====================================================================

Author: Alistair Stewart, Fatemeh Shirazi (minor)

Last update: 20.12.2019

====================================================================

XCMP - Relay chain light client design

In this document, we describe how messages are stored and retrieved for XCMP. This write up does not cover ICMP networking, but rather the emphasis is on what data is on-chain such that parachains and parathreads can be sure about which messages they have been received.

Problem

To build a new parablock (parachain block) we need to be aware of any sending chains who have sent the receiving chain messages since the relay chain block we have already acted on messages up to.

However, to keep all the hashes of these messages on the relay chain is a lot of data and may require looking for that data in many places.

The period since we have acted on messages might be long and parachain validators might have been reassigned or not be validators at all anymore.

All this is especially true for parathreads, who might have long gaps between parablocks.

Goals

(1) We want to be always able to validate PoVs for as long as possible, at least a day after a parablock has been produced. To do this, we need to check that the right incoming messages were acted on.

(2) Also, we want to use minimal relay chain state. Relay chain processing and state access per block also needs to be feasible.

(3) If we are a full node of receiving parachain or parathread we want to know whether we have a new message sent to us from a parachain since the last relay chain block that we acted on messages on.

(4) In particular, if another parachain that could send a receiving parachain a message, produces blocks that do not send any messages to that receiver, then a collator of the receiving parachain does not need any data from full nodes or parachain validators of the non-sending parachain.

Assumptions

A receiving para acts on messages in order of the relay chain block that includes the header of the parablocks that iniated that message. If multiple sending paras have sent a receiving para messages in the same relay chain block then the order of messages that the receiving para will act on is according to a rule such as increasing paraid, or alternatively a deterministic shuffle based block number. It is reasonable to assume that a para can act on at least all messages sent by another single para in a single parablock. Hence, we can always assume once a receiving para has acted on a parablock in the relay chain it has acted on all messages associated to that parablock. Thus there is well-defined watermark=(relay chain block number, paraid) that indicates the last parachain block whose messages the receiving para has acted on.

The parablock’s watermark should be in the parachain header that goes into a relay chain block and the last watermark needs to be stored in the relay chain state associated with the para.

Each parachain can talk to every other parachain, however, since there may be a very large number of parathreads we want to limit the places we have to query every time we want to build a block. Hence, we need to limit the amount of metadata we have to store messages sent from parathreads.

Either we have to query the relay chain in lots of places or else the relay chain logic (and so all full nodes of the relay chain) has to query lots of places in the relay chain. To limit this, we want to limit the number of chains the parathread can communicate with to 100 and refer to those as channels. A parachain can communicate to all other parachains (up to a 100) and also have channels to a known number of parathreads (possibly more than 100). The list of channels is stored on the relay chain state. Both chains need to agree to set up a channel, and while it is open, both need to have the other as one of their channels.

We assume here that channels are one directional, but they may be implemented as bidirectional.

We will also have a limitation on the number of unreceived messages one chain can send to the other.

Solution Overview

We want to have a data structure that is more compressed and also ensures receiving para can still find messages sent to them. Next, we describe how to construct such a data structure.

Data Structure: Merkle Tree and Bitfield

We want to build a data structure that allows having a small amount of data on the relay chain blocks and relay chain state, but want to enable verfication of all received messages in the PoV block.

Message Queue Chain: Is a hash chain defined as follows. We have a \(H(Head_{HC})\): \(Head_{HC}\)\(=H(m)|| b || H(\text{ previous } Head_{HC}))\),

where m is a message, H() is a hash function, and b is the block number we last sent a message (not \(m\), but the previous message).

See here for more details.

For each parablock we have a tuple that consists of the parablock message root (sender_message_queue_merkle_root) and a bitfield in the parablock header in the relay chain block.

The message root is the root of a Merkle tree that can be used to look up the \(head_{HC}\) from the receiving paraid. The bitfield has one bit for each channel and indicates which receiving paras this parablock sent messages to. The message root and bitfield will be in the sending para header and will be used t update the relay chain state.

When a receiving para is building a PoV block it is going to include the latest of these message roots from the paras that have channels open to this para. Using the message root, the receiving para needs to prove that it got all the messages from the last watermark up to the current watermark. This it can do by giving the message root and Merkle proof and revealing the hash chain back to the earliest message that came after the last watermark. This contains the hashes of all the current messages which can be used to verify that all the received message were correct. Moreover, the message hash chain that is revealed also can be used to verify that the last message before the ones we acted on had a block number that is lower than the last watermark.

Creating a Block PoV block:Thus there are two things that need to work to produce a parablock. Firstly, we need to get all the messages and the corresponding Merkle proofs. Secondly, to produce a PoV block, we need to be able to query the relay chain for the latest message root with the corresponding block number, for the last message received in each channel.

To validate a PoV block we will need to be able to find these message roots for at least a day after. This has a potentially large relay chain storage requirement if these are still on-chain. It would also be nice for light clients of the relay chain to be fishermen, and so be able to validate relay chain-blocks. For this reason, we will use relay chain light client state proofs for these message roots.

That is, for each channel, in the PoV block we will have a chain of hashes, starting at a relay chain state root, that consists of 3 parts: - a relay chain light client proof of the message root, - the Merkle proof of the head of the hash chain, and - the hash chain expanded back to the point where the previous block number is before the previous watermark. This has the hashes of all messages we need to act on in that channel.

Implementation details about Relay-chain egress data

The Channel State Table (CST) is a construct that exists within the Relay-chain’s state and tracks the latest sender message queue roots. The CST items are stored in rows, where all items share the same sender. They are paired with the target’s ParaId into a storage map. A second storage item contains a Merkle root of each row.

See here for more details.

When the relay chain processes a parablock header, which includes a message root and bitfield, we update a row of the CST corresponding to the sending para and the Merkle root of this row. The row contains the latest message root and block numbers for each para that has a channel from the chain that this parablock belongs to.

This row may be quite large, but we can update it with a single storage write as it is in one place.

In principle, if we use this design, along with the bitfield, we can have a large number of outgoing channels, at the cost of more data in this single write opration. In particular, parachains will be allowed to connect to many more than 100 parathreads.

Optionally, parachains could have ingress queues that consist of (paraid, last message root, block number) for all incoming channels. The relay chain could updates this every block. This would make it possible to have 10,000 channels for one chain and not to have to look up 10,000 places on the relay chain.

Which Data is Stored Where?

Parachain-header/candidate_receipt in the relay chain block: the message root and a bitfield that refer to receiving paras. Since we have a limited number of known channels this bitfield could be 128 bits for parathreads but for parachains it might need to be variably sized. It also needs the watermark (relay chain block number and paraid). Also it includes a relay chain state root and corresponding block number for which all relay light client proofs in the PoV block are based on.

Sending parachain state: the sending parachain state stores the hash chain back to the last watermark it saw for the receiving para on the relay chain. It also stores the merkle proofs for each message root for all links in the hash chain (not just the head of the hash chain). Link refers to the triple which is hash of message, previous block number, and hash of previous link.

The size of the hash chain determines how full the channel is. We will drop old messages on receiving evidence (via more relay chain light client proofs) that the watermark of the receiving chain has been updated.

Sending para validators: they keep the message that has been sent at parablocks that they attested to, the full Merkle tree and the latest head of hash chain \(Head_{HC}\). This data is stored for a day.

Relay chain state on-chain: we have CST that was described in the previous section.

Producing a PoV block

A PoV block needs to include a nested Merkle proof and hash chain expansion thats starts at the light client state root and ends at each incoming message that needs to be acted on. The Merkle proofs will have a lot of parts in common and can be optimized by sharing the common parts (future work).

Consider a collator \(C_A\) that wants to produce a PoV block for para \(A\). We assume para B has a channel to para A (can send messages to A) and para A has a channel to para D (can send messages to D). Note that if channels are unidirectional then A might not be able to send messages to B and D not to A.

The collator \(C_A\) ask some full node of the relay chain needs to construct a light client proof of what the message roots for all channel that are open to para \(A\) (e.g., para B). Note that \(C_A\) and the full node might be riunning on the same machine.

\(C_A\) also needs light client proofs for the watermarks of paras, para A has channels to (e.g., para D). All these light client proofs should be constructed simultaneously from the relay chain state so they all start with the same relay chain state root. This relay chain state root and corresponding block numebr will be in the parachain header (candidate_receipt).

Optional: For parachains, if we are going with ingress queues for them, we maintain a list of (paraid, last message root, block number) for all incoming channels that the relay chain updates every block. Thus the relay chain light client proof is just this list and a Merkle proof.

For parathreads or parachains if we do not special case them, the full node needs to look at egress data in the CST for up to 100 rows (or more for parachains) corresponding to paras that have incoming channels with para \(A\) (i.e., para B). For each of these channels, we give a Merkle proof that starts at the relay chain state root and ends at the (message root, block number) pair. That is, for each channel there is a nested Merkle proof, where first we need a Merkle proof of the CST row hash and secondly need to construct a Merkle tree for the row and Merkle proof for the entry corresponding to para A.

We include all 100+ of these channel Merkle proofs in the relay chain light client proof.

After the full node has given the collater, \(C_A\), all the light client proofs, \(C_A\) has the block number and message root of all latest messages. Thus it can verify if para A has correctly received any particular message’s content (payload) already.

In case a message say from para B has not been acted on by para A, then \(C_A\) needs that message and its proof from the message root. \(C_A\) may have this message and proof already, if \(C_A\) does not, then it needs to ask any full node of the para B that it happens to be connected to or para A’s para validators or the para validators of B at the block number of the message. If the messages from para B are coming from its para validators, this may mean asking many validators who were para validators of B at different times, since the para validators of paras rotate as a function of block number. Note that full nodes pf para B would know all of these messages and should be asked first.

Along with the latest message from B, \(C_A\) should receive the proof that links the latest message to the message root and also the block number of the previous message, so it knows if it needs to ask for earlier messages as well.

When \(C_A\) has both: - all proofs of messages from message roots, - all proofs of messages roots from one relay chain state root (the nested Merkle prrofs described above), it can combine them to get proofs for all messages from the relay chain state root and put these proofs along with all messages acted on into the PoV block.

For example, if para A has received many messages from para B since its last watermark, then the PoV block should include:

  • A Merkle proof from the relay chain state root in the parachain header (or candidate receipt) to the CST row hash of B’s row in the CST

  • A Merkle proof of the message root and block number corresponding to the last message from B to A at the block height of the relay chain state root from the CST row hash.

  • A Merkle proof of the head of the hash chain of messages from B to A from the message root

  • An expansion of the hash chain (the triples) for the channel from B to A back to the point where the previous block number is before A’s previous watermark

  • Messages from B to A from after A’s previous watermark and up to its new watermark, whose hashes correspond to those in the hash chain expansion.

Note that if the relay chain state root is correct and it is for a block number no ealier than the new watermark, then this proof shows that these are exactly the messages from B that A should be acting on.

It is likely that the parachain block, that full nodes of the parachain use to update their state, will contain unproven assertions about the received messages, watermark updates etc.

Validating a PoV block

Given the scheme above, we can make anyone who knows three things able to validate a PoV block: - The PoV block itself, - the state-transition-validation-funtion (STVF) - the parachain block header. This would enable fishermen who are not clients of either or both the parachain and the relay chain to validate PoV blocks.

However there is a downside to the scheme if we cannot trust the STVF. (Once we have SPREE, which we’ll talk about below, this will not be an issue anymore.) The downside when we have a malicous STVF is that the relay chain does not verify the hash chain updates, and they are left in parachain state. If this parachain state was changed by the STVF, it would be possible to require a sending para to receive a message with a hash for which no message has ever been sent and so eventually stalling the receiving para.

Before SPREE, we should require that the parachain validators verify the hash chain update independently of the STVF verification. The parachain validators would need to check the 1) Merkle proof of the new message and hash chain head from the relay chain root, and 2) the Merkle proof from the last message root, which is currently in the relay chain. Checking (1) and (2) satisfy that the previous hash and block number in the new hash chain head indeed corresponds to the previous hash chain head.

Failing to do that correctly should be a slashing condition for the parachain validators as well. However if we are going to implement SPREE soon, then this is a low priority as we may end up skipping it.

SPREE integration

SPREE is a method of having modules with state and execution sandboxed from the rest of the wasm execution. We want a SPREE module on one chain (can be para or maybe relay chain) to send a message to the same SPREE module on another chain and for it to be impossible for the STVF of either chain to interfere with that message.

Since our solution requires parachain state for messages, the obvious way to do this is to have the message handling code and state itself be handles by a SPREE module. We would have a central SPREE module that all parachains would require if they wanted to participate in XCMP at all.

The message handling SPREE module would be called first on execution of an STVF and it would route incoming messages to other SPREE modules and to the bulk of the STVF, before handing over control to the rest of the STVF.

We think that receiving modules should not act on the messages on receipt, but merely add the incoming messages to a buffer and wait for the STVF to scedule them time to act on them.

How much data is this?

The egress data for a sending pararchain has a Merkle root and block number for receiving paras. The Merkle root will be a 32 byte hash and the block number 4 bytes.

We may have up to a million channels. This means 36 MB data on-chain or 72MB if we include the Merkle trees as well as the data and the Merkle root for each egress table. In the worst case, half of these would be updated in a block.

We need to hash twice this amount of data to calulate its Merkle root. Blake2b is fast, see https://blake2.net/ , and in 1 second, it can hash over 100 MB on a modern processor. So we’d be looking at 36 MB and 360ms.

But even this is unlikely.