) Dahlia Malkhi Michael K. Reiter AT&T Labs Research, Florham Park, NJ, USA fdalia,reiterg@research.att.com Abstract Phalanx is a software system for building a persistent, survivable data repository that supports shared data abstractions (e.g., variables, mutual exclusion) for clients. Phalanx implements data abstractions that ensure useful properties without trusting the servers supporting these abstractions or the clients accessing them, i.e., Phalanx can survive even the arbitrarily malicious corruption of clients and (some number of) servers. At the core of the system are survivable replication techniques that enable efficient scaling to hundreds of Phalanx servers. In this paper we describe the implementation of some of the data abstractions provided by Phalanx, discuss their ability to scale to large systems, and describe an example application. 1. Introduction In this paper we introduce Phalanx, a software system for building persistent services that support shared data ab...

We present a quorum-based protocol for a Byzantine fault-tolerant storage system that can dynamically adapt its failure threshold and server count, allowing the storage system to be reconfigured in anticipation of possible failures or to replace servers as desired. Our protocol provides confirmable wait-free atomic semantics while tolerating Byzantine failures from the clients or servers. The system can grow without bound to tolerate as many failures as desired. Finally, the protocol is optimal and fast: only the minimal number of servers—3f + 1 — is needed to tolerate any f failures and, in the common case, reads require only one message round-trip. 1

Phalanx is a software system for building a persistent, survivable data repository that supports shared data abstractions (e.g., variables, mutual exclusion) for clients. Phalanx implements data abstractions that ensure useful properties without trusting the servers supporting these abstractions or the clients accessing them, i.e., Phalanx can survive even the arbitrarily malicious corruption of clients and (some number of) servers. At the core of the system are survivable replication techniques that enable efficient scaling to hundreds of Phalanx servers. In this paper we describe the implementation of some of the data abstractions provided by Phalanx, discuss their ability to scale to large systems, and describe an example application.

) Dahlia Malkhi Michael K. Reiter AT&T Labs-Research, Florham Park, NJ, USA fdalia,reiterg@research.att.com Abstract Reaching consensus among multiple processes in a distributed system is fundamental to coordinating distributed actions. In this paper we present a new approach to building survivable consensus objects in a system consisting of a (possibly large) collection of persistent object servers and a transient population of clients. Our consensus object implementation requires minimal support from servers, but at the same time enables clients to reach coordinated decisions despite the arbitrary (Byzantine) failure of any number of clients and up to a threshold number of servers. 1. Introduction A consensus object is a shared object to which a client can propose a value and receive a value in return. The consensus object returns the same value to each client, and the returned value is one proposed by some client. Applications of consensus objects to achieving distributed coor...

Dahlia Malkhi Michael K. Reiter AT&T Labs Research, Florham Park, NJ, USA fdalia,reiterg@research.att.com Abstract Phalanx is a software system for building a persistent, survivable data repository that supports shared data abstractions (e.g., variables, mutual exclusion) for clients. Phalanx implements data abstractions that ensure useful properties without trusting the servers supporting these abstractions or the clients accessing them, i.e., Phalanx can survive even the arbitrarily malicious corruption of clients and (some number of) servers. At the core of the system are survivable replication techniques that enable efficient scaling to hundreds of Phalanx servers. In this paper we describe the implementation of some of the data abstractions provided by Phalanx, discuss their ability to scale to large systems, and describe an example application.

We present a framework for transforming several quorum-based protocols so that they can dynamically adapt their failure threshold and server count, allowing them to be reconfigured in anticipation of possible failures or to replace servers as desired. We demonstrate this transformation on the dissemination quorum protocol. The resulting system provides confirmable wait-free atomic semantics while tolerating Byzantine failures from the clients or servers. The system can grow without bound to tolerate as many failures as desired. Finally, the protocol is optimal and fast: only the minimal number of servers ---3f 1--- is needed to tolerate any f failures and, in the common case, reads require only one message round-trip.

Reaching consensus among multiple processes in a distributed system is fundamental to coordinating distributed actions. In this paper we present a new approach to building survivable consensus objects in a system consisting of a (possibly large) collection of persistent object servers and a transient population of clients. Our consensus object implementation requires minimal support from servers, but at the same time enables clients to reach coordinated decisions despite the arbitrary (Byzantine) failure of any number of clients and up to a threshold number of servers.