard transfers that it is making. An even simpler meta-execution environment for ETH.
A meta-execution environment for cross-shard ETH transfers. Can you describe some of these abuses in particular? I would like to share our thoughts on moving native token between shards, which are close to the solutions 2 and 5 with the following features: Guaranteed and ordered delivery via incentives : A cross-shard receipt will be incentivized to be eventually processed at destination shard.
DoS attack prevention : Even the attacks may send lots of transactions to one shard from other shards, the system would continue to work. Happen-before guarantee : A cross-shard receipt will be always processed at the destination shard after the original token was spent from the source shard. Assumptions: A1. A shard block contains a hash pointer to root block and a cursor : The root block hash pointer tells which root block the BP of the shard block observed and included.
According to A1, the BP could fully recover all receipts from shards by the Merkle root hashes of the blocks of root chain since the genesis root block. By ordering the receipts according to their position in the Merkle root and the position in the root chain, we can obtain a deterministic receipt queue, which will be processed by the shard in sequence. At target shard j, upon observing a new root block and creating a new shard block, the BP of shard j create a pre-block unprocessed receipt queue by electing to include the root block or not in the shard block and : If a root block is not included, the pre-block unprocessed receipt queue of the new block equals to the post-block unprocessed receipt queue of the previous block If a root block is included, the pre-block unprocessed receipt queue of the block is constructed by appending all receipts included to the post-block unprocessed receipt queue of the previous block.
Again, the construction can be on-demand and asynchronously according to A1. In the case tx fee is small, we could further incentivize the BP as follows: if a BP includes a new root block, it will collect a full block reward rather than a partial block reward. The sharding model we described so far is not a very useful, because if individual shards cannot communicate with each other, they are no better than multiple independent blockchains.
If one wishes to transfer money from one account to another within the same shard, the transaction can be processed entirely by the validators in that shard. There are two families of approaches to cross-shard transactions:. Note that communication between chains is useful outside of sharded blockchains too.
Interoperability between chains is a complex problem that many projects are trying to solve. In a sharded blockchain, however, all the shard chains are the same, while in the global blockchains ecosystem there are lots of different blockchains, with different target use cases, decentralization and privacy guarantees.
Building a system in which a set of chains have different properties but use sufficiently similar consensus and block structure and have a common beacon chain could enable an ecosystem of heterogeneous blockchains that have a. Such system is unlikely to feature validator rotation, so some extra measures need to be taken to ensure security.
In this section we will review what adversarial behavior can malicious validators exercise if they manage to corrupt a shard. We will review classic approaches to avoiding corrupting shards in section 2. A set of malicious validators might attempt to create a fork.
As discussed in section 1. This problem has multiple solutions, the most common one being occasional cross-linking of the latest shard chain block to the beacon chain. The fork choice rule in the shard chains is then changed to always prefer the chain that is cross-linked, and only apply shard-specific fork-choice rule for blocks that were published since the last cross-link.
A set of validators might attempt to create a block that applies the state transition function incorrectly. For example, starting with a state in which Alice has 10 tokens and Bob has 0 tokens, the block might contain a transaction that sends 10 tokens from Alice to Bob, but ends up with a state in which Alice has 0 tokens and Bob has tokens, as shown on figure 3.
In a classic non-sharded blockchain such an attack is not possible, since all the participant in the network validate all the blocks, and the block with such an invalid state transition will be rejected by both other block producers, and the participants of the network that do not create blocks.
On the figure 4 there are five validators, three of whom are malicious. Since there are fewer validators in the honest fork, their chain is shorter. However, in classic nonsharded blockchain every participant that uses blockchain for any purpose is responsible for validating all the blocks they receive and recomputing the state.
In a sharded blockchain, however, no participant can validate all the transactions on all the shards, so they need to have some way to confirm that at no point in history of any shard of the blockchain no invalid block was included. It can only validate that a sufficient number of validators in that shard signed the block and as such attested to its correctness.
We will discuss solutions to this problem in section 2. The core idea in sharded blockchains is that most participants operating or using the network cannot validate blocks in all the shards. As such, whenever any participant needs to interact with a particular shard they generally cannot download and validate the entire history of the shard.
The partitioning aspect of sharding, however, raises a significant potential problem: without downloading and validating the entire history of a particular shard the participant cannot necessarily be certain that the state with which they interact is the result of some valid sequence of blocks and that such sequence of blocks is indeed the canonical chain in the shard.
We will first present a simple solution to this problem that has been proposed by many protocols and then analyze how this solution can break and what attempts have been made to address it. With this assumption of honest validator percentage, if the current set of validators in a shard provides us with some block, the naive solution assumes that the block is valid and that it is built on what the validators believed to be the canonical chain for that shard when they started validating.
The validators learned the canonical chain from the previous set of validators, who by the same assumption built on top of the block which was the head of the canonical chain before that. By induction the entire chain is valid, and since no set of validators at any point produced forks, the naive solution is also certain that the current chain is the only chain in the shard. See figure 6 for a visualization. Adaptively corrupting a single shard in a system with shards is significantly cheaper than corrupting the entire system.
Therefore, the security of the protocol decreases linearly with the number of shards. To have certainty in the validity of a block, we must know that at any point in history no shard in the system has a majority of validators colluding; with adaptive adversaries, we no longer have such certainty. As we discussed in section 1. Malicious forks can be addressed by blocks being cross-linked to the Beacon chain that is generally designed to have significantly higher security than the shard chains.
Producing invalid blocks, however, is a significantly more challenging problem to tackle. Consider figure 7 on which Shard 1 is corrupted and a malicious actor produces invalid block B. From this moment the improperly created tokens reside on an otherwise completely valid blockchain in Shard 2.
Some simple approaches to tackle this problem are:. A promising idea to resolve this issue would be to arrange shards into an undirected graph in which each shard is connected to several other shards, and only allow cross-shard transactions between neighboring shards e. If a cross-shard transaction is needed between shards that are not neighbors, such transaction is routed through multiple shards. In this design a validator in each shard is expected to validate both all the blocks in their shard as well as all the blocks in all the neighboring shards.
Consider a figure below with 10 shards, each having four neighbors, and no two shards requiring more than two hops for a cross-shard communication shown on figure 8. So if a malicious actor on Shard 1 is attempting to create an invalid block B, then build block C on top of it and initiate a cross-shard transaction, such cross-shard transaction will not go through since Shard 2 will have validated the entire history of Shard 1 which will cause it to identify invalid block B.
While corrupting a single shard is no longer a viable attack, corrupting a few shards remains a problem. On figure 9 an adversary corrupting both Shard 1 and Shard 2 successfully executes a cross-shard transaction to Shard 3 with funds from an invalid block B:. Shard 3 validates all the blocks in Shard 2, but not in Shard 1, and has no way to detect the malicious block. There are two major directions of properly solving state validity: fishermen and cryptographic proofs of computation.
There are various constructions that enable very succinct proofs that the blocks are invalid, so the communication overhead for the receiving nodes is way smaller than that of receiving a full block. This approach, however, has two major disadvantages:. The second solution to multiple-shard corruption is to use some sort of cryptographic constructions that allow one to prove that a certain computation such as computing a block from a set of transactions was carried out correctly.
Such constructions do exist, e. The primary problem with such primitives is that they are notoriously slow to compute. Coda Protocol, that uses zk-SNARKs specifically to prove that all the blocks in the blockchain are valid, said in one of the interviews that it can take 30 seconds per transaction to create a proof this number is probably smaller by now. Thus, the computation of such proofs can be split among a set of participants with significantly less redundancy than would be necessary to perform some trustless computation.
It also allows for participants who compute zk-SNARKs to run on special hardware without reducing the decentralization of the system. The second problem we will touch upon is data availability. Generally nodes operating a particular blockchain are separated into two groups: Full Nodes, those that download every full block and validate every transaction, and Light Nodes, those that only download block headers, and use Merkle proofs for parts of the state and transactions they are interested in, as shown on figure Now if a majority of full nodes collude, they can produce a block, valid or invalid, and send its hash to the light nodes, but never disclose the full content of the block.
There are various ways they can benefit from it. For example, consider figure There are three blocks: the previous, A, is produced by honest validators; the current, B, has validators colluding; and the next, C, will be also produced by honest validators the blockchain is depicted in the bottom right corner. You are a merchant. The validators of the current block B received block A from the previous validators, computed a block in which you receive money, and sent you a header of that block with a Merkle proof of the state in which you have money or a Merkle proof of a valid transaction that sends the money to you.
Confident the transaction is finalized, you provide the service. However, the validators never distribute the full content of the block B to anyone. When we apply the same scenario to sharding, the definitions of full and light node generally apply per shard: validators in each shard download every block in that shard and validate every transaction in that shard, but other nodes in the system, including those that snapshot shard chains state into the beacon chain, only download the headers.
Thus the validators in the shard are effectively full nodes for that shard, while other participants in the system, including the beacon chain, operate as light nodes. For the fisherman approach we discussed above to work, honest validators need to be able to download blocks that are cross-linked to the beacon chain.
If malicious validators cross-linked a header of an invalid block or used it to initiate a cross-shard transaction , but never distributed the block, the honest validators have no way to craft a challenge. We will cover three approaches to address this problem that complement each other. The most immediate problem to be solved is whether a block is available once it is published.
One proposed idea is to have so-called Notaries that rotate between shards more often than validators whose only job is to download a block and attest to the fact that they were able to download it. The problem with this naive approach is that it is impossible to prove later whether the Notary was or was not able to download the block, so a Notary can choose to always attest that they were able to download the block without even attempting to retrieve it. One solution to this is for Notaries to provide some evidence or to stake some amount of tokens attesting that the block was downloaded.
This is not a complete solution, since unless the light nodes collectively download the entire block the malicious block producers can choose. One solution is to use a construction called Erasure Codes to make it possible to recover the full block even if only some part of the block is available, as shown on figure Both Polkadot and Ethereum Serenity have designs around this idea that provide a way for light nodes to be reasonably confident the blocks are available.
The Ethereum Serenity approach has a detailed description in . In Polkadot, like in most sharded solutions, each shard called parachain snapshots its blocks to the beacon chain called relay chain. They then distribute one part to each validator on the relay chain. A particular relay chain validator would only sign on a relay chain block if they have their part for each parachain block that is snapshotted to such relay chain block.
See figure Note that all the approaches discussed above only attest to the fact that a block was published at all, and is available now. Blocks can later become unavailable for a variety of reasons: nodes going offline, nodes intentionally erasing historical data, and others. A whitepaper worth mentioning that addresses this issue is Polyshard , which uses erasure codes to make blocks available across shards even if several shards completely lose their data.
Unfortunately their specific approach requires all the shards to download blocks from all other shards, which is prohibitively expensive. The long term availability is not as pressing of an issue: since no participant in the system is expected to be capable of validating all the chains in all the shards, the security of the sharded protocol needs to be designed in such a way that the system is secure even if some old blocks in some shards become completely unavailable.
The sharding model with shard chains and a beacon chain is very powerful but has certain complexities. In particular, the fork choice rule needs to be executed in each chain separately, the fork choice rule in the shard chains and the beacon chain must be built differently and tested separately.
In Nightshade we model the system as a single blockchain, in which each block logically contains all the transactions for all the shards, and changes the whole state of all the shards. Physically, however, no participant downloads the full state or the full logical block.
Instead, each participant of the network only maintains the state that corresponds to the shards that they validate transactions for, and the list of all the transactions in the block is split into physical chunks, one chunks per shard. Under ideal conditions each block contains exactly one chunk per shard per block, which roughly corresponds to the model with shard chains in which the shard chains produce blocks with the same speed as the beacon chain.
However, due to network delays some chunks might be missing, so in practice each block contains either one or zero chunks per shard. See section 3. The two dominant approaches to the consensus in the blockchains today are the longest or heaviest chain, in which the chain that has the most work or stake used to build it is considered canonical, and BFT, in which for each block some set of validators reach a BFT consensus. In the protocols proposed recently the latter is a more dominant approach, since it provides immediate finality, while in the longest chain more blocks need to be built on top of the block to ensure the finality.
Often for a meaningful security the time it takes for sufficient number of blocks to be built takes on the order of hours. Using BFT consensus on each block also has disadvantages, such as:.
A hybrid model in which the consensus used is some sort of the heaviest chain, but some blocks are periodically finalized using a BFT finality gadget maintain the advantages of both models. Nightshade uses the heaviest chain consensus. Specifically when a block producer produces a block see section 3.
The weight of a block is then the cumulative stake of all the signers whose signatures are included in the block. The weight of a chain is the sum of the block weights. On top of the heaviest chain consensus we use a finality gadget that uses the attestations to finalize the blocks. We note, however, that the choice of the finality gadget is largely orthogonal to the rest of the design.
In Nightshade there are two roles: block producers and validators. As with all the Proof of Stake systems, not all the w block producers and not all the wv validators are different entities, since that cannot be enforced.
Each of the w block producers and the wv validators, however, do have a separate stake. As mentioned in section 3. The state of the main chain is split into n shards, and each block producer and validator at any moment only have downloaded locally a subset of the state that corresponds to some subset of the shards, and only process and validate transactions that affect those parts of the state.
To become a block producer, a participant of the network locks some large amount of tokens a stake. The maintenance of the network is done in epochs, where an epoch is a period of time on the order of days.
The participants with the w largest stakes at the beginning of a particular epoch are the block producers for that epoch. The block producer downloads the state of the shard they are assigned to before the epoch starts, and throughout the epoch collects transactions that affect that shard, and applies them to the state. The part of b related to shard s is called a chunk, and contains the list of the transactions for the shard to be included in b, as well as the merkle root of the resulting state.
Throughout the rest of the document we often refer to the block producer that is responsible to produce a chunk at a particular time for a particular shard as a chunk producer. Chunk producer is always one of the block producers. The block producers and the chunk producers rotate each block according to a fixed schedule. The block producers have an order and repeatedly produce blocks in that order. To ensure the data availability we use an approach similar to that of Polkadot described in section 2.
They then send one piece of the erasure coded chunk we call such pieces chunk parts, or just parts to each block producer.
We compute a merkle tree that contains all the parts as the leaves, and the header of each chunk contains the merkle root of such tree. The parts are sent to the validators via onepart messages. Each such message contains the chunk header, the ordinal of the part and the part contents. The message also contains the signature of the block producer who produced the chunk and the merkle path to prove that the part corresponds to the header and is produced by the proper block producer.
Once a block producer receives a main chain block, they first check if they have onepart messages for each chunk included in the block. If not, the block is not processed until the missing onepart messages are retrieved. Once all the onepart messages are received, the block producer fetches the remaining parts from the peers and reconstructs the chunks for which they hold the state.
If a block producer has a block for which a onepart message is missing, they might choose to still sign on it, because if the block ends up being on chain it will maximize the reward for the block producer. To address it we make each chunk producer when creating the chunk to choose a color red or blue for each part of the future encoded chunk, and store the bitmask of assigned color in the chunk before it is encoded.
Each onepart message then contains the color assigned to the part, and the color is used when computing the merkle root of the encoded parts. If the chunk producer deviates from the protocol, it can be easily proven, since either the merkle root will not correspond to onepart messages, or the colors in the onepart messages that correspond to the merkle root will not match the mask in the chunk. When a block producer signs on a block, they include a bitmask of all the red parts they received for the chunks included in the block.
Publishing an incorrect bitmask is a slashable behavior. The chunk producers only choose which transactions to include in the chunk but do not apply the state transition when they produce a chunk.
Correspondingly, the chunk header contains the merkle root of the merkelized state as of before the transactions in the chunk are applied. The transactions are only applied when a full block that includes the chunk is processed. A participant only processes a block if.
Once the block is being processed, for each shard for which the participant maintains the state for, they apply the transactions and compute the new state as of after the transactions are applied, after which they are ready to produce the chunks for the next block, if they are assigned to any shard, since they have the merkle root of the new merkelized state.
If a transaction needs to affect more than one shard, it needs to be consecutively executed in each shard separately. The full transaction is sent to the first shard affected, and once the transaction is included in the chunk for such shard, and is applied after the chunk is included in a block, it generates a so called receipt transaction, that is routed to the next shard in which the transaction need to be executed. If more steps are required, the execution of the receipt transaction generates a new receipt transaction and so on.
It is desirable that the receipt transaction is applied in the block that immediately follows the block in which it was generated. The receipt transaction is only generated after the previous block was received and applied by block producers that maintain the originating shard, and needs to be known by the time the chunk for the next block is produced by the block producers of the destination shard.
Thus, the receipt must be communicated from the source shard to the destination shard in the short time frame between those two events. Let A be the last produced block which contains a transaction t that generates a receipt r. Let B be the next produced block i. Let t be in the shard a and r be in the shard b. The lifetime of the receipt, also depicted on figure 18, is the following: Producing and storing the receipts. The chunk producer cpa for shard a receives the block A, applies the transaction t and generates the receipt r.
Distributing the receipts. Once cpa is ready to produce the chunk for shard a for block B, they fetch all the receipts generated by applying the transactions from block A for shard a, and included them into the chunk for shrad a in block B. Once such chunk is generated, cpa produces its erasure coded version and all the corresponding onepart messages. For a particular block producer bp cpa includes the receipts that resulted from applying transactions in block A for shard a that have any of the shards that bp cares about as their destination in the onepart message when they distributed the chunk for shard a in block B see figure 17, that shows receipts included in the onepart message.
Receiving the receipts. Remember that the participants both block producers and validators do not process blocks until they have onepart messages for each chunk included in the block.
Thus, by the time any particular particpiant applies the block B, they have all the onepart messages that correspond to chunks in B, and thus they have all the incoming receipts that have the shards the participant maintains state for as their destination. When applying the state transition for a particular shard, the participant apply both the receipts that they have collected for the shard in the onepart messages, as well as all the transactions included in the chunk itself.
It is possible that the number of receipts that target a particular shard in a particular block is too large to be processed. For example, consider figure 19, in which each transaction in each shard generates a receipt that targets shard 1. By the next block the number of receipts that shard 1 needs to process is comparable to the load that all the shards combined processed while handling the previous block.
Specifically, for each shard the last block B and the last shard s within that block from which the receipts were applied is recorded. When the new shard is created, the receipt are applied in order first from the remaining shards in B, and then in blocks that follow B, until the new chunk is full. Under normal circumstances with a balanced load it will generally result in all the receipts being applied and thus the last shard of the last block will be recorded for each chunk , but during times when the load is not balanced, and a particular shard receives disproportionately many receipts, this technique allows them to be processed while respecting the limits on the number of transactions included.
Note that if such unbalanced load remains for a long time, the delay from the receipt creation until application can continue growing indefinitely. One way to address it is to drop any transaction that creates a receipt targeting a shard that has a processing delay that exceeds some constant e. Consider figure By block B the shard 4 cannot process all the receipts, so it only processes receipts origination from up to shard 3 in block A, and records it.
In block C the receipts up to shard 5 in block B are included, and then by block D the shard catches up, processing all the remaining receipts in block B and all the receipts from block C. A chunk produced for a particular shard or a shard block produced for a particular shard chain in the model with shard chains can only be validated by the.
They can be block producers, validators, or just external witnesses that downloaded the state and validate the shard in which they store assets. In this document we assume that majority of the participants cannot store the state for a large fraction of the shards. It is worth mentioning, however, that there are sharded blockchains that are designed with the assumption that most participants do have capacity to store the state for and validate most of the shards, such as QuarkChain.
Since only a fraction of the participants have the state to validate the shard chunks, it is possible to adaptive corrupt just the participants that have the state, and apply an invalid state transition. As discussed in section 2. Such participants are called Fishermen. For a fisherman to be able to challenge an invalid block, it must be ensured that such a block is available to them. The data availability in Nightshade is discussed in section 3.
In Nightshade once a block is produced, the chunks were not validated by anyone but the actual chunk producer. When the next block is produced, it contains attestations see section 3. To address this issue, we allow any participant that maintains the state of a shard to submit a challenge on-chain for any invalid chunk produced in that shard.
Once a participant detects that a particular chunk is invalid, they need to provide a proof that the chunk is invalid. Since the majority of the network participants do not maintain the state for the shard in which the invalid chunk is produced, the proof needs to have sufficient information to confirm the block is invalid without having the state.
We set a limit Ls of the amount of state in bytes that a single transaction can cumulatively read or write. Any transaction that touches more than Ls state is considered to be invalid. Remember from the section 3. The state root included in the chunk in block B is the state root before applying such transactions, but after applying the transactions from the last chunk in the same shard before the block B. We extend the information that a chunk producer includes in the chunk.
Instead of just including the state after applying all the transactions, it instead includes a state root after applying each contiguous set of transactions that collectively read and write Ls bytes of state.
Each shard would contain its own independent state, meaning a unique set of account balances and smart contracts. Sharding is definitely the most complex Ethereum scaling solution. This presents a big problem: if Ethereum nodes become too expensive to run, the network will be more susceptible to centralization.
At the same time, requiring each transaction to be processed by every node will make it so Ethereum never scales. Sharding is a potential solution to this very problem. Sharding begs the question, does every node in the network need to process each transaction for a blockchain to be considered secure? To date, no blockchain network can exhibit all three of the following traits without having to sacrifice one of them:. Within a shard, notaries are randomly picked to periodically vote on the validity of blocks, think miners in a regular blockchain.
These shard blocks are referred to as collations and are chained together the same way blocks on a blockchain are. In fact, each shard is tied to the main Ethereum chain in the form of merkle trees, creating a cryptographic connection between the two. We can prove certain things about the shard relative to when it was created.
Each shard acts as its own standalone blockchain. The users on each shard have their own account balances away from the main Ethereum network and can only transact with other users on the shard. An easy way to think of it is to imagine if Ethereum was split into thousands of islands. Each island can do its own thing, it can have its own features and everyone belonging to that island can enjoy it. If they want to contact other islands, they will have to use some sort of protocol.
It creates a way for each shard to store individual receipts of each transaction. While Sharding sounds great in theory, there are a number of potential attack vectors. One specific attack is the single-shard takeover attack. In this scheme, an attacker takes over the majority of block producers in a shard to create a malicious shard that can submit invalid transactions.
The Ethereum core developers point to random sampling as a solution, but this is still in active development. Sharding is also much easier to implement on a proof-of-stake chain than it is on a proof-of-work chain. There are already active validators within proof-of-stake which can be randomly assigned to different shards. In proof-of-work, nothing can be done to completely stop a miner from contributing hash power to a particular shard.
Start here! Without diving into the technical nitty gritty, this post will give you a high-level overview of what Ethereum is. This simple video explains smart contracts, the basic function that powers applications and programs built on Ethereum. In the case of Casper FFG, it will achieve finality by introducing the notion of validators. The validators are responsible for confirming the blockchain at key checkpoints.
Once finalized, it will no longer be possible to change any of the blocks before the checkpoint. More about Byzantine Fault Tolerance here. Ethereum has an active area of research and development for Ethereum 2. The first phase won't have any execution or EVM, so it won't integrate with the main net. This phase will focus on establishing the basic structure of sharding, which is the data layer, coming to consensus as to what data is in the shards.
Phase two is all about the state, giving meaning to the data and the notion of transaction. Here is where it will have an EVM, and will introduce backwards incompatible changes at a smart contract level, like storage rent. Just like in the Casper implementation, there is not an official release date but it is expected that we will see these changes in for the first phase and for the second. One of the most important aspects of sharding would be to implement some method of cross-shard communication.
What if you wanted to send a transaction from address X in shard 1 to address Y in shard 3? This cross-shard communication will be achieved through applying the concept of transaction receipts. The receipt for a transaction will be stored in a transaction group merkle root in the main chain block. The shard receiving a transaction from another shard will check the merkle root to ensure that the receipt has not been spent.
Essentially, the receipts are stored in a shared memory that can be verified by other shards, but not altered. Therefore, shards will be able to communicate with each other. Going beyond the initial sharding development, it is possible that Ethereum will adopt a super-quadratic sharding scheme. This means that the system will have shards within shards. The potential for scalability would be massive � a super-quadratically sharded blockchain could potentially go to into hundreds of thousands of transactions per second perhaps even more.
This will offer tremendous benefits to users, decreasing transaction fees and serving as a more general purpose infrastructure for new applications. For now, this is way down the road in the development roadmap Phase 6 but it is certainly worth mentioning. Sharding may look like a very comprehensive solution for scalability, and in many ways it is, but there is still a lot of work to be done. It is important to highlight that sharding will exist exclusively at the protocol layer and will not be exposed to developers.
The Ethereum state system will continue to look as it currently does, but the protocol will have a built-in system to manage the shards so everything will be in the background for developers.
Finally, one thing is sure, once sharding and Casper are fully merged into the blockchain and another game or app can become as popular as Crypto Kitties, it will be very difficult for the network to get congested again.
Three ways developers and data scientists can play to their strengths and compliment each other's weaknesses. What's the right package manager to manage your dependencies?
This article compares the pros and cons of each package manager and how to use them. I love the process of turning ideas into code, and you can count on me for writing good quality code. Constantly tackling new programming tools, Drew has developed a powerful learning curve that has allowed him to master web developement, mobile development, cryptocurrenc I'm an expert problem solver, and these days I focus on helping others design big things based on blockchain.
In Ethereum, this is the current account set containing current balances, smart contract code, and nonces at some point in time. History : an ordered list of all transactions that have taken place since genesis. Transaction : represents an operation that some user wants to make, and is cryptographically signed. It changes the state of a system.
State transition function: a function that takes a state, applies a transaction, and outputs a new state. Merkle tree: a cryptographic hash tree structure that can store a very large amount of data, where authenticating each individual piece of data only takes O log n space and time.
More about merkle trees here. Receipt: an object that represents an effect of a transaction that is not directly stored in the state, but is still stored in a merkle tree e. State root: the root hash of the merkle tree representing the state.
In the world of blockchain, there seems to be a trilemma that claims that blockchain systems can only, at most, have two of the following three properties: Decentralization Scalability Security Currently, Ethereum is decentralized and secured but not scalable. Vitalik Buterin Co-founder of Ethereum describes this concept with the following example : Imagine that Ethereum has been split into thousands of islands.
How would a sharded Ethereum blockchain look like? We can see the sharding solution in two layers. This is an example of what a collation looks like: Source: Hackernoon Collations are basically groups of transactions that belong to one single shard. Ethereum 2. Enter Casper FFG Casper is a PoS consensus protocol being developed by the team at Ethereum and just as we would expect from a PoS protocol, it reduces the cost of consensus - which is the amount of energy cost when compared with PoW.
Main Changes in the Sharding Roadmap Ethereum has an active area of research and development for Ethereum 2. On the other hand, sharding was broken down into two big phases. Cross-Shard Communication One of the most important aspects of sharding would be to implement some method of cross-shard communication. Example of the concept of receipts for the cross-sharding system Diagram by Sharding FAQ Future Implementations in Sharding Going beyond the initial sharding development, it is possible that Ethereum will adopt a super-quadratic sharding scheme.
Conclusion Sharding may look like a very comprehensive solution for scalability, and in many ways it is, but there is still a lot of work to be done. Like this article? Share it with your friends! Alejandro Vargas Corral. Full stack engineer with over 6 years of experience. Former CTO and co-founder of a tech startup that facilitated bill payment solutions in Mexico.
Currently working with computer vision and machine learning in augmented reality Related Articles. Arc has top developers available for hire and freelance jobs. Check out our Blockchain developers! Satwik Kansal. Drew Taylor.
We modify the format of a transaction so that the transaction must specify an access list enumerating the parts of the state that it can access we describe this more precisely later; for now consider this informally as a list of addresses. Any attempt to read or write to any state outside of a transaction's specified access list during VM execution returns an error.
This prevents attacks where someone sends a transaction that spends 5 million cycles of gas on random execution, then attempts to access a random account for which the transaction sender and the collator do not have a witness, preventing the collator from including the transaction and thereby wasting the collator's time.
Outside of the signed body of the transaction, but packaged along with the transaction, the transaction sender must specify a "witness", an RLP-encoded list of Merkle tree nodes that provides the portions of the state that the transaction specifies in its access list. This allows the collator to process the transaction with only the state root. When publishing the collation, the collator also sends a witness for the entire collation.
See also ethresearch thread on The Stateless Client Concept. In a stateless client model, nodes do not store the state. The returned output is:. This allows the functions to be "pure", as well as only dealing with small-sized objects as opposed to the state in existing Ethereum, which is currently hundreds of gigabytes , making them convenient to use for sharding.
If a validator address is provided, then it checks on the main chain if the address is an active validator. If it is, then every time a new period on the main chain starts i.
For every shard i in the watching list, every time a new collation header appears in the main chain, it downloads the full collation from the shard network, and verifies it. It locally keeps track of all valid headers where validity is defined recursively, i.
Note that this implies the reorgs of the main chain and reorgs of the shard chain may both influence the shard head. To implement the algorithms for watching a shard, and for creating a collation, the first primitive that we need is the following algorithm for fetching candidate heads in highest-to-lowest order. First, suppose the existence of an impure, stateful method getNextLog , which gets the most recent CollationAdded log in some given shard that has not yet been fetched.
This would work by fetching all the logs in recent blocks backwards, starting from the head, and within each block looking in reverse order through the receipts. The idea is that this algorithm is guaranteed to check potential head candidates in highest-to-lowest sorted order of score, with the second priority being oldest to most recent. For example, suppose that CollationAdded logs have hashes and scores as follows:. If we number the collations A A5, B B5, C C5 and D D5, the precise returning order is:.
If a client is watching a shard, it should attempt to download and verify any collations in that shard that it can checking any given collation only if its parent has already been verified.
This will in normal circumstances return a valid collation immediately or at most after a few tries due to latency or a small-scale attack that creates a few invalid or unavailable collations.
This process has three parts. The above algorithm is equivalent to "pick the longest valid chain, check validity as far as possible, and if you find it's invalid then switch to the next-highest-scoring valid chain you know about". The algorithm should only stop when the validator runs out of time and it is time to create the collation. When it comes time to attempt to include a transaction into a collation, this algorithm will need to be run on the transaction first.
Suppose that the transaction has an access list [A An] , and a witness W. If the original W was correct, and the transaction was sent not before the time that the client checked back to, then getting this Merkle branch will always succeed. For illustration, here is full pseudocode for a possible transaction-gathering part of this method. This requires asking the network for a Merkle branch for the collator's account.
When the network replies with this, the post-state root after applying the reward, as well as the fees, can be calculated. The collator can then package up the collation, of the form header, txs, witness , where the witness is the union of the witnesses of all the transactions and the branch for the collator's account.
The existing account model is replaced with one where there is a single-layer trie, and all account balances, code and storage are incorporated into the trie. Specifically, the mapping is:. See also ethresearch thread on A two-layer account trie inside a single-layer trie. These shard blocks are referred to as collations and are chained together the same way blocks on a blockchain are. In fact, each shard is tied to the main Ethereum chain in the form of merkle trees, creating a cryptographic connection between the two.
We can prove certain things about the shard relative to when it was created. Each shard acts as its own standalone blockchain. The users on each shard have their own account balances away from the main Ethereum network and can only transact with other users on the shard.
An easy way to think of it is to imagine if Ethereum was split into thousands of islands. Each island can do its own thing, it can have its own features and everyone belonging to that island can enjoy it. If they want to contact other islands, they will have to use some sort of protocol.
It creates a way for each shard to store individual receipts of each transaction. While Sharding sounds great in theory, there are a number of potential attack vectors. One specific attack is the single-shard takeover attack.
In this scheme, an attacker takes over the majority of block producers in a shard to create a malicious shard that can submit invalid transactions.
The Ethereum core developers point to random sampling as a solution, but this is still in active development. Sharding is also much easier to implement on a proof-of-stake chain than it is on a proof-of-work chain. There are already active validators within proof-of-stake which can be randomly assigned to different shards.
In proof-of-work, nothing can be done to completely stop a miner from contributing hash power to a particular shard. Start here! Without diving into the technical nitty gritty, this post will give you a high-level overview of what Ethereum is. This simple video explains smart contracts, the basic function that powers applications and programs built on Ethereum. DApp is an abbreviated form for decentralized application. This animated video explains what makes them different � and perhaps far superior.
Learn why Ethereum is so much more than just a simple cryptocurrency, but an open software platform built on the blockchain. Gas is essential to the Ethereum network, quite literally the fuel that allows it to operate. Gas refers to the unit that measures the amount of computational effort required to execute specific operations on the Ethereum network. The ERC Standard outlines a set of common rules that all tokens can follow on the Ethereum network to produce expected results.
ERC tokens, more commonly referred to as Non-Fungible tokens NFTs allow developers to tokenize ownership of any arbitrary data, drastically increasing the design space of what can be represented as a token on the Ethereum blockchain. This video explains how it works.
WebNov 25, �� Initially there would be a two speeds ethereum with individuals running an eth node and a sharding node connected to the eth node. The two then eventually, once . WebNov 11, �� You can understand the definition of sharding in Ethereum by identifying the primary goals behind sharding. In the case of centralized database management, .