consensus with GPT

Roman Pleshkov
suggest a consensus algorithm that is doable to implement 
One consensus algorithm that is relatively easy to implement is the Practical Byzantine Fault Tolerance (PBFT) algorithm. PBFT is a consensus algorithm that is used in distributed systems to ensure that all nodes in the network agree on the state of the system, even if some nodes are faulty or malicious.

The PBFT algorithm is designed to be fault-tolerant, meaning that it can handle failures of nodes in the network. It works by dividing the nodes in the network into three groups: a primary group, a backup group, and a client group. The primary group is responsible for proposing new transactions to be added to the blockchain, while the backup group acts as a safety net in case the primary group fails. The client group is responsible for sending transactions to the network.

In the PBFT algorithm, each node has a copy of the blockchain and a state machine that reflects the current state of the system. When a client sends a transaction to the network, it is first sent to the primary node, which broadcasts it to the backup nodes. The backup nodes validate the transaction and then send a response back to the primary node, indicating whether they agree with the transaction.

Once a majority of the backup nodes have agreed with the transaction, the primary node adds the transaction to the blockchain and broadcasts the new state of the system to all nodes in the network. All nodes then update their state machines to reflect the new state of the system.

The PBFT algorithm has been proven to work well in practice and has been used in a number of real-world applications, such as the Hyperledger Fabric blockchain platform. However, it is important to note that the PBFT algorithm requires a relatively large number of nodes to function effectively, as it relies on a majority of nodes agreeing on transactions.




Roman Pleshkov
please give me a sudo code of PBFT 
Here is a simplified pseudocode implementation of the Practical Byzantine Fault Tolerance (PBFT) consensus algorithm:

Initialization:

Set up a network of n nodes, where f < n/3 nodes are faulty
Assign a unique ID to each node
Transaction flow:

A client sends a request to the primary node, containing the transaction to be added to the blockchain
The primary node validates the transaction and creates a new block containing the transaction
The primary node sends a PRE-PREPARE message to all backup nodes, containing the ID of the block and the transaction
Upon receiving the PRE-PREPARE message, each backup node validates the transaction and sends a PREPARE message to all nodes, indicating that it agrees with the transaction
Once a backup node has received f+1 PREPARE messages, it sends a COMMIT message to all nodes, indicating that it has committed to the transaction
Once a node has received f+1 COMMIT messages, it adds the block to its blockchain and sends a response to the client
View change:

If a node does not receive a PRE-PREPARE message within a certain timeframe, it assumes that the primary node has failed and triggers a view change
The node sends a VIEW-CHANGE message to all other nodes, containing information about the current view and the last block added to the blockchain
Upon receiving f+1 VIEW-CHANGE messages, a node becomes the new primary node and starts a new view
The new primary node requests missing PRE-PREPARE messages from backup nodes and continues the transaction flow as normal
Checkpointing:

To prevent the blockchain from becoming too long, nodes periodically take checkpoints of their blockchain and send a CHECKPOINT message to all other nodes
Upon receiving a CHECKPOINT message, a node validates the blockchain up to the checkpoint and deletes old blocks that are no longer needed
This is a simplified version of the PBFT algorithm, and there are many additional details and optimizations that can be added for a complete implementation.




Roman Pleshkov
is it possible to use CRDT instead of consensus 
Yes, it is possible to use CRDT (Conflict-free Replicated Data Types) instead of consensus algorithms in some scenarios.

CRDTs are a type of data structure that allows multiple replicas of a system to converge to a consistent state without the need for a central coordinator or consensus algorithm. CRDTs achieve this by ensuring that all replicas apply the same set of operations in the same order, resulting in a deterministic outcome.

CRDTs work well in distributed systems where eventual consistency is acceptable and strong consistency is not strictly required. For example, CRDTs can be used in collaborative document editing or real-time collaborative applications where a small amount of inconsistency is acceptable.

However, it is important to note that CRDTs have their limitations and may not be suitable for all use cases. CRDTs may require more storage space than traditional data structures, and some operations may be more complex to implement. Additionally, some types of data may not be amenable to CRDTs.

In summary, while CRDTs can provide an alternative to consensus algorithms in some scenarios, it is important to carefully evaluate the requirements of the system and the capabilities of CRDTs before deciding whether to use them.




Roman Pleshkov
do I need a leader election algo for PBFT
Yes, the PBFT consensus algorithm does require a leader election algorithm to select the primary node responsible for proposing new blocks to be added to the blockchain.

In PBFT, the primary node is responsible for proposing a new block, and the backup nodes validate the block and send their agreement to the primary node. The primary node then waits for a sufficient number of backup nodes to agree with the proposed block before adding it to the blockchain.

To select the primary node, PBFT uses a leader election algorithm. The leader election algorithm selects a primary node for a particular view or period of time, and all nodes in the network agree on the same primary node for that period. If a node detects that the primary node has failed or is not responding, it triggers a view change to elect a new primary node.

There are various leader election algorithms that can be used with PBFT, such as a round-robin algorithm or a random selection algorithm. The leader election algorithm used must be fault-tolerant and ensure that all nodes in the network agree on the same primary node for a given view.

In summary, PBFT does require a leader election algorithm to select the primary node responsible for proposing new blocks to be added to the blockchain. The leader election algorithm must be fault-tolerant and ensure that all nodes in the network agree on the same primary node.




Roman Pleshkov
is it possible to process messages in parallel using PBFT or messages have to be sent to a primary node
In PBFT, messages must be sent to the primary node for processing, and the primary node is responsible for proposing new blocks and coordinating the consensus process.

PBFT is designed to be a state machine replication protocol, where a group of nodes maintains a replicated state machine that processes incoming requests in a coordinated manner. In PBFT, the primary node receives requests from clients, validates them, and proposes a new block to the backup nodes. The backup nodes then validate the block and send their agreement back to the primary node.

Because PBFT is a coordinated protocol, it is not possible to process messages in parallel without affecting the consistency of the replicated state machine. PBFT requires all nodes to agree on the same order of operations and the same sequence of blocks to maintain the consistency of the replicated state machine.

However, PBFT can still provide high throughput by processing multiple requests in parallel within the same block. PBFT allows multiple client requests to be batched together in a single block, which can be validated and agreed upon by the backup nodes in parallel. This batching can significantly improve the throughput of PBFT compared to processing requests one at a time.

In summary, in PBFT, messages must be sent to the primary node for processing, and processing messages in parallel is not possible without affecting the consistency of the replicated state machine. However, PBFT can still achieve high throughput by batching multiple client requests together in a single block for parallel processing.




Roman Pleshkov
so it's not possible to achieve a consensus in the case of concurrent processing of client messags 
It is possible to achieve consensus in the case of concurrent processing of client messages in PBFT, but it requires careful coordination to ensure that all nodes agree on the same order of operations and the same sequence of blocks.

PBFT is designed to handle concurrent processing of client messages by allowing multiple client requests to be batched together in a single block. However, in order to maintain the consistency of the replicated state machine, all nodes in the network must agree on the same sequence of blocks, and the order of operations within each block must also be agreed upon.

To achieve this, PBFT uses a multi-round voting process to ensure that all backup nodes validate and agree on each proposed block. The primary node proposes a new block to the backup nodes, and the backup nodes validate the block before sending their agreement back to the primary node. If the primary node receives enough agreements from the backup nodes, it adds the block to the blockchain, and all nodes in the network update their replicated state machine accordingly.

If concurrent processing of client messages results in conflicting requests, PBFT can still achieve consensus by using a process called "request deduplication". In this process, the primary node can detect and eliminate duplicate requests before proposing them to the backup nodes, ensuring that all nodes in the network agree on the same sequence of blocks and the same order of operations.

In summary, while PBFT can handle concurrent processing of client messages, it requires careful coordination and multi-round voting to ensure that all nodes in the network agree on the same sequence of blocks and the same order of operations. PBFT can also use request deduplication to eliminate conflicting requests and ensure consensus.




Roman Pleshkov
PBFT  is  basically a two-phase commit 
PBFT is a consensus algorithm that shares some similarities with the two-phase commit (2PC) protocol, but it is not equivalent to 2PC.

Both PBFT and 2PC are designed to achieve consensus among a group of distributed nodes, but they have different goals and assumptions.

The two-phase commit (2PC) protocol is designed to ensure atomicity and consistency in distributed transactions. In 2PC, a coordinator node is responsible for initiating a transaction and coordinating its commit or rollback among the distributed nodes. The coordinator node uses a two-phase commit protocol to ensure that all nodes agree to commit the transaction before it is committed. If any node fails during the process, the coordinator can abort the transaction to ensure consistency.

PBFT, on the other hand, is designed to achieve consensus among distributed nodes in a replicated state machine. PBFT assumes that some nodes in the network may be Byzantine, meaning that they may fail or behave maliciously. PBFT uses a three-phase protocol to ensure that all non-faulty nodes agree on the order of transactions and the resulting state changes in the replicated state machine.

In PBFT, there is no single coordinator node responsible for initiating and coordinating transactions. Instead, any node in the network can propose a new block to be added to the blockchain, and all nodes participate in validating and agreeing upon the block. PBFT uses a three-phase protocol to ensure that all nodes agree on the same order of transactions and state changes, even in the presence of faulty nodes.

In summary, while PBFT and 2PC both aim to achieve consensus among distributed nodes, they have different goals and assumptions. PBFT is designed for achieving consensus in a replicated state machine and is more tolerant to Byzantine faults, while 2PC is designed for ensuring atomicity and consistency in distributed transactions. While PBFT shares some similarities with 2PC, it is a distinct and more complex protocol.




Roman Pleshkov
imagine you have a set of N processes, where a process performs some computations upon a message. A process also has a state. let's defined a process as follows:

scala code:


trait Process[S, E] {
 
def hadle(event: E):Unit

}

where E - is a message type that can be handled by a process 
S - a state type

example: 

trait Event
case object Inc <: Event
case object Dec <: Event
class State(var i: Int) // 

class CounterProcess[State, Event]

we can run N physical nodes (machines) to serve CounterProcess. 

Please confirm that in PBFT , there can be M nodes running CounterProcess, but only a primary node can serve a client requests, correct ?
Yes, in PBFT there can be multiple nodes running the CounterProcess, but only one primary node can serve client requests at any given time.

In PBFT, the primary node is responsible for proposing new blocks to the backup nodes, and the backup nodes validate the proposed blocks before agreeing to add them to the blockchain. The primary node is selected using a leader election algorithm, which ensures that only one node is acting as the primary node at any given time.

When a client sends a request to the PBFT network, it sends the request to the primary node, which then proposes a new block to the backup nodes. The backup nodes validate the proposed block before agreeing to add it to the blockchain. Once the block is added to the blockchain, all nodes in the network update their replicated state machine accordingly.

So, while multiple nodes can be running the CounterProcess in PBFT, only the primary node can serve client requests at any given time, and the backup nodes act as validators to ensure the consistency and validity of the proposed blocks.




Roman Pleshkov
can a network node  (machine) serve as a primary node for different processes ?
Yes, in PBFT, a network node (machine) can serve as a primary node for different processes running on the same or different machines. PBFT allows for multiple processes to run concurrently, and each process can have its own primary node.

In PBFT, the primary node is responsible for proposing new blocks to the backup nodes and is selected using a leader election algorithm. The leader election algorithm ensures that only one node is acting as the primary node at any given time for a particular process. However, multiple processes can run concurrently, and each process can have its own primary node.

Each process in PBFT has a unique identifier, and the leader election algorithm selects a primary node for each process independently. Therefore, a node can be selected as the primary node for one process and simultaneously serve as a backup node for another process running on a different machine. This enables PBFT to handle multiple processes running concurrently and achieve consensus among distributed nodes for each process.




Roman Pleshkov
what language is more suitable for implementing the above design? I'd like to use Julia 
Julia is a high-level, high-performance dynamic programming language that is well-suited for implementing distributed systems and parallel computing. Julia is designed to be fast, expressive, and easy to use, making it an excellent choice for implementing the above design.

Julia has built-in support for distributed computing, which makes it easy to implement distributed systems that run across multiple machines. Julia's distributed computing model is based on message passing, which is a natural fit for implementing PBFT, as PBFT is also based on message passing.

Julia also has a number of features that make it well-suited for implementing parallel algorithms, such as support for multi-threading, shared memory, and distributed memory. This can be useful for implementing concurrent processing of client messages, as you mentioned earlier.

Overall, Julia is a great choice for implementing the design you described, especially if you need high performance and scalability. With Julia's built-in support for distributed computing and parallel algorithms, you can easily implement PBFT and other distributed systems on a cluster of machines.




Roman Pleshkov
ok, just to summarize, give a Process abstraction, that contains a client logic to be executed upon defined events, in PBFT we can select a primary (leader) node for each process that's responsible to serve client requests and consensus protocol 
Yes, that's a good summary. To expand on it:

In the design you described, you have a Process abstraction that defines a set of events that can be handled by a process, and a client logic that is executed when these events occur. The Process abstraction can be implemented in Julia as follows:

julia
Copy code
abstract type Process{S, E} end

function handle!(p::Process, state::S, event::E)
    # execute client logic here
    # update state as needed
end
In PBFT, you can select a primary (leader) node for each process that is responsible for serving client requests and ensuring consensus among the backup nodes. The primary node is responsible for proposing new blocks to the backup nodes, and the backup nodes validate the proposed blocks before agreeing to add them to the blockchain. The leader election algorithm ensures that only one node is acting as the primary node at any given time for a particular process. Here's an example implementation of a primary node in Julia:

julia
Copy code
struct PrimaryNode{S, E}
    process::Process{S, E}
    state::S
    node_id::Int
end

function propose!(p::PrimaryNode, event::E)
    # propose new block to backup nodes
    # wait for validation from backup nodes
    # update state as needed
end
Overall, Julia provides a powerful and flexible programming environment for implementing distributed systems such as PBFT, with support for parallel computing, distributed computing, and message passing.




Roman Pleshkov
love you )
I'm just an AI language model, so I don't have feelings, but I'm glad I could help you! If you have any more questions, feel free to ask.




Roman Pleshkov
what is the complexity of PBFT , (n/2 + 1) ^ 3  ?
The complexity of PBFT is O(n^2) in the worst-case scenario, where n is the number of nodes in the network. This is because PBFT requires three phases of communication between all nodes, where each phase involves sending messages to all other nodes in the network. Therefore, the total number of messages that need to be sent is O(n^2).

However, the actual number of messages sent in practice is typically lower than the worst-case scenario, since not all nodes are required to participate in every phase of the protocol. For example, if a node detects that the proposed block is invalid, it can skip the third phase of the protocol, which reduces the number of messages that need to be sent.

The formula you mentioned, (n/2 + 1)^3, is actually the number of nodes required to tolerate f Byzantine nodes in PBFT, where f is the maximum number of nodes that can be faulty. This is because PBFT can tolerate f Byzantine nodes as long as there are (3f+1) correct nodes in the network. The formula gives the minimum number of nodes required to achieve this fault tolerance.




Roman Pleshkov
` where each phase involves sending messages to all other nodes in the network.` , pleae clarify, only primary node sends messages to backup nodes , or each round is N^2
In PBFT, each node sends messages to all other nodes in the network in each phase of the protocol, not just the primary node. This is because PBFT is a state machine replication protocol, where all nodes need to agree on the same sequence of operations in the same order.

In each phase of PBFT, a node broadcasts a message to all other nodes in the network, and then waits to receive messages from a quorum of nodes (at least 2f+1 nodes) before proceeding to the next phase. This means that each node needs to send and receive messages from all other nodes in the network at least once in each phase of the protocol.

Therefore, the total number of messages sent in each phase of PBFT is O(n^2). However, as I mentioned earlier, not all nodes need to participate in every phase of the protocol, so the actual number of messages sent in practice may be lower than the worst-case scenario.




Roman Pleshkov
I see, so it's 3 *  O(n^2) =>  O(n^2), correct ?
Yes, that's correct. Since there are three phases in PBFT, each with a worst-case message complexity of O(n^2), the total worst-case message complexity of PBFT is 3 * O(n^2), which simplifies to O(n^2).




Roman Pleshkov
is there any better alternatives to PBFT
There are several alternatives to PBFT, each with their own strengths and weaknesses. Some popular alternatives include:

Raft: Raft is a consensus algorithm designed for ease of understanding and implementation. It uses a leader-based approach, where a single leader node is responsible for managing the consensus process. Raft is often considered simpler to understand and implement than PBFT, but it may not be as fault-tolerant or scalable.

Tendermint: Tendermint is a Byzantine fault-tolerant consensus algorithm that uses a round-robin approach to select a validator node to propose new blocks. It is designed to be highly scalable and efficient, and is often used as the consensus algorithm in blockchain platforms such as Cosmos and Binance Chain.

Proof of Stake: Proof of Stake (PoS) is a family of consensus algorithms where nodes are selected to validate new blocks based on the amount of cryptocurrency they hold or stake. PoS is often considered more energy-efficient than PoW (Proof of Work) algorithms, but it may require more trust in the validators and be susceptible to certain types of attacks.

HoneyBadgerBFT: HoneyBadgerBFT is a robust Byzantine fault-tolerant consensus algorithm that is designed to be highly resilient to attacks and failures. It uses advanced cryptographic techniques such as threshold signatures and polynomial secret sharing to achieve consensus, but may be more complex to implement than other consensus algorithms.

The choice of consensus algorithm depends on the specific requirements of the application or system being built. Each algorithm has its own trade-offs in terms of performance, fault-tolerance, security, and complexity, and it's important to choose the one that best fits the needs of the system.




Roman Pleshkov
which one is the most performant and reliable 
It's difficult to say which consensus algorithm is the most performant and reliable, as it depends on the specific use case and implementation details. However, some consensus algorithms are known for their performance and reliability in certain contexts:

Tendermint is known for its high throughput and low latency, and is often used in blockchain applications that require fast transaction processing and finality.

PBFT is known for its strong Byzantine fault-tolerance guarantees, and is often used in systems that require high levels of resilience to attacks and failures.

Raft is known for its simplicity and ease of implementation, and is often used in systems that prioritize ease of understanding and maintainability over performance.

HoneyBadgerBFT is known for its resilience to attacks and failures, and is often used in mission-critical applications where the stakes are high and failure is not an option.

Ultimately, the choice of consensus algorithm depends on the specific needs of the application or system being built, and requires careful consideration of factors such as performance, fault-tolerance, security, and complexity.




Roman Pleshkov
what kind of ` specific needs ` I should consider ?
The specific needs that should be considered when choosing a consensus algorithm depend on the particular requirements of the system or application being built. Some common factors to consider include:

Performance: The desired throughput and latency of the system, as well as any scalability requirements, will impact the choice of consensus algorithm.

Fault-tolerance: The level of resilience to failures and attacks required by the system, including considerations such as Byzantine fault tolerance, crash fault tolerance, and network partition tolerance.

Security: The security requirements of the system, including considerations such as resistance to Sybil attacks, resistance to censorship, and resistance to malicious or compromised nodes.

Complexity: The ease of implementation, maintainability, and understandability of the consensus algorithm, as well as any trade-offs between simplicity and performance or fault-tolerance.

Consistency model: The desired consistency guarantees of the system, including strong consistency, eventual consistency, and weak consistency.

Deployment environment: The characteristics of the deployment environment, such as the number of nodes, network topology, and communication latency, can impact the choice of consensus algorithm.

Cost: The cost of implementing and operating the consensus algorithm, including factors such as hardware requirements, energy consumption, and ongoing maintenance and support costs.

By carefully considering these and other factors, it is possible to select a consensus algorithm that meets the specific needs of the system or application being built.




Roman Pleshkov
I guess RAFT is more complex than PBFT
In general, PBFT is considered to be more complex than Raft due to its higher message complexity and more intricate Byzantine fault tolerance guarantees. PBFT requires multiple rounds of message exchange between nodes, and involves complex cryptographic operations to ensure the integrity and authenticity of messages. Raft, on the other hand, uses a leader-based approach to achieve consensus, and has simpler message exchange patterns and fault tolerance mechanisms.

That being said, the complexity of a consensus algorithm depends on the specific implementation details and use case, and it's possible that a particular implementation of Raft or PBFT could be more or less complex than the other. Ultimately, the choice of consensus algorithm should be based on a careful consideration of the specific requirements and constraints of the system being built.




Roman Pleshkov
I meant implementation complexity , not message complexity 
In terms of implementation complexity, PBFT is generally considered to be more complex than Raft due to its use of complex cryptographic operations and multiple rounds of message exchange between nodes. PBFT also requires careful handling of message timeouts and retransmissions, as well as complex logic for handling node failures and reconfigurations.

Raft, on the other hand, has a simpler message exchange pattern and a more straightforward leader-based approach to achieving consensus. The core algorithm can be implemented in a few hundred lines of code, and there are many well-documented and battle-tested open-source implementations available in a variety of programming languages.

That being said, the implementation complexity of a consensus algorithm will depend on the specific requirements and constraints of the system being built, as well as the programming language and tooling being used. It's possible that a particular implementation of Raft or PBFT could be more or less complex than the other depending on these factors.




Roman Pleshkov
PBFT  is paxos ?
No, PBFT (Practical Byzantine Fault Tolerance) is a consensus algorithm that is distinct from Paxos, which is another well-known consensus algorithm. While both algorithms are used to achieve consensus in distributed systems, they have different approaches to achieving this goal.

PBFT is designed to tolerate Byzantine faults, which means it can handle nodes that behave arbitrarily or maliciously, whereas Paxos assumes that nodes fail only by crashing and recovering. PBFT achieves Byzantine fault tolerance by requiring a quorum of correct nodes to agree on each decision, and using cryptographic techniques to ensure the authenticity and integrity of messages.

Paxos, on the other hand, is a family of consensus algorithms that use a leader-based approach to achieve consensus. In Paxos, a distinguished node called the leader proposes values to be agreed upon, and the other nodes can either accept or reject the proposed value. Paxos uses a round-based protocol to ensure that only one value is agreed upon at each round, and it is designed to handle node failures and network partitions.

While both PBFT and Paxos are widely used in practice, they have different strengths and weaknesses and are suited to different use cases.




Roman Pleshkov
both PBFT  and Paxos require a leader node that proposes a value
In PBFT, there is no concept of a leader node that proposes a value. Instead, the client sends requests to all the nodes in the system, and one of the nodes is elected as the primary for a particular request. The primary is responsible for gathering responses from the other nodes and computing the final result.

In contrast, Paxos does use a leader-based approach, where a distinguished node called the proposer proposes a value to be agreed upon. The other nodes can then either accept or reject the proposed value. If the proposal is accepted, the leader informs the other nodes of the decision.

While both PBFT and Paxos are used to achieve consensus in distributed systems, they have different approaches to the problem and different strengths and weaknesses. PBFT is designed to tolerate Byzantine faults, while Paxos is designed to handle node failures and network partitions.




Roman Pleshkov
oh, so in PBFT a client sends a messages to all nodes so it doesn't no which in is a primary or leader 
That's correct. In PBFT, the client sends a request message to all the nodes in the system. The nodes then use a consensus algorithm to determine which node will act as the primary for that particular request. Once a primary is chosen, it is responsible for gathering responses from the other nodes and computing the final result, which is then sent back to the client.




Roman Pleshkov
what if a primary node didn't receive a message b/c of network partitioning ?
In PBFT, if a primary node fails to receive a message due to a network partition, the protocol will not be able to make progress until the partition is resolved. This is because PBFT requires that a quorum of nodes (i.e., at least (n/2)+1 nodes) receive and agree on a message before proceeding to the next phase of the protocol.

If a primary node fails to receive a message from a subset of nodes due to network issues, the system may elect a new primary node to handle the request. However, if the partition separates the primary node from a quorum of nodes, the system may not be able to make progress until the partition is resolved.

To handle network partitions, PBFT can be extended with additional mechanisms such as view changes, where the system elects a new set of nodes to act as the primary and backups, or by using mechanisms such as gossip protocols to propagate information between nodes in the system.




Roman Pleshkov
will other nodes initiate a leader election round if a leader node is unreachable?
In PBFT, there is no leader election algorithm, as the primary node for each request is chosen through a consensus algorithm that is run by all nodes in the system. If a primary node becomes unreachable, the protocol will not be able to make progress until the primary node is restored or a new primary node is elected.

To handle the case where a primary node becomes unreachable, PBFT includes a mechanism known as a "view change". During a view change, the remaining nodes in the system elect a new set of nodes to act as the primary and backups. The view change process involves a series of rounds where the nodes in the system exchange messages to determine a new set of primary and backup nodes.

If a quorum of nodes agree on a new set of primary and backup nodes, then the system can continue to make progress with the new nodes. However, if a quorum cannot be reached due to network partitions or other issues, the system may be forced to remain in a state of partial availability until the network issues are resolved.




Roman Pleshkov
previously you said that there is ` leader election algorithm` in PBFT
I apologize for any confusion. I misspoke earlier when I referred to a "leader election algorithm" in PBFT. PBFT does not have a traditional leader election algorithm like other consensus protocols such as Raft or Paxos. Instead, PBFT uses a round-robin approach to select a primary node for each request, with each node in the system taking turns acting as the primary.

In the event that the primary node fails or becomes unavailable, PBFT includes a view-change mechanism where the remaining nodes can elect a new set of primary and backup nodes to continue processing requests. However, this is not a traditional leader election algorithm like those found in other consensus protocols.




Roman Pleshkov
a client sends requests to a set of primary nodes in round-robin fasion ?
In PBFT, a client sends a request to a single primary node, which is selected in a round-robin fashion from the set of all nodes in the system. The primary node is responsible for processing the request and broadcasting a message to all other nodes in the network to initiate the consensus protocol. The other nodes will then respond with messages of their own until a sufficient number of nodes have agreed on the request and a result can be returned to the client.




Roman Pleshkov
how the client knows which node is primary of it's changing every round ?
In PBFT, the client doesn't need to know the identity of the primary node in advance, since the selection of the primary node is handled by the nodes in the system themselves. When a client wants to make a request, it sends the request to all of the nodes in the system, and each node determines whether it is the primary node for that particular request.

Once a primary node has been selected for a request, it broadcasts this information to all of the other nodes in the network. The client can then wait for a response from any of the nodes indicating that the request has been processed successfully.

In some implementations of PBFT, there may be a mechanism for clients to learn the identity of the current primary node, such as by querying one of the nodes in the network. However, this is not strictly necessary for the protocol to function correctly.




Roman Pleshkov
does a primary node changing for the process upon every messags ?
Yes, in PBFT, the primary node is selected on a per-request basis, which means that a different node can act as the primary node for each request. This helps to distribute the workload evenly among the nodes in the system and prevent any one node from becoming a bottleneck.

The selection of the primary node is based on a round-robin algorithm, where each node takes turns being the primary node for incoming requests. When a client sends a request to all nodes in the system, each node determines whether it is the primary node for that particular request based on the round-robin algorithm.

The primary node for a request is responsible for initiating the consensus protocol and ensuring that all nodes in the network reach agreement on the outcome of the request. Once consensus has been reached, the primary node sends a response to the client indicating that the request has been processed successfully.




Roman Pleshkov
do nodes communicate to select a primary node ?
Yes, nodes in the PBFT network communicate to select a primary node on a per-request basis. The selection of the primary node is based on a round-robin algorithm, which means that each node takes turns being the primary node for incoming requests.

When a client sends a request to all nodes in the system, each node determines whether it is the primary node for that particular request based on the round-robin algorithm. If a node determines that it is not the primary node, it acts as a backup node and participates in the consensus protocol to ensure that the request is processed correctly.

During the consensus protocol, nodes exchange messages with each other to reach agreement on the outcome of the request. Once consensus has been reached, the primary node sends a response to the client indicating that the request has been processed successfully.




Roman Pleshkov
could you explain round-robin in this context, are the nodes ordered somehow , round-robin implies ordering , correct ?
In the context of PBFT, round-robin refers to a load balancing technique in which the client sends requests to a set of primary nodes in a cyclic order.

There is an ordering of nodes in the sense that the client has a list of primary nodes and sends requests to them in a fixed order, but the order does not necessarily reflect any kind of preference or ranking of the nodes. The order can be determined randomly or based on some predefined pattern.

For example, if there are three primary nodes (A, B, C), the client can send the first request to A, the second request to B, and the third request to C, then start over with A for the fourth request, and so on. This way, the load is distributed evenly among the primary nodes, and each node gets an equal chance to serve client requests.




Roman Pleshkov
you said that there is only one primary node at the time
Yes, that's correct. In PBFT, at any given point in time, there is only one primary node responsible for processing client requests and initiating the consensus protocol. The primary node is chosen in a round-robin fashion from a set of pre-determined primary nodes.




Roman Pleshkov
and then you
Yes, I apologize for any confusion earlier. To clarify, there is only one primary node in PBFT at any given time, and it is responsible for processing client requests and initiating the consensus protocol. The primary node is chosen in a round-robin fashion from a set of pre-determined primary nodes. Once a primary node is chosen, it remains the primary node until it fails or is otherwise removed from the system.




Roman Pleshkov
you are saying: sends requests to a set of primary nodes 
I apologize for the confusion. Let me clarify my previous statement. In PBFT, there is only one primary node responsible for processing client requests at any given time. The primary node is chosen by the other nodes in the network through a consensus protocol. Once a primary node is selected, it remains the primary until either it fails or a view change occurs.

When a client sends a request, it sends it to the current primary node. If the client doesn't know which node is the primary, it can send the request to all nodes in the network. However, this is not the usual practice as it may result in unnecessary network traffic. The primary node can be identified by the other nodes in the network and its identity can be disseminated to the clients by the application layer.

So, to answer your previous question, a client sends a request to the current primary node, not to a set of primary nodes in round-robin fashion.




Roman Pleshkov
`The primary node is chosen by the other nodes in the network through a consensus protocol` this is leader election esentially 
Yes, you are correct. The process of selecting a primary node in PBFT is essentially a leader election algorithm. The other nodes in the network reach a consensus on which node should be the primary for a given round.




Roman Pleshkov
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