11,482 research outputs found
Rapid Recovery for Systems with Scarce Faults
Our goal is to achieve a high degree of fault tolerance through the control
of a safety critical systems. This reduces to solving a game between a
malicious environment that injects failures and a controller who tries to
establish a correct behavior. We suggest a new control objective for such
systems that offers a better balance between complexity and precision: we seek
systems that are k-resilient. In order to be k-resilient, a system needs to be
able to rapidly recover from a small number, up to k, of local faults
infinitely many times, provided that blocks of up to k faults are separated by
short recovery periods in which no fault occurs. k-resilience is a simple but
powerful abstraction from the precise distribution of local faults, but much
more refined than the traditional objective to maximize the number of local
faults. We argue why we believe this to be the right level of abstraction for
safety critical systems when local faults are few and far between. We show that
the computational complexity of constructing optimal control with respect to
resilience is low and demonstrate the feasibility through an implementation and
experimental results.Comment: In Proceedings GandALF 2012, arXiv:1210.202
A group membership algorithm with a practical specification
Presents a solvable specification and gives an algorithm for the group membership problem in asynchronous systems with crash failures. Our specification requires processes to maintain a consistent history in their sequences of views. This allows processes to order failures and recoveries in time and simplifies the programming of high level applications. Previous work has proven that the group membership problem cannot be solved in asynchronous systems with crash failures. We circumvent this impossibility result building a weaker, yet nontrivial specification. We show that our solution is an improvement upon previous attempts to solve this problem using a weaker specification. We also relate our solution to other methods and give a classification of progress properties that can be achieved under different models
Integrating Scale Out and Fault Tolerance in Stream Processing using Operator State Management
As users of big data applications expect fresh results, we witness a new breed of stream processing systems (SPS) that are designed to scale to large numbers of cloud-hosted machines. Such systems face new challenges: (i) to benefit from the pay-as-you-go model of cloud computing, they must scale out on demand, acquiring additional virtual machines (VMs) and parallelising operators when the workload increases; (ii) failures are common with deployments on hundreds of VMs - systems must be fault-tolerant with fast recovery times, yet low per-machine overheads. An open question is how to achieve these two goals when stream queries include stateful operators, which must be scaled out and recovered without affecting query results. Our key idea is to expose internal operator state explicitly to the SPS through a set of state management primitives. Based on them, we describe an integrated approach for dynamic scale out and recovery of stateful operators. Externalised operator state is checkpointed periodically by the SPS and backed up to upstream VMs. The SPS identifies individual operator bottlenecks and automatically scales them out by allocating new VMs and partitioning the check-pointed state. At any point, failed operators are recovered by restoring checkpointed state on a new VM and replaying unprocessed tuples. We evaluate this approach with the Linear Road Benchmark on the Amazon EC2 cloud platform and show that it can scale automatically to a load factor of L=350 with 50 VMs, while recovering quickly from failures. Copyright © 2013 ACM
Fault estimation and active fault tolerant control for linear parameter varying descriptor systems
Starting with the baseline controller design, this paper proposes an integrated approach of active fault tolerant control based on proportional derivative extended state observer (PDESO) for linear parameter varying descriptor systems. The PDESO can simultaneously provide the estimates of the system states, sensor faults, and actuator faults. The L₂ robust performance of the closed-loop system to bounded exogenous disturbance and bounded uncertainty is achieved by a two-step design procedure adapted from the traditional observer-based controller design. Furthermore, an LMI pole-placement region and the L₂ robustness performance are combined into a multiobjective formulation by suitably combing the appropriate LMI descriptions. A parameter-varying system example is given to illustrate the design procedure and the validity of the proposed integrated design approach
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FOREVER: Fault/intrusiOn REmoVal through Evolution & Recovery
The goal of the FOREVER project is to develop a service for Fault/intrusiOn REmoVal through Evolution & Recovery. In order to achieve this goal, our work addresses three main tasks: the definition of the FOREVER service architecture; the analysis of how diversity techniques can improve resilience; and the evaluation of the FOREVER service. The FOREVER service is an important contribution to intrustion-tolerant replication middleware and significantly enhances the resilience
Layered architecture for quantum computing
We develop a layered quantum computer architecture, which is a systematic
framework for tackling the individual challenges of developing a quantum
computer while constructing a cohesive device design. We discuss many of the
prominent techniques for implementing circuit-model quantum computing and
introduce several new methods, with an emphasis on employing surface code
quantum error correction. In doing so, we propose a new quantum computer
architecture based on optical control of quantum dots. The timescales of
physical hardware operations and logical, error-corrected quantum gates differ
by several orders of magnitude. By dividing functionality into layers, we can
design and analyze subsystems independently, demonstrating the value of our
layered architectural approach. Using this concrete hardware platform, we
provide resource analysis for executing fault-tolerant quantum algorithms for
integer factoring and quantum simulation, finding that the quantum dot
architecture we study could solve such problems on the timescale of days.Comment: 27 pages, 20 figure
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