PBFT Sample Clauses

PBFT. ‌ Most previous byzantine fault tolerance xxxxxxxxxx [00, 30] assume synchrony for their systems to have safety, a property later described. However, malicious users might delay communication between non- faulty nodes and lead the system to rule them out as faulty: a Denial of Service (DoS) attack [31]. Thus, the Practical Byzantine Fault Tolerance (PBFT) paper [26] describes a state machine replication consensus algorithm that functions correctly despite byzantine faults in an asynchronous context. The PBFT algorithm aims to provide two main properties in a byzantine context: safety and liveness [32]. The former property means that all non-faulty replicas agree on a group of requests, while the latter means that clients will eventually receive a reply to their request (e.g., read/write to a file system). However, these properties assume that n−1 replicas are faulty, where n is the total number of replicas available. Note that while this algorithm does not rely on synchrony for safety, it must rely on it for liveness to ensure termination and make asynchronous consensus possible. This means that if there is a delay on the network when receiving a request, it must end in a finite time t. Furthermore, given that this is an asynchronous context, PBFT is optimally resilient since it uses the minimum number of replicas: 3f + 1, with f being the faulty replicas. This number of replicas is necessary because f replicas might not respond due to an infinite delay and another f might be byzantine and, for instance, give a wrong response on purpose. Thus, the system must have n − 2f > f replicas. Hence, n > 3f replicas. The protocol is implemented using the state machine replication [22] approach: each node has a state machine replica to reach consensus on the client requests, which are executed deterministically. Additionally, the replicas are split into one primary and the rest as backups. All the replicas move through numbered views, which are successive configurations of the system. The algorithm steps can be roughly described as follows: 1) the client sends a request to the primary replica; 2) the primary replica broadcasts the request to backups; 3) all the replicas execute the request and send it back to the client; 4) the client waits for f + 1 replies from different replicas, where f is the number of faulty replicas. The algorithm is further expanded in the following paragraph. Each replica has a message log to append the messages it accepted and a number tha...
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