Next Consensus Architecture Proposal

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Authors: Christian Cachin, Konstantinos Christidis, Chet Murthy, Binh Nguyen and Marko Vukolić

This page documents the architecture of a blockchain infrastructure with the roles of a blockchain node separated into roles of peers (who maintain state/ledger) and consenters (who consent on the order of transactions included in the blockchain state). In common blockchain architectures (including Hyperledger fabric as of June 2016) these roles are unified (cf. validating peer in Hyperledger fabric). The architecture also introduces endorsing peers (endorsers), as special type of peers responsible for validating (i.e., endorsing) transactions.

The architecture has the following advantages compared to the design in which peers/consenters/endorsers are unified.

Chaincode trust flexibility. The architecture separates trust assumptions for chaincodes (blockchain applications) from trust assumptions for consensus. In other words, the consensus service may be provided by one set of nodes (consenters) and tolerate some of them to fail or misbehave, and the nodes responsible for executing and endorsing transactions of particular chaincode may be different for each chaincode.
Scalability. As the endorser nodes responsible for particular chaincode are orthogonal to the consenters, the system may scale better than if these functions were done by the same nodes. In particular, this results when different chaincodes specify disjoint endorsers, which introduces a partitioning of chaincodes between endorsers and allows parallel chaincode execution (endorsement). Besides, chaincode execution, which can potentially be costly, is removed from the critical path of the consensus service.
Confidentiality. The architecture also facilitates deployment of chaincodes whose state is part of the blockchain state but that should remain confidential outside its endorsers.
Consensus modularity. The architecture is modular and allows pluggable consensus implementations.

1. System architecture

The blockchain is a distributed system consisting of many nodes that communicate with each other. The blockchain runs programs called chaincode, holds state and ledger data, and executes transactions. The chaincode is the central element: transactions are operations invoked on the chaincode and only chaincode changes the state. Transactions have to be "validated" and only valid transactions are committed and have an effect on the state. There may exist a special chaincode for management functions and parameters, called system chaincode.

1.1. Transactions

Transactions may be of two types:

Deploy transactions create new chaincode and take a program as parameter. When a deploy transaction executes successfully, the chaincode has been installed "on" the blockchain.
Invoke transactions perform an operation in the context of previously deployed chaincode. An invoke transaction refers to a chaincode and to one of its provided functions. When successful, the chaincode executes the specified function - which may involve modifying the corresponding state, and returning an output.

As described later, deploy transactions are special cases of invoke transactions, where a deploy transaction that creates new chaincode, corresponds to an invoke transaction on a system chaincode.

Remark: This document currently assumes that a transaction either creates new chaincode or invokes an operation provided by one already deployed chaincode. This document does not yet describe: a) support for cross-chaincode transactions, b) optimizations for query (read-only) transactions.

1.2. State

The state of the blockchain ("world state") has a simple structure and consists of a key/value store (KVS), where keys are names and values are arbitrary blobs. These entries are manipulated by the chaincodes (applications) running on the blockchain through put, get, list, delete and other KVS-operations. Keys in the KVS can be recognized from their name to belong to a particular chaincode. The state is stored persistently and updates to the state are logged.

More formally, blockchain state s is modeled as an element of a mapping K -> (V X N), where:

K is a set of keys
V is a set of values
N is an infinite ordered set of version numbers. Injective function next: N -> N takes an element of N and returns the next version number.

Both V and N contain a special element \bot, which is in case of N the lowest element. Initially all keys are mapped to (\bot,\bot). For s(k)=(v,ver) we denote v by s(k).value, and ver by s(k).version.

KVS operations are modeled as follows:

put(k,v), for k\in K and v\in V, takes the blockchain state s and changes it to s' such that s'(k)=(v,next(s(k).version)) with s'(k')=s(k') for all k'!=k.
get(k) returns s(k).
list() returns the largest subset K' of K such that for every k in K': s(k).value!=\bot.
delete(k) is equivalent to put(k,\bot).

Evolution of blockchain state (history) is kept in a ledger. Ledger is a hashchain of blocks of transactions. Transactions in the ledger are totally ordered.

Blockchain state and ledger are further detailed in Section 4.

1.3. Nodes

Nodes are the communication entities of the blockchain. A "node" is only a logical function in the sense that multiple nodes of different types can run on the same physical server. What counts is how nodes are grouped in "trust domains" and associated to logical entities that control them.

There are three types of nodes:

Client or submitting-client: a thin client that submits an actual transaction-invocation.
Peer: a node that commits transactions and maintains the state and a copy of the ledger. Besides, peers can have two special roles:

a. A submitting peer or submitter,

b. An endorsing peer or endorser.
Consensus-service-node or consenter: a node running the communication service that implements a delivery guarantee (such as atomic broadcast) typically by running consensus.

Notice that consenters and clients do not maintain ledgers and blockchain state, only peers do.

The types of nodes are explained next in more detail.

1.3.1. Client

The client represents the entity that acts on behalf of an end-user. It is stateless and must connect to a peer for communicating with the blockchain. The client may connect to any peer of its choice. Clients create and thereby invoke transactions.

1.3.2. Peer

A peer communicates with the consensus service and maintain the blockchain state and the ledger. Such peers receive ordered state updates from the consensus service and apply them to the locally held state.

Peers can additionally take up one of two roles described next.

Submitting peer. A submitting peer is a special role of a peer that provides an interface to clients, such that a client may connect to a submitting peer for invoking transactions and obtaining results. The peer communicates with the other blockchain nodes on behalf of one or more clients for executing the transaction.
Endorsing peer. The special function of an endorsing peer occurs with respect to a particular chaincode and consists in validating (i.e., endorsing) a transaction before it is committed. Every chaincode may specify an endorsement policy that may refer to a set of endorsing peers. The policy defines the necessary and sufficient conditions for a transaction to be valid (typically a set of endorsers' signatures), as described later in Sections 2 and 3. In the special case of deploy transactions that install new chaincode the (deployment) endorsement policy is specified as an endorsement policy of the system chaincode.

To emphasize a peer that does not also have a role of a submitting peer or an endorsing peer, such a peer is sometimes referred to as a committing peer.

1.3.3. Consensus service nodes (Consenters)

The consenters form the consensus service, i.e., a communication fabric that provides delivery guarantees. The consensus service can be implemented in different ways: ranging from a centralized service (used e.g., in development and testing) to distributed protocols that target different network and node fault models.

Peers are clients of the consensus service, to which the consensus service provides a shared communication channel offering a broadcast service for messages containing transactions. Peers connect to the channel and may send and receive messages on the channel. The channel supports atomic delivery of all messages, that is, message communication with total-order delivery and (implementation specific) reliability. In other words, the channel outputs the same messages to all connected peers and outputs them to all peers in the same logical order. This atomic communication guarantee is also called total-order broadcast, atomic broadcast, or consensus in the context of distributed systems. The communicated messages are the candidate transactions for inclusion in the blockchain state.

Partitioning. Consensus service may support multiple channels similar to the topics of a publish/subscribe (pub/sub) messaging system. Clients can connects to a given channel and can then send messages and obtain the messages that arrive. Channels can be thought of as partitions - clients connecting to one channel are unaware of the existence of other channels, but clients may connect to multiple channels. For simplicity, in the rest of this document and unless explicitly mentioned otherwise, we assume consensus service consists of a single channel/topic.

Consensus service API. Peers connect to the channel provided by the consensus service, via the interface provided by the consensus service. The consensus service API consists of two basic operations (more generally asynchronous events):

broadcast(blob): the submitting peer calls this to broadcast an arbitrary message blob for dissemination over the channel. This is also called request(blob) in the BFT context, when sending a request to a service.
deliver(seqno, prevhash, blob): the consensus service calls this on the peer to deliver the message blob with the specified sequence number (seqno) and hash of the most recently delivered blob (prevhash). In other words, it is an output event from the consensus service. deliver() is also sometimes called notify() in pub-sub systems or commit() in BFT systems.

Notice that consensus service clients (i.e., peers) interact with the service only through broadcast() and deliver() events.

Consensus properties. The guarantees of the consensus service (or atomic-broadcast channel) are as follows. They answer the following question: What happens to a broadcasted message and what relations exist among delivered messages?

Safety (ordering guarantee): As long as peers are connected for sufficiently long periods of time to the channel (they can disconnect or crash, but will restart and reconnect), they will see an identical series of delivered (seqno, prevhash, blob) messages. This means the outputs (deliver() events) occur in the same order on all peers and according to sequence number and carry identical content (blob and prevhash) for the same sequence number. Note this is only a logical order, and a deliver(seqno, prevhash, blob) on one peer is not required to occur in any real-time relation to deliver(seqno, prevhash, blob) that outputs the same message at another peer. Put differently, given a particular seqno, no two correct peers deliver different prevhash or blob values. Moreover, every broadcasted blob is only delivered once, and no value blob is delivered unless some consensus client (peer) actually called broadcast(blob).
Safety (hash chain integrity guarantee): The deliver() event contains the cryptographic hash of the previous deliver() event (prevhash). When the consensus service implements atomic broadcast guarantees, prevhash is the cryptographic hash of the parameters from the deliver() event with sequence number seqno-1. In other words, for two events deliver(seqno-1, prevhash0, blob0) and deliver(seqno, prevhash, blob), prevhash = HASH(seqno-1||prevhash0||blob0).

This establishes a hash chain across deliver() events, which is used to help verify the integrity of the consensus output, as discussed in Sections 4 and 5 later. In the special case of the first deliver() event, prevhash has a default value.
Liveness (delivery guarantee): Liveness guarantees of the consensus service are specified by a consensus service implementation. The exact guarantees may depend on the network and node fault model.

In principle, absent network faults and submitting peer faults, consensus service should guarantee that every correct peer that connects to the consensus service eventually delivers every submitted transaction.

2. Basic workflow of transaction endorsement

In the following we outline the high-level request flow for a transaction.

Remark: Notice that the following protocol does not assume that all transactions are deterministic, i.e., it allows for non-deterministic transactions.

2.1. The client creates a transaction and sends it to a submitting peer of its choice

To invoke a transaction, the client sends the following message to a submitting peer spID.

<SUBMIT,clientID,chaincodeID,txPayload,retryFlag,clientSig>, where

clientID is the ID of the submitting client,
chaincodeID refers to the chaincode to which the transaction pertains,
txPayload is the payload containing the submitted transaction itself,
retryFlag is a boolean that tells the submitting peer whether to retry the submission of the transaction in case transaction fails,
clientSig is the client's signature on the tuple (SUBMIT,clientID,chaincodeID,txPayload).

TODO: Decide whether to include explicitly local/logical time at the client (a timestamp).

2.2. The submitting peer prepares a transaction and sends it to endorsers for obtaining an endorsement

On reception of a <SUBMIT,clientID,chaincodeID,txPayload,retryFlag,clientSig> message from a client, the submitting peer first verifies the client's signature clientSig and then prepares a transaction. This involves submitting peer tentatively executing a transaction (txPayload), by invoking the chaincode to which the transaction refers (chaincodeID) and the copy of the state that the submitting peer locally holds.

As a result of the execution, the submitting peer computes a state update (stateUpdate) and version dependencies (verDep) - (MVCC+postimage info in DB language).

Recall that the state consists of key/value (k/v) pairs. All k/v entries are versioned, that is, every entry contains ordered version information, which is incremented every time when the value stored under a key is updated. The peer that interprets the transaction records all k/v pairs accessed by the chaincode, either for reading or for writing, but the peer does not yet update its state. More specifically:

verDep is a tuple verDep=(readset,writeset). Given state s before a submitting peer executes a transaction:
- for every key k read by the transaction, pair (k,s(k).version) is added to readset.
- for every key k modified by the transaction, pair (k,s(k).version) is added to writeset.
additionally, for every key k modified by the transaction to the new value v', pair (k,v') is added to stateUpdate. Alternatively, v' could be the delta of the new value to previous value (s(k).value).

An implementation may combine verDep.writeset with stateUpdate into a single data structure.

Then, tran-proposal := (spID,chaincodeID,txContentBlob,stateUpdate,verDep),

where txContentBlob is chaincode/transaction specific information that is treated as an opaque blob by the fabric. The intention is to have txContentBlob used as some representation of txPayload (e.g., txContentBlob=txPayload, or txContentBlob=HASH(txPayload), or in general txContentBlob=f(txPayload), where f is chaincode specific function).

Cryptographic hash of tran-proposal is used by all nodes as a unique transaction identifier tid (i.e., tid=HASH(tran-proposal)).

The submitting peer then sends the transaction (i.e., tran-proposal) to the endorsers for the chaincode concerned. The endorsing peers are selected according to the interpretation of the policy and the availability of peers, known by the peers. For example, the transaction could be sent to all endorsers of a given chaincodeID. That said, some endorsers could be offline, others may object and choose not to endorse the transaction. The submitting peer tries to satisfy the policy expression with the endorsers available.

The submitting peer spID sends the transaction to an endorsing peer epID using the following message:

<PROPOSE,txPayload,tran-proposal>

Possible optimization: txPayload may be omitted from a PROPOSE message if in tran-proposal.txContentBlob=txPayload.

Finally, the submitting peer stores tran-proposal and tid in memory and waits for responses from endorsing peers.

Alternative design: As described here the submitting peer communicates directly with the endorsers. This could also be a function performed by the consensus service; in this case it should be determined whether fabric has to follow atomic broadcast delivery guarantee for this or use simple peer-to-peer communication. In that case the consensus service would also be responsible to collect the endorsements according to the policy and to return them to the submitting peer.

TODO: Decide on communication between submitting peers and endorsing peers: peer-to-peer or using the consensus service.

2.3. An endorser receives and endorses a transaction

When a transaction in tran-proposal is delivered to a connected endorsing peer for the chaincode tran-proposal.chaincodeID by means of a PROPOSE message, the endorsing peer performs the following steps:

The endorser simulates the transaction (using txPayload) and verifies that the state update and dependency information are correct. If everything is valid, the peer digitally signs the statement (TRANSACTION-VALID, tid) producing signature epSig. The endorsing peer then sends <TRANSACTION-VALID, tid,epSig> message to the submitting peer (tran-proposal.spID).
Else, in case the transaction fails to validate, we distinguish the following cases:

a. if the endorser obtains different state updates than those in tran-proposal.stateUpdates, the peer signs a statement (TRANSACTION-INVALID, tid, INCORRECT_STATE) and sends the signed statement to the submitting peer.

b. if the endorser is aware of more advanced data versions than those referred to in tran-proposal.verDeps, it signs a statement (TRANSACTION-INVALID, tid, STALE_VERSION) and sends the signed statement to the submitting peer.

c. if the endorser does not want to endorse a transaction for any other reason (internal endorser policy, error in a transaction, etc.) it signs a statement (TRANSACTION-INVALID, tid, REJECTED) and sends the signed statement to the submitting peer.

Notice that an endorser does not change its state in this step, the updates are not logged!

Alternative design: An endorsing peer may omit to inform the submitting peer about an invalid transaction altogether, without sending explicit TRANSACTION-INVALID notifications.

Alternative design: The endorsing peer submits the TRANSACTION-VALID/TRANSACTION-INVALID statement and signature to the consensus service for delivery.

TODO: Decide on alternative designs above.

2.4. The submitting peer collects an endorsement for a transaction and broadcasts it through consensus

The submitting peer waits until it receives enough messages and signatures on (TRANSACTION-VALID, tid) statements to conclude that the transaction proposal is valid. This will depend on the chaincode endorsement policy (see also Section 3). If the endorsement policy is satisfied, the transaction has been endorsed; note that it is not yet committed. The collection of signatures from endorsing peers which establish that a transaction is valid is called an endorsement, the peer stores them in endorsement.

If the submitting peer does not manage to collect an endorsement for a transaction proposal, it abandons this transaction and notifies the submitting client. If retryFlag has been originally set by the submitting client (see step 1 and the SUBMIT message) the submitting peer may (depending on submitting peer policies) retry the transaction (from step 2).

For transaction with a valid endorsement, we now start using the consensus-fabric. The submitting peer invokes consensus service using the broadcast(blob), where blob=(tran-proposal, endorsement).

2.5. The consensus service delivers a transactions to the peers

When an event deliver(seqno, prevhash, blob) occurs and a peer has applied all state updates for blobs with sequence number lower than seqno, a peer does the following:

It checks that the blob.endorsement is valid according to the policy of the chaincode (blob.tran-proposal.chaincodeID) to which it refers. (This step might be performed even without waiting for applying the state updates with sequence numbers smaller than seqno.)
It verifies that the dependencies (blob.tran-proposal.verDep) have not been violated meanwhile.

Verification of dependencies can be implemented in different ways, according to a consistency property or "isolation guarantee" that is chosen for the state updates. For example, serializability can be provided by requiring the version associated with each key in the readset or writeset to be equal to that key's version in the state, and rejecting transactions that do not satisfy this requirement. As another example, one can provide snapshot isolation when all keys in the writeset still have the same version as in the state as in the dependency data. The database literature contains many more isolation guarantees.

TODO: Decide whether to insist on serializability or allow chaincode to specify isolation level.

If all these checks pass, the transaction is valid and it is committed. This means that a peer appends the transaction to the ledger and subsequently applies blob.tran-proposal.stateUpdates to blockchain state. Only committed transactions may change the state.
If any of these checks fail, the transaction is invalid and the peer drops the transaction. It is important to note that invalid transactions are not committed, do not change the state, and are not recorded.

Additionally, the submitting peer notifies the client of a dropped transaction. If retryFlag has been originally set by the submitting client (see step 1 and the SUBMIT message) the submitting peer may (depending on submitting peer policies) retry the transaction (from step 2).

Illustration of the transaction flow (common-case path).

Figure 1. Illustration of the transaction flow (common-case path).

3. Endorsement policies

3.1. Endorsement policy specification

An endorsement policy, is a condition on what endorses a transaction. An endorsement policy is specified by a deploy transaction that installs specific chaincode. A transaction is declared valid only if it has been endorsed according to the policy. An invoke transaction for a chaincode will first have to obtain an endorsement that satisfies the chaincode's policy or it will not be committed. This takes place through the interaction between the submitting peer and endorsing peers as explained in Section 2.

Formally the endorsement policy is a predicate on the transaction, endorsement, and potentially further state that evaluates to TRUE or FALSE. For deploy transactions the endorsement is obtained according to a system-wide policy (for example, from the system chaincode).

Formally an endorsement policy is a predicate referring to certain variables. Potentially it may refer to:

keys or identities relating to the chaincode (found in the metadata of the chaincode), for example, a set of endorsers;
further metadata of the chaincode;
elements of the transaction itself;
and potentially more.

The evaluation of an endorsement policy predicate must be deterministic.

The list is ordered by increasing expressiveness and complexity, that is, it will be relatively simple to support policies that only refer to keys and identities of nodes.

TODO: Decide on parameters of the endorsement policy.

The predicate may contain logical expressions and evaluates to TRUE or FALSE. Typically the condition will use digital signatures on the transaction invocation issued by endorsing peers for the chaincode.

Suppose the chaincode specifies the endorser set E = {Alice, Bob, Charlie, Dave, Eve, Frank, George}. Some example policies:

A valid signature from all members of E.
A valid signature from any single member of E.
Valid signatures from endorsing peers according to the condition (Alice OR Bob) AND (any two of: Charlie, Dave, Eve, Frank, George).
Valid signatures by any 5 out of the 7 endorsers. (More generally, for chaincode with n > 3f endorsers, valid signatures by any 2f+1 out of the n endorsers, or by any group of more than (n+f)/2 endorsers.)
Suppose there is an assignment of "stake" or "weights" to the endorsers, like {Alice=49, Bob=15, Charlie=15, Dave=10, Eve=7, Frank=3, George=1}, where the total stake is 100: The policy requires valid signatures from a set that has a majority of the stake (i.e., a group with combined stake strictly more than 50), such as {Alice, X} with any X different from George, or {everyone together except Alice}. And so on.
The assignment of stake in the previous example condition could be static (fixed in the metadata of the chaincode) or dynamic (e.g., dependent on the state of the chaincode and be modified during the execution).

How useful these policies are will depend on the application, on the desired resilience of the solution against failures or misbehavior of endorsers, and on various other properties.

3.2. Implementation

Typically, endorsement policies will be formulated in terms of signatures required from endorsing peers. The metadata of the chaincode must contain the corresponding signature verification keys.

An endorsement will typically consist of a set of signatures. It can be evaluated locally by every peer or by every consenter node with access to the chaincode metadata (which includes these keys), such that this node does not require interaction with another node. Neither does a node need access to the state for verifying an endorsement.

Endorsements that refer to other metadata of the chaincode can be evaluated in the same way.

TODO: Formalize endorsement policies and design an implementation.

4. Blockchain data structures

The blockchain consists of three data structures: a) raw ledger, b) blockchain state and c) validated ledger). Blockchain state and validated ledger are maintained for efficiency - they can be derived from the raw ledger.

Raw ledger (RL). The raw ledger contains all data output by the consensus service at peers. It is a sequence of deliver(seqno, prevhash, blob) events, which form a hash chain according to the computation of prevhash described before. The raw ledger contains information about both valid and invalid transactions and provides a verifiable history of all successful and unsuccessful state changes and attempts to change state, occurring during the operation of the system.

The RL allows peers to replay the history of all transactions and to reconstruct the blockchain state (see below). It also provides submitting peer with information about invalid (uncommitted) transactions, on which submitting peers can act as described in Section 2.5.
(Blockchain) state. The state is maintained by the peers (in the form of a KVS) and is derived from the raw ledger by filtering out invalid transactions as described in Section 2.5 (Step 5 in Figure 1) and applying valid transactions to state (by executing put(k,v) for every (k,v) pair in stateUpdate or, alternatively, applying state deltas with respect to previous state).

Namely, by the guarantees of consensus, all correct peers will receive an identical sequence of deliver(seqno, prevhash, blob) events. As the evaluation of the endorsement policy and evaluation of version dependencies of a state update (Section 2.5) are deterministic, all correct peers will also come to the same conclusion whether a transaction contained in a blob is valid. Hence, all peers commit and apply the same sequence of transactions and update their state in the same way.
Validated ledger (VL). To maintain the abstraction of a ledger that contains only valid and committed transactions (that appears in Bitcoin, for example), peers may, in addition to state and raw ledger, maintain the validated ledger. This is a hash chain derived from the raw ledger by filtering out invalid transactions.

###4.1. Batch and block formation

Instead of outputting individual transactions (blobs), the consensus service may output batches of blobs. In this case, the consensus service must impose and convey a deterministic ordering of the blobs within each batch. The number of blobs in a batch may be chosen dynamically by a consensus implementation.

Consensus batching does not impact the construction of the raw ledger, which remains a hash chain of blobs. But with batching, the raw ledger becomes a hash chain of batches rather than hash chain of individual blobs.

With batching, the construction of the (optional) validated ledger blocks proceeds as follows. As the batches in the raw ledger may contain invalid transactions (i.e., transactions with invalid endorsement or with invalid version dependencies), such transactions are filtered out by peers before a transaction in a batch becomes committed in a block. Every peer does this by itself. A block is defined as a consensus batch without the invalid transactions, that have been filtered out. Such blocks are inherently dynamic in size and may be empty. An illustration of block construction is given in the figure below. Illustration of the transaction flow (common-case path).

Figure 2. Illustration of validated ledger block formation from raw ledger batches.

###4.2. Chaining the blocks

The batches of the raw ledger output by the consensus service form a hash chain, as described in Section 1.3.3.

The blocks of the validated ledger are chained together to a hash chain by every peer. The valid and committed transactions from the batch form a block; all blocks are chained together to form a hash chain.

More specifically, every block of a validated ledger contains:

The hash of the previous block.
Block number.
An ordered list of all valid transactions committed by the peers since the last block was computed (i.e., list of valid transactions in a corresponding batch).
The hash of the corresponding batch from which the current block is derived.

All this information is concatenated and hashed by a peer, producing the hash of the block in the validated ledger.

5. State transfer and checkpointing

In the common case, during normal operation, a peer receives a sequence of deliver() events (containing batches of transactions) from the consensus service. It appends these batches to its raw ledger and updates the blockchain state and the validated ledger accordingly.

However, due to network partitions or temporary outages of peers, a peer may miss several batches in the raw ledger. In this case, a peer must transfer state of the raw ledger from other peers in order to catch up with the rest of the network. This section describes a way to implement this.

###5.1. Raw ledger state transfer (batch transfer)

To illustrate how basic state transfer works, assume that the last batch in a local copy of the raw ledger at a peer p has sequence number 25 (i.e., seqno of the last received deliver() event equals 25). After some time peer p receives deliver(seqno=54,hash53,blob) event from the consensus service.

At this moment, peer p realizes that it misses batches 26-53 in its copy of the raw ledger. To obtain the missing batches, p resorts to peer-to-peer communication with other peers. It calls out and asks other peers for returning the missing batches. While it transfers the missing state, p continues listening to the consensus service for new batches.

Notice that p does not need to trust any of its peers from which it obtains the missing batches via state transfer. As p has the hash of the batch 53 (namely, hash53), which p trusts since it obtained that directly from the consensus service, p can verify the integrity of the missing batches, once all of them have arrived. The verification checks that they form a proper hash chain.

As soon as p has obtained all missing batches and has verified the missing batches 26-53, it can proceed to the steps of section 2.5 for each of the batches 26-54. From this p then constructs the blockchain state and the validated ledger.

Notice that p can start to speculatively reconstruct the blockchain state and the validated ledger as soon as it receives batches with lower sequence numbers, even if it still misses some batches with higher sequence numbers. However, before externalizing the state and committing blocks to the validated ledger, p must complete the state transfer of all missing batches (in our example, up to batch 53, inclusively) and processing of individual transferred batches as described in Section 2.5.

###5.2. Checkpointing

The raw ledger contains invalid transactions, which may not necessarily be recorded forever. However, peers cannot simply discard raw-ledger batches and thereby prune the raw ledger once they establish the corresponding validated-ledger blocks. Namely, in this case, if a new peer joins the network, other peers could not transfer the discarded batches (in the raw ledger) to the joining peer, nor convince the joining peer of the validity of their blocks (of the validated ledger).

To facilitate pruning of the raw ledger, this document describes a checkpointing mechanism. This mechanism establishes the validity of the validated-ledger blocks across the peer network and allows checkpointed validated-ledger blocks to replace the discarded raw-ledger batches. This, in turn, reduces storage space, as there is no need to store invalid transactions. It also reduces the work to reconstruct the state for new peers that join the network (as they do not need to establish validity of individual transactions when reconstructing the state from the raw ledger, but simply replay the state updates contained in the validated ledger).

Notice that checkpointing facilitates pruning of the raw ledger and, as such, it is only performance optimization. Checkpointing is not necessary to make the design correct.

####5.2.1. Checkpointing protocol

Checkpointing is performed periodically by the peers every CHK blocks, where CHK is a configurable parameter. To initiate a checkpoint, the peers broadcast (e.g., gossip) to other peers message <CHECKPOINT,blocknohash,blockno,peerSig>, where blockno is the current blocknumber and blocknohash is its respective hash, and peerSig is peer's signature on (CHECKPOINT,blocknohash,blockno), referring to the validated ledger.

A peer collects CHECKPOINT messages until it obtains enough correctly signed messages with matching blockno and blocknohash to establish a valid checkpoint (see Section 5.2.2.).

Upon establishing a valid checkpoint for block number blockno with blocknohash, a peer:

if blockno>latestValidCheckpoint.blockno, then a peer assigns latestValidCheckpoint=(blocknohash,blockno),
stores the set of respective peer signatures that constitute a valid checkpoint into the set latestValidCheckpointProof.
(optionally) prunes its raw ledger up to batch number blockno (inclusive).

####5.2.2. Valid checkpoints

Clearly, the checkpointing protocol raises the following questions: When can a peer prune its Raw Ledger? How many CHECKPOINT messages are "sufficiently many"?. This is defined by a checkpoint validity policy, with (at least) two possible approaches, which may also be combined:

Local (peer-specific) checkpoint validity policy (LCVP). A local policy at a given peer p may specify a set of peers which peer p trusts and whose CHECKPOINT messages are sufficient to establish a valid checkpoint. For example, LCVP at peer Alice may define that Alice needs to receive CHECKPOINT message from Bob, or from both Charlie and Dave.
Global checkpoint validity policy (GCVP). A checkpoint validity policy may be specified globally. This is similar to a local peer policy, except that it is stipulated at the system (blockchain) granularity, rather than peer granularity. For instance, GCVP may specify that:
- each peer may trust a checkpoint if confirmed by 7 different peers.
- in a deployment where every consenter is also a peer and where up to f consenters may be (Byzantine) faulty, each peer may trust a checkpoint if confirmed by f+1 different consenters.

####5.2.3. Validated ledger state transfer (block transfer)

Besides facilitating the pruning of the raw ledger, checkpoints enable state transfer through validated-ledger block transfers. These can partially replace raw-ledger batch transfers.

Conceptually, the block transfer mechanism works similarly to batch transfer. Recall our example in which a peer p misses batches 26-53, and is transferring state from a peer q that has established a valid checkpoint at block 50. State transfer then proceeds in two steps:

First, p tries to obtain the validated ledger up to the checkpoint of peer q (at block 50). To this end, q sends to p its local (latestValidCheckpoint,latestValidCheckpointProof) pair. In our example latestValidCheckpoint=(hash50,block50). If latestValidCheckpointProof satisfies the checkpoint validity policy at peer p, then the transfer of the blocks 26 to 50 is possible. Otherwise, peer q cannot convince p that its local checkpoint is valid. Peer p might then choose to proceed with raw-ledger batch transfer (Section 5.1).
If the transfer of blocks 26-50 was successful, peer p still needs to complete state transfer by fetching blocks 51-53 of the validated ledger or batches 51-53 of the raw ledger. To this end, p can simply follow the Raw-ledger batch transfer protocol (Section 5.1), transferring these from q or any other peer. Notice that the validated-ledger blocks contain hashes of respective raw-ledger batches (Section 4.2). Hence the batch transfer of the raw ledger can be done even if peer p does not have batch 50 in its Raw Ledger, as hash of batch 50 is included in block 50.

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