Stochastic modeling for performance evaluation of database replication protocols

Performance is often the most important non-functional property for database systems and associated replication solutions. This is true at least in in-dustrial contexts. Evaluating performance using real systems, however, is com-putationally demanding and costly. In many cases, choosing between several competing replication protocols poses a difficulty in ranking these protocols meaningfully: the ranking is determined not so much by the quality of the com-peting protocols but, instead, by the quality of the available implementations. Addressing this difficulty requires a level of abstraction in which the impact on the comparison of the implementations is reduced, or entirely eliminated. We propose a stochastic model for performance evaluation of database replication protocols, paying particular attention to: i) empirical validation of a number of assumptions used in the stochastic model, and ii) empirical validation of model accuracy for a chosen replication protocol. For the empirical validations we used the TPC-C benchmark. Our implementation of the model is based on Stochastic Activity Networks (SAN), extended by bespoke code. The model may reduce the cost of performance evaluation in comparison with empirical measurements, while keeping the accuracy of the assessment to an acceptable level

A survey on online monitoring approaches of computer-based systems

This report surveys forms of online data collection that are in current use (as well as being the subject of research to adapt them to changing technology and demands), and can be used as inputs to assessment of dependability and resilience, although they are not primarily meant for this use

Hyperledger Fabric: A Distributed Operating System for Permissioned Blockchains

Fabric is a modular and extensible open-source system for deploying and operating permissioned blockchains and one of the Hyperledger projects hosted by the Linux Foundation (www.hyperledger.org). Fabric is the first truly extensible blockchain system for running distributed applications. It supports modular consensus protocols, which allows the system to be tailored to particular use cases and trust models. Fabric is also the first blockchain system that runs distributed applications written in standard, general-purpose programming languages, without systemic dependency on a native cryptocurrency. This stands in sharp contrast to existing blockchain platforms that require "smart-contracts" to be written in domain-specific languages or rely on a cryptocurrency. Fabric realizes the permissioned model using a portable notion of membership, which may be integrated with industry-standard identity management. To support such flexibility, Fabric introduces an entirely novel blockchain design and revamps the way blockchains cope with non-determinism, resource exhaustion, and performance attacks. This paper describes Fabric, its architecture, the rationale behind various design decisions, its most prominent implementation aspects, as well as its distributed application programming model. We further evaluate Fabric by implementing and benchmarking a Bitcoin-inspired digital currency. We show that Fabric achieves end-to-end throughput of more than 3500 transactions per second in certain popular deployment configurations, with sub-second latency, scaling well to over 100 peers.Comment: Appears in proceedings of EuroSys 2018 conferenc

Tolerating Byzantine Faults in Transaction Processing Systems using Commit Barrier Scheduling

This paper describes the design, implementation, and evaluation of a replication scheme to handle Byzantine faults in transaction processing database systems. The scheme compares answers from queries and updates on multiple replicas which are unmodified, off-the-shelf systems, to provide a single database that is Byzantine fault tolerant. The scheme works when the replicas are homogeneous, but it also allows heterogeneous replication in which replicas come from different vendors. Heterogeneous replicas reduce the impact of bugs and security compromises because they are implemented independently and are thus less likely to suffer correlated failures. The main challenge in designing a replication scheme for transaction processing systems is ensuring that the different replicas execute transactions in equivalent serial orders while allowing a high degree of concurrency. Our scheme meets this goal using a novel concurrency control protocol, commit barrier scheduling (CBS). We have implemented CBS in the context of a replicated SQL database, HRDB (Heterogeneous Replicated DB), which has been tested with unmodified production versions of several commercial and open source databases as replicas. Our experiments show an HRDB configuration that can tolerate one faulty replica has only a modest performance overhead (about 17 % for the TPC-C benchmark). HRDB successfully masks several Byzantine faults observed in practice and we have used it to find a new bug in MySQL