Ethereum state trie
In the last edition of The 1. We ended with the concept of stateless ethereum , and left a more detailed examination of the stateless client for this post. Stateless is the new direction of Eth 1. Every finalized block in the chain has one and only one state, which is agreed upon by all participants in the network.
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Dead end Ethereum source code analysis of state
By clicking below, you agree to our terms of service. Published Linked with GitHub. Like Bookmark Subscribe Edit. Ethereum blockchain state on swarm This document describes a way to put ethereum state data on swarm, gives a 4 step roadmap and discusses the potential merits of the approach.
Ethereum state on swarm The simplest idea is to treat trie nodes as a chunk type, using their ethereum keccak hash as content address. With this, the state tries log, contract storage, tx become content address-linked native data structures on swarm.
The second phase the protocol is aware of the internal structure of the trie node and is able to traverse the trie. The URL path can serve as intructions for the protocol to traverse along the branches based on the partial key given in the url path. If a root trie node hash and a full address are given as host and path part of the URL respectively , the url retrieves an account node ECA or contract. This supports the use-case of a simple decentralised blockchain explorer API.
If anywhere along the path an empty subtrie is encountered, i. Importantly, this is to be distinguished from a response which means that a properly referenced trie node chunk the one in the url or along the traversed path is not retrievable from swarm. Caveats: the size of chunks is not limited in theory, especially contract creation transactions can be of arbitrary size. If no reasonable upper limit applies to nodes, trie node chunk delivery could be used for DoS attacks Empirical analysis is needed to investigate the distribution of transaction sizes.
In other words the tries are considered to encode the datastream as a file in a similar way to the swarm hash. If served via streams, this can be used to aid fast syncing snapshots. This allows for light client requests without light servers and their throughput management. SWAP incentivisation can be extended to this scenario.
Syncing support The statetrie's retrieval is way more economical if only the leaf nodes are downloaded. All the intermediate nodes can be reconstructed locally and validated against trie roots. Nodes that keep state locally can pin trie nodes and advertise that the leaf data can be streamed from them. Nodes would connect to these state seeder s either directly or via pss and leech the data from them using the stream! This would be exactly the same mechanism as the one used for webzztorrent, torrent-like stream download of files.
Nodes that pin content can notify the content owner defined as the ens owner or publisher of the root manifest who maintains and publishes a pinning feed, pointing to a resource including addresses of content providers similar to torrent trackers.
Consumers of large files or large merklized structures can then choose to retrieve content via the stream protocol. Servers only need to store the leaf chunks and keep the sequence of hashes of leaf chunks as special streamable chunks content addressed by the appropriate merkle hash, ie.
Discussion Fast sync loads a snapshot of a state. Using a snapshot with a format that needs to be create raises problems. Checkpointing is deemed prohibitive since the creating the snapshot - defined here as a fixed format describing the state - is computationally intensive. Purely iterating over all trie nodes takes 15 minutes. Even if such a snapshot is created by some service once, generating updates would not be feasible. If there was a format with which a node can generate diffs to the previous state, it may be possible, since a node would need to keep all state info only until the next checkpoint snapshot is created.
With diffs available, clients could sync by downloading a chain of diffs and apply to the genesis snapshot, to come to a state. Surely this also has the caveat that as the diffs to apply increase, the more past state will have stale nodes which were fetched initially creating unnecessary downloads.
Adding this file to the swarm raises further problems. If swarm has no spam protection, the system is attackable by DDOS. If POB based spam protection is in place then full nodes have a barrier of entry for even the charitable service they provide.
While in theory incentivisation could somehow solve the sustainability of such a service, it is complex to implement. The other issue is that with content address storage, if state snapshots and their diffs are to be retrieved based on their address, there needs to be a trusted translation service to advise clients about the content address of new state diffs.
Such a service is difficult to incentivise and in any case requires staked nodes for accountability so raises the same problem as upload itself. Putting the state tries as a native data structure on swarm, i. We can assume that any client has the header chain available and therefore knows the root hashes of state tries. The client would start to download the nodes of the latest state. As the header chain progresses, the client can always switch to the latest root, and 'apply the diff'.
Those try nodes that are preserved in the new state will simply find the trie node chunk locally. The snapshot is purely the set of trie nodes constituting a state.
Diffs are automatically defined as those trie nodes that are not in the previous set. Creating the snapshot is a non-issue and uploading can be load-balanced among a cluster of nodes and be guaranteed by charitable volunteers initially until properly incentivised. As the trie roots are part of the block header, any client having the header chain will immediately allow the use of swarm retrieval without a mapping service.
Designating specific checkpoints is unnecessary for the correctness but can help diffs of a particular state become more wide spread through swarm caching, thereby increasing availability and decreasing latency of retrieval. Consequently coordinating on checkpoints at consensual puntcuated intervals will help further. This same structure supports retrieval of trie nodes by hash or random access to trie state data therefore serving LES requests, or even serve as a remote trie implementation.
Using the scheme to bootsrap a full node then is the same mechanism as light nodes. If the trie falls back to on demand retrieval via swarm, then running the VM will only populate the db with trie nodes that transactions reference, therefore they can bootstrap in a short amount of time, requiring nothing special. Ultimately, the client will have the full state and act as a full node, able to serve the eth protocol.
Beyond archive, full and light nodes, there has been proposals to introduce a 4th type of node syncing, which prunes historical blocks. Such a pruned state is much easier to bootsrap from. The caveat is that without incentives this might discourage participants to operate proper full nodes and with time run the danger of historical blocks disappearing. A solution to this problem if we make sure that historical blocks, though not stored on each full node, at least stay available collectively in swarm.
First a service run by a charitable entity could make sure these pruned blocks and their states remain available by uploading them to swarm. This process could be collectivised, but uploading the pruned blocks will raise the spam issue.
If there is enough nodes serving content with swarm to cover the address space, ie. Published on HackMD. Like Bookmark Subscribe. Password Forgot password.
Golang New Examples
Evm call opcode. Each instantiation has its sand-box world state initialized from the sand-box of the EVM at the level above. Stack items have a size of bits; in fact, the EVM is a bit word machine this facilitates Keccak hash scheme and elliptic-curve computations. Ethereum Evm Opcodes. With this approach, we eliminate other factors and only count the normalized execution time unit, and nodes can reach a consensus as well.
A Deeper look into Ethereum’s Technology
This article is the second in a series explaining a bug I found in the go-ethereum Geth client. An attacker could use this bug to set traps for the ethereum blockchain and arbitrarily trigger a hard fork. Synchronization When you want to run an Ethernet node, you must first synchronize on the entire network, i. As the name implies, full sync means that the entire sync process to the ethereum blockchain is performed independently. This means that your Geth node downloads and verifies the proof-of-work PoW for each block, in addition to counting every transaction within the block; thus, the node can generate the latest state of the blockchain locally without having to trust other nodes. This model is more secure, but at the expense of speed; full synchronization of Geth can take anywhere from a few days to a few weeks. However, some users may not want to wait for weeks. In fast-sync mode, Geth downloads blocks, but only randomly selects blocks to verify the proof of workload instead of verifying every block; also, instead of performing transactions itself, it downloads the state tree directly from other nodes in the network to get the final blockchain state. Of course, Geth will not blindly trust the state tree data sent back by other nodes either, as a malicious node could also claim that an account has only a little bit of money but actually has a lot.
Ethereum State Data Structures
This post is a quick summary on how verkle tries work and how they can be used in order to make Eth1 stateless. The KZG Kate polynomial commitment scheme is a polynomial commitment scheme. Its primary functionality is the ability to commit to a polynomial via an elliptic curve group element for notation see the linked post. We can then open this commitment at any point by giving the verifier the value as well as a group element , and this proof of the correctness of the value can be checked using a pairing equation. A vector commitment is a commitment scheme that takes as an input different values and produces a commitment that can be opened at any of these values.
The State Growth Problem Facing Blockchains
Before discussing the main data objects in Ethereum, we need to go over what Merkle trees are, and what are the properties that make them useful. A Merkle tree is a tree data structure, where the leaf nodes contain the hash of a block of data, and the non-leaf nodes contain the hash of its children nodes. In a Merkle tree, any change to the underlying data causes the hash of the node referring to the data to change. Since each parent node hash depends on the data of its children, any change to the data of a child node causes the parent hash to change. This happens to each parent node up to the root node. Therefore, any change to the data at the leaf nodes causes the root node hash to change.
Ethereum Smart-Contract Storage
This is the second in a series of blog posts about bugs I've found in go-ethereum Geth. If you haven't already, take a look at Part 1 here. Today's post is about a bug in Geth's state downloader which could be used to trick it into syncing with mainnet incorrectly. If exploited, an attacker could have booby trapped the Ethereum blockchain and triggered a hard fork at will. Whenever someone wants to run an Ethereum node, they must first synchronize with the network. This means downloading or computing all of the data needed to build a complete picture of the chain state at the latest block. Depending on the needs of the user, some tradeoffs between security and speed can be made, so Geth supported at the time two different sync modes: full sync and fast sync. As the name would suggest, full sync performs a full synchronization of the Ethereum blockchain.
Try out PMC Labs and tell us what you think. Learn More. As pharmacogenomics data becomes increasingly integral to clinical treatment decisions, appropriate data storage and sharing protocols need to be adopted. One promising option for secure, high-integrity storage and sharing is Ethereum smart contracts.
This post is a continuation of my Getting Deep Into Series started in an effort to provide a deeper understanding of the internal workings and other cool stuff about Ethereum and blockchain in general which you will not find easily on the web. Here are the other parts of the Series:. First of all, we have to see that what all things we need to store for making the blockchain system work. As we can see here that we can change the state by executing a transaction on it.
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Find centralized, trusted content and collaborate around the technologies you use most. Connect and share knowledge within a single location that is structured and easy to search. Though blockchain is immutable, it does not mean the current state can not be updated.
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