Consensus in decentralized systems that asynchronously receive events and which are subject to Byzantine faults is a common problem with many real-life applications. Advances in decentralized systems, such as distributed ledger (i.e., blockchain) technology, has only increased the importance of finding performant and secure solutions to consensus of state machine replication in decentralized systems. YAC is a practical decentralized consensus algorithm, that solves the problems of inefficient message passing and strong leaders that occur in classical Byzantine fault tolerant consensus algorithms. The algorithm is open source and currently is used to provide Byzantine fault tolerant consensus for the Hyperledger Iroha blockchain project. We provide proofs of safety and liveness, as well as empirical results showing that our algorithm can scale to dozens of validating peers.
Zyzzyva @cite_5 extended PBFT, avoiding the expensive three-phase commit protocol, utilizing fast track and actively involving the client into the consensus process. In the best case scenario, the client sends the request to the leader, who is broadcasts it to all other replicas, and the client waits for replies from all the peers. If the client receives 3 @math +1 replies, it commits the transaction(s). In the case when the client receives between 2 @math +1 to 3 @math messages, a regular consensus algorithm is used. The client is a major player, who is responsible for checking the integrity of replicas.
@cite_5
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We present Zyzzyva, a protocol that uses speculation to reduce the cost and simplify the design of Byzantine fault tolerant state machine replication. In Zyzzyva, replicas respond to a client's request without first running an expensive three-phase commit protocol to reach agreement on the order in which the request must be processed. Instead, they optimistically adopt the order proposed by the primary and respond immediately to the client. Replicas can thus become temporarily inconsistent with one another, but clients detect inconsistencies, help correct replicas converge on a single total ordering of requests, and only rely on responses that are consistent with this total order. This approach allows Zyzzyva to reduce replication overheads to near their theoretical minimal. It is well known that causal consistency is more expensive to implement than eventual consistency due to its requirement of dependency tracking and checking for causality. To close the performance gap between the two consistency models, we propose a new protocol that implements causal consistency for both partitioned and replicated data stores. Our protocol trades the visibility latency of updates across different client sessions for higher throughput. An update, either from a local client or a remote replica, is only visible to other clients after it is replicated by all replicas. As a result, a read operation never introduces dependencies to its client session. Only update operations introduce dependencies. By exploiting the transitive property of causality and total order update propagation, an update always has at most one dependency. By reducing the number of tracked dependencies and the number of messages for dependency checking down to one, we believe our protocol can provide causal consistency with similar cost to eventual consistency. A group of mutually trusting clients outsources a computation service to a remote server, which they do not fully trust and that may be subject to attacks. The clients do not communicate with each other and would like to verify the correctness of the remote computation and the consistency of the server's responses. This paper first presents the Commutative-Operation verification Protocol (COP) that ensures linearizability when the server is correct and preserves fork-linearizability in any other case. All clients that observe each other's operations are consistent, in the sense that their own operations and those operations of other clients that they see are linearizable. Second, this work extends COP through authenticated data structures to Authenticated COP, which allows consistency verification of outsourced services whose state is kept only remotely, by the server. This yields the first fork-linearizable consistency verification protocol for generic outsourced services that (1) relieves clients from storing the state, (2) supports wait-free client operations, and (3) handles sequences of arbitrary commutative operations. This paper sketches the design of PAST, a large-scale, Internet-based, global storage utility that provides scalability, high availability, persistence and security. PAST is a peer-to-peer Internet application and is entirely self-organizing. PAST nodes serve as access points for clients, participate in the routing of client requests, and contribute storage to the system. Nodes are not trusted, they may join the system at any time and may silently leave the system without warning. Yet, the system is able to provide strong assurances, efficient storage access, load balancing and scalability. Among the most interesting aspects of PAST's design are (1) the Pastry location and routing scheme, which reliably and efficiently routes client requests among the PAST nodes, has good network locality properties and automatically resolves node failures and node additions; (2) the use of randomization to ensure diversity in the set of nodes that store a file's replicas and to provide load balancing; and (3) the optional use of smartcards, which are held by each PAST user and issued by a third party called a broker The smartcards support a quota system that balances supply and demand of storage in the system.