CATS: linearizability and partition tolerance in scalable and self-organizing key-value stores

Distributed key-value stores provide scalable, fault-tolerant, and self-organizing storage services, but fall short of guaranteeing linearizable consistency in partially synchronous, lossy, partitionable, and dynamic networks, when data is distributed and replicated automatically by the principle of consistent hashing. This paper introduces consistent quorums as a solution for achieving atomic consistency. We present the design and implementation of CATS, a distributed key-value store which uses consistent quorums to guarantee linearizability and partition tolerance in such adverse and dynamic network conditions. CATS is scalable, elastic, and self-organizing; key properties for modern cloud storage middleware. Our system shows that consistency can be achieved with practical performance and modest throughput overhead (5%) for read-intensive workloads

QuORAM: A Quorum-Replicated Fault Tolerant ORAM Datastore

Privacy and security challenges due to the outsourcing of data storage and processing to third-party cloud providers are well known. With regard to data privacy, Oblivious RAM (ORAM) schemes provide strong privacy guarantees by not only hiding the contents of the data (by encryption) but also obfuscating the access patterns of the outsourced data. But most existing ORAM datastores are not fault tolerant in that if the external storage server (which stores encrypted data) or the trusted proxy (which stores the encryption key and other meta- data) crashes, an application loses all of its data. To achieve fault-tolerance, we propose QuORAM, the first ORAM datastore to replicate data with a quorum-based replication protocol. QuORAM’s contributions are three-fold: (i) it obfuscates access patterns to provide obliviousness guarantees, (ii) it replicates data using a novel lock-free and decentralized replication protocol to achieve fault-tolerance, and (iii) it guarantees linearizable semantics. Experimentally evaluating QuORAM highlights counter-intuitive results: QuORAM in- curs negligible cost to achieve obliviousness when compared to an insecure fault-tolerant replicated system; QuORAM’s peak throughput is 2.4x of its non-replicated baseline; and QuORAM performs 33.2x better in terms of throughput than an ORAM datastore that relies on CockroachDB, an open- source geo-replicated database, for fault tolerance

Coordination-Free Byzantine Replication with Minimal Communication Costs

State-of-the-art fault-tolerant and federated data management systems rely on fully-replicated designs in which all participants have equivalent roles. Consequently, these systems have only limited scalability and are ill-suited for high-performance data management. As an alternative, we propose a hierarchical design in which a Byzantine cluster manages data, while an arbitrary number of learners can reliable learn these updates and use the corresponding data. To realize our design, we propose the delayed-replication algorithm, an efficient solution to the Byzantine learner problem that is central to our design. The delayed-replication algorithm is coordination-free, scalable, and has minimal communication cost for all participants involved. In doing so, the delayed-broadcast algorithm opens the door to new high-performance fault-tolerant and federated data management systems. To illustrate this, we show that the delayed-replication algorithm is not only useful to support specialized learners, but can also be used to reduce the overall communication cost of permissioned blockchains and to improve their storage scalability

Implementing fault tolerant applications using reflective object-oriented programming

Abstract: Shows how reflection and object-oriented programming can be used to ease the implementation of classical fault tolerance mechanisms in distributed applications. When the underlying runtime system does not provide fault tolerance transparently, classical approaches to implementing fault tolerance mechanisms often imply mixing functional programming with non-functional programming (e.g. error processing mechanisms). The use of reflection improves the transparency of fault tolerance mechanisms to the programmer and more generally provides a clearer separation between functional and non-functional programming. The implementations of some classical replication techniques using a reflective approach are presented in detail and illustrated by several examples, which have been prototyped on a network of Unix workstations. Lessons learnt from our experiments are drawn and future work is discussed

A metaobject architecture for fault-tolerant distributed systems : the FRIENDS approach

The FRIENDS system developed at LAAS-CNRS is a metalevel architecture providing libraries of metaobjects for fault tolerance, secure communication, and group-based distributed applications. The use of metaobjects provides a nice separation of concerns between mechanisms and applications. Metaobjects can be used transparently by applications and can be composed according to the needs of a given application, a given architecture, and its underlying properties. In FRIENDS, metaobjects are used recursively to add new properties to applications. They are designed using an object oriented design method and implemented on top of basic system services. This paper describes the FRIENDS software-based architecture, the object-oriented development of metaobjects, the experiments that we have done, and summarizes the advantages and drawbacks of a metaobject approach for building fault-tolerant system

Fault tolerant architectures for integrated aircraft electronics systems

Work into possible architectures for future flight control computer systems is described. Ada for Fault-Tolerant Systems, the NETS Network Error-Tolerant System architecture, and voting in asynchronous systems are covered

A Survey of Fault-Tolerance and Fault-Recovery Techniques in Parallel Systems

Supercomputing systems today often come in the form of large numbers of commodity systems linked together into a computing cluster. These systems, like any distributed system, can have large numbers of independent hardware components cooperating or collaborating on a computation. Unfortunately, any of this vast number of components can fail at any time, resulting in potentially erroneous output. In order to improve the robustness of supercomputing applications in the presence of failures, many techniques have been developed to provide resilience to these kinds of system faults. This survey provides an overview of these various fault-tolerance techniques.Comment: 11 page