Anonymous Obstruction-free (n,k)(n,k)-Set Agreement with n−k+1n-k+1 Atomic Read/Write Registers

The $k$-set agreement problem is a generalization of the consensus problem. Namely, assuming each process proposes a value, each non-faulty process has to decide a value such that each decided value was proposed, and no more than $k$ different values are decided. This is a hard problem in the sense that it cannot be solved in asynchronous systems as soon as $k$ or more processes may crash. One way to circumvent this impossibility consists in weakening its termination property, requiring that a process terminates (decides) only if it executes alone during a long enough period. This is the well-known obstruction-freedom progress condition. Considering a system of $n$ {\it anonymous asynchronous} processes, which communicate through atomic {\it read/write registers only}, and where {\it any number of processes may crash}, this paper addresses and solves the challenging open problem of designing an obstruction-free $k$-set agreement algorithm with $(n-k+1)$ atomic registers only. From a shared memory cost point of view, this algorithm is the best algorithm known so far, thereby establishing a new upper bound on the number of registers needed to solve the problem (its gain is $(n-k)$ with respect to the previous upper bound). The algorithm is then extended to address the repeated version of $(n,k)$-set agreement. As it is optimal in the number of atomic read/write registers, this algorithm closes the gap on previously established lower/upper bounds for both the anonymous and non-anonymous versions of the repeated $(n,k)$-set agreement problem. Finally, for 1 \leq x\leq k \textless{} n, a generalization suited to $x$-obstruction-freedom is also described, which requires $(n-k+x)$ atomic registers only

Leaderless State-Machine Replication: Specification, Properties, Limits

Modern Internet services commonly replicate critical data across several geographical locations using state-machine replication (SMR). Due to their reliance on a leader replica, classical SMR protocols offer limited scalability and availability in this setting. To solve this problem, recent protocols follow instead a leaderless approach, in which each replica is able to make progress using a quorum of its peers. In this paper, we study this new emerging class of SMR protocols and states some of their limits. We first propose a framework that captures the essence of leaderless state-machine replication (Leaderless SMR). Then, we introduce a set of desirable properties for these protocols: (R)eliability, (O)ptimal (L)atency and (L)oad Balancing. We show that protocols matching all of the ROLL properties are subject to a trade-off between performance and reliability. We also establish a lower bound on the message delay to execute a command in protocols optimal for the ROLL properties. This lower bound explains the persistent chaining effect observed in experimental results

The Weakest Failure Detector for Genuine Atomic Multicast

Atomic broadcast is a group communication primitive to order messages across a set of distributed processes. Atomic multicast is its natural generalization where each message m is addressed to dst(m), a subset of the processes called its destination group. A solution to atomic multicast is genuine when a process takes steps only if a message is addressed to it. Genuine solutions are the ones used in practice because they have better performance. Let ? be all the destination groups and ? be the cyclic families in it, that is the subsets of ? whose intersection graph is hamiltonian. This paper establishes that the weakest failure detector to solve genuine atomic multicast is ? = (?_{g,h ? ?} ?_{g ? h}) ? (?_{g ? ?} ?_g) ? ?, where ?_P and ?_P are the quorum and leader failure detectors restricted to the processes in P, and ? is a new failure detector that informs the processes in a cyclic family f ? ? when f is faulty. We also study two classical variations of atomic multicast. The first variation requires that message delivery follows the real-time order. In this case, ? must be strengthened with 1^{g ? h}, the indicator failure detector that informs each process in g ? h when g ? h is faulty. The second variation requires a message to be delivered when the destination group runs in isolation. We prove that its weakest failure detector is at least ? ? (?_{g, h ? ?} ?_{g ? h}). This value is attained when ? = ?

Fault-Tolerant Partial Replication in Large-Scale Database Systems

We investigate a decentralised approach to committing transactions in a replicated database, under partial replication. Previous protocols either re-execute transactions entirely and/or compute a total order of transactions. In contrast, ours applies update values, and orders only conflicting transactions. It results that transactions execute faster, and distributed databases commit in small committees. Both effects contribute to preserve scalability as the number of databases and transactions increase. Our algorithm ensures serializability, and is live and safe in spite of faults

Comparing Optimistic Database Replication Techniques

International audienceReplication is attractive for scaling databases up, as it does not require costly equipment and it enables fault tolerance. However, as the latency gap between local and remote accesses continues to widen, maintaining consistency between replicas remains a performance and complexity bottleneck. Optimistic replication (OR) addresses these problems. In OR, a database tentatively executes transactions against its local cache; databases reconcile a posteriori to agree on a common schedule of committed transactions. We present three OR protocols based on the deferred update scheme. The first two are representative of the state the art. The third is new; we describe it in detail. As all three protocols are expressed within a common formal framework, we are able to compare them, to identify similarities and differences, and to introduce common variants. We show that our protocol behaves better than the other two, with respect to latency, message cost and abort rate