A Dual Digraph Approach for Leaderless Atomic Broadcast (Extended Version)

Many distributed systems work on a common shared state; in such systems, distributed agreement is necessary for consistency. With an increasing number of servers, these systems become more susceptible to single-server failures, increasing the relevance of fault-tolerance. Atomic broadcast enables fault-tolerant distributed agreement, yet it is costly to solve. Most practical algorithms entail linear work per broadcast message. AllConcur -- a leaderless approach -- reduces the work, by connecting the servers via a sparse resilient overlay network; yet, this resiliency entails redundancy, limiting the reduction of work. In this paper, we propose AllConcur+, an atomic broadcast algorithm that lifts this limitation: During intervals with no failures, it achieves minimal work by using a redundancy-free overlay network. When failures do occur, it automatically recovers by switching to a resilient overlay network. In our performance evaluation of non-failure scenarios, AllConcur+ achieves comparable throughput to AllGather -- a non-fault-tolerant distributed agreement algorithm -- and outperforms AllConcur, LCR and Libpaxos both in terms of throughput and latency. Furthermore, our evaluation of failure scenarios shows that AllConcur+'s expected performance is robust with regard to occasional failures. Thus, for realistic use cases, leveraging redundancy-free distributed agreement during intervals with no failures improves performance significantly.Comment: Overview: 24 pages, 6 sections, 3 appendices, 8 figures, 3 tables. Modifications from previous version: extended the evaluation of AllConcur+ with a simulation of a multiple datacenters deploymen

Online disturbance prediction for enhanced availability in smart grids

A gradual move in the electric power industry towards Smart Grids brings new challenges to the system's efficiency and dependability. With a growing complexity and massive introduction of renewable generation, particularly at the distribution level, the number of faults and, consequently, disturbances (errors and failures) is expected to increase significantly. This threatens to compromise grid's availability as traditional, reactive management approaches may soon become insufficient. On the other hand, with grids' digitalization, real-time status data are becoming available. These data may be used to develop advanced management and control methods for a sustainable, more efficient and more dependable grid. A proactive management approach, based on the use of real-time data for predicting near-future disturbances and acting in their anticipation, has already been identified by the Smart Grid community as one of the main pillars of dependability of the future grid. The work presented in this dissertation focuses on predicting disturbances in Active Distributions Networks (ADNs) that are a part of the Smart Grid that evolves the most. These are distribution networks with high share of (renewable) distributed generation and with systems in place for real-time monitoring and control. Our main goal is to develop a methodology for proactive network management, in a sense of proactive mitigation of disturbances, and to design and implement a method for their prediction. We focus on predicting voltage sags as they are identified as one of the most frequent and severe disturbances in distribution networks. We address Smart Grid dependability in a holistic manner by considering its cyber and physical aspects. As a result, we identify Smart Grid dependability properties and develop a taxonomy of faults that contribute to better understanding of the overall dependability of the future grid. As the process of grid's digitization is still ongoing there is a general problem of a lack of data on the grid's status and especially disturbance-related data. These data are necessary to design an accurate disturbance predictor. To overcome this obstacle we introduce a concept of fault injection to simulation of power systems. We develop a framework to simulate a behavior of distribution networks in the presence of faults, and fluctuating generation and load that, alone or combined, may cause disturbances. With the framework we generate a large set of data that we use to develop and evaluate a voltage-sag disturbance predictor. To quantify how prediction and proactive mitigation of disturbances enhance availability we create an availability model of a proactive management. The model is generic and may be applied to evaluate the effect of proactive management on availability in other types of systems, and adapted for quantifying other types of properties as well. Also, we design a metric and a method for optimizing failure prediction to maximize availability with proactive approach. In our conclusion, the level of availability improvement with proactive approach is comparable to the one when using high-reliability and costly components. Following the results of the case study conducted for a 14-bus ADN, grid's availability may be improved by up to an order of magnitude if disturbances are managed proactively instead of reactively. The main results and contributions may be summarized as follows: (i) Taxonomy of faults in Smart Grid has been developed; (ii) Methodology and methods for proactive management of disturbances have been proposed; (iii) Model to quantify availability with proactive management has been developed; (iv) Simulation and fault-injection framework has been designed and implemented to generate disturbance-related data; (v) In the scope of a case study, a voltage-sag predictor, based on machine- learning classification algorithms, has been designed and the effect of proactive disturbance management on downtime and availability has been quantified

Operating System Support for Redundant Multithreading

Failing hardware is a fact and trends in microprocessor design indicate that the fraction of hardware suffering from permanent and transient faults will continue to increase in future chip generations. Researchers proposed various solutions to this issue with different downsides: Specialized hardware components make hardware more expensive in production and consume additional energy at runtime. Fault-tolerant algorithms and libraries enforce specific programming models on the developer. Compiler-based fault tolerance requires the source code for all applications to be available for recompilation. In this thesis I present ASTEROID, an operating system architecture that integrates applications with different reliability needs. ASTEROID is built on top of the L4/Fiasco.OC microkernel and extends the system with Romain, an operating system service that transparently replicates user applications. Romain supports single- and multi-threaded applications without requiring access to the application's source code. Romain replicates applications and their resources completely and thereby does not rely on hardware extensions, such as ECC-protected memory. In my thesis I describe how to efficiently implement replication as a form of redundant multithreading in software. I develop mechanisms to manage replica resources and to make multi-threaded programs behave deterministically for replication. I furthermore present an approach to handle applications that use shared-memory channels with other programs. My evaluation shows that Romain provides 100% error detection and more than 99.6% error correction for single-bit flips in memory and general-purpose registers. At the same time, Romain's execution time overhead is below 14% for single-threaded applications running in triple-modular redundant mode. The last part of my thesis acknowledges that software-implemented fault tolerance methods often rely on the correct functioning of a certain set of hardware and software components, the Reliable Computing Base (RCB). I introduce the concept of the RCB and discuss what constitutes the RCB of the ASTEROID system and other fault tolerance mechanisms. Thereafter I show three case studies that evaluate approaches to protecting RCB components and thereby aim to achieve a software stack that is fully protected against hardware errors

Um estudo sobre rejuvenescimento de software em servidores web apache

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-Graduação em Ciência da Computação

Multi-domain Software Defined Networking: Research status and challenges

A key focus of the transition to next generation computer networking is to improve management of network services thereby enhancing traffic control and flows while simplifying higher-level functionality. Software-defined networking (SDN) is an approach that is being developed to facilitate next generation computer networking by decoupling the traffic control system from the underlying traffic transmission system. SDN offers programmability in network services by separating the control plane from the data plane within network devices and providing programmability for network services. Enhanced connectivity services across the global digital network require a multi-domain capability. This paper presents a review of the current research status in SDN and multi-domain SDN, focusing on OpenFlow protocol, and its future related challenges

Towards the design of efficient error detection mechanisms

The pervasive nature of modern computer systems has led to an increase in our reliance on such systems to provide correct and timely services. Moreover, as the functionality of computer systems is being increasingly defined in software, it is imperative that software be dependable. It has previously been shown that a fault intolerant software system can be made fault tolerant through the design and deployment of software mechanisms implementing abstract artefacts known as error detection mechanisms (EDMs) and error recovery mechanisms (ERMs), hence the design of these components is central to the design of dependable software systems. The EDM design problem, which relates to the construction of a boolean predicate over a set of program variables, is inherently difficult, with current approaches relying on system specifications and the experience of software engineers. As this process necessarily entails the identification and incorporation of program variables by an error detection predicate, this thesis seeks to address the EDM design problem from a novel variable-centric perspective, with the research presented supporting the thesis that, where it exists under the assumed system model, an efficient EDM consists of a set of critical variables. In particular, this research proposes (i) a metric suite that can be used to generate a relative ranking of the program variables in a software with respect to their criticality, (ii) a systematic approach for the generation of highly-efficient error detection predicates for EDMs, and (iii) an approach for dependability enhancement based on the protection of critical variables using software wrappers that implement error detection and correction predicates that are known to be efficient. This research substantiates the thesis that an efficient EDM contains a set of critical variables on the basis that (i) the proposed metric suite is able, through application of an appropriate threshold, to identify critical variables, (ii) efficient EDMs can be constructed based only on the critical variables identified by the metric suite, and (iii) the criticality of the identified variables can be shown to extend across a software module such that an efficient EDM designed for that software module should seek to determine the correctness of the identified variables