Scalable Byzantine Reliable Broadcast

Byzantine reliable broadcast is a powerful primitive that allows a set of processes to agree on a message from a designated sender, even if some processes (including the sender) are Byzantine. Existing broadcast protocols for this setting scale poorly, as they typically build on quorum systems with strong intersection guarantees, which results in linear per-process communication and computation complexity. We generalize the Byzantine reliable broadcast abstraction to the probabilistic setting, allowing each of its properties to be violated with a fixed, arbitrarily small probability. We leverage these relaxed guarantees in a protocol where we replace quorums with stochastic samples. Compared to quorums, samples are significantly smaller in size, leading to a more scalable design. We obtain the first Byzantine reliable broadcast protocol with logarithmic per-process communication and computation complexity. We conduct a complete and thorough analysis of our protocol, deriving bounds on the probability of each of its properties being compromised. During our analysis, we introduce a novel general technique that we call adversary decorators. Adversary decorators allow us to make claims about the optimal strategy of the Byzantine adversary without imposing any additional assumptions. We also introduce Threshold Contagion, a model of message propagation through a system with Byzantine processes. To the best of our knowledge, this is the first formal analysis of a probabilistic broadcast protocol in the Byzantine fault model. We show numerically that practically negligible failure probabilities can be achieved with realistic security parameters

Timed Quorum System for Large-Scale and Dynamic Environments

This paper presents Timed Quorum System (TQS), a new quorum system especially suited for large-scale and dynamic systems. TQS requires that two quorums intersect with high probability if they are used in the same small period of time. It proposed an algorithm that implements TQS and that verifies probabilistic atomicity: a consistency criterion that requires each operation to respect atomicity with high probability. This TQS implementation has quorum of size O(\sqrt{nD}) and expected access time of O(log \sqrt{nD}) message delays, where n measures the size of the system and D is a required parameter to handle dynamism

Quantifying Eventual Consistency with PBS

Data replication results in a fundamental trade-off between operation latency and consistency. At the weak end of the spectrum of possible consistency models is eventual consistency, which provides no limit to the staleness of data returned. However, anecdotally, eventual consistency is often “good enough ” for practitioners given its latency and availability benefits. In this work, we explain this phenomenon and demonstrate that, despite their weak guarantees, eventually consistent systems regularly return consistent data while providing lower latency than their strongly consistent counterparts. To quantify the behavior of eventually consistent stores, we introduce Probabilistically Bounded Staleness (PBS), a consistency model that provides expected bounds on data staleness with respect to both versions and wall clock time. We derive a closed-form solution for version-based staleness and model real-time staleness for a large class of quorum replicated, Dynamo-style stores. Using PBS, we measure the trade-off between latency and consistency for partial, non-overlapping quorum systems under Internet production workloads. We quantitatively demonstrate how and why eventually consistent systems frequently return consistent data within tens of milliseconds while offering large latency benefits. 1

Investigating Impact of Quorum Construction on Data Processing in Mobile Ad Hoc Networks

In a mobile ad hoc network (MANET), since mobility of mobile hosts causes frequent network partitioning, consistency management of data operations on replicas becomes a crucial issue. in our previous work, we have defined several consistency levels for MANET applications and designed protocols to achieve these consistency levels. These protocols are mainly based on a dynamic quorum system to cope with network partitioning and node and network failures. in this paper, we further investigate the impact of quorum construction on the system performance through simulation studies. Specifically, we change the number of mobile hosts that replicate data items, and which hosts replicate each data item in the simulations and examine the impact on the system performance in terms of data availability and traffic. © 2010 IEEE

Implementing Atomic Data through Indirect Learning in Dynamic Network

Developing middleware services for dynamic distributed systems, e.g., ad-hoc networks, is a challenging task given that suchservices must deal with communicating devices that may join and leave the system, and fail or experience arbitrary delays. Algorithmsdeveloped for static settings are often not usable in dynamic settings because they rely on (logical) all-to-all connectivityor assume underlying routing protocols, which may be unfeasible in highly dynamic settings. This paper explores the indirectlearning approach to information dissemination within a dynamic distributed data service. The indirect learning scheme is usedto improve the liveness of the atomic read/write object service in the settings with uncertain connectivity. The service is formallyproved to be correct, i.e., the atomicity of the objects is guaranteed in all executions. Conditional analysis of the performanceof the new service is presented. This analysis has the potential of being generalized to other similar dynamic algorithms. Underthe assumption that the network is connected, and assuming reasonable timing conditions, the bounds on the duration of theread/write operations of the new service are calculated. Finally, the paper proposes a deployment strategy where indirect learningleads to an improvement in communication costs relative to a previous solution

SQUARE: Scalable Quorum-Based Atomic Memory with Local Reconfiguration

International audienceInternet applications require more and more resources to satisfy the unpredictable clients needs. Specifically, such applications must ensure quality of service despite bursts of load. Distributed dynamic self-organized systems present an inherent adaptiveness that can face unpredictable bursts of load. Nevertheless quality of service, and more particularly data consistency, remains hardly achievable in such systems since participants (i.e., nodes) can crash, leave, and join the system at arbitrary time. The atomic consistency guarantees that any read operation returns the last written value of a data and is generalizable to data composition. To guarantee atomicity in message-passing model, mutually intersecting sets (a.k.a.quorums) of nodes are used. The solution presented here, namely SQUARE, provides scalability, load-balancing, fault-tolerance, and self-adaptiveness, while ensuring atomic consistency. We specify our solution, prove it correct and analyse it through simulations. \\ Les applications utilisées via internet nécessitent de plus en plus de ressources afin de satisfaire les besoins imprévisibles des clients. De telles applications doivent assurer une certaine qualité de service en dépit des pics de charge. Les systèmes distribués dynamiques capable de s'auto-organiser ont une capacité intrinsèque pour supporter ces pics de charge imprévisibles. Cependant, la qualité de service et plus particulièrement la cohérence des données reste très difficile à assurer dans de tels systèmes. En effet, les participants, ou noeuds, peuvent rejoindre, quitter le système, et tomber en panne de façon arbitraire. La cohérence atomique assure que toute lecture renvoie la dernière valeur écrite et la relation de composition la préserve. Afin de garantir l'atomicité dans un modèle à passage de message, des ensembles de noeuds s'intersectant mutuellement (les quorums) sont utilisés. La solution présentée ici, appelée SQUARE, est exploitable à grande échelle, permet de balancer la charge, tolère les pannes et s'auto-adapte tout en assurant l'atomicité. Nous spécifions la solution, la prouvons correcte et la simulons pour en analyser les performances