15,933 research outputs found
Real-time and fault tolerance in distributed control software
Closed loop control systems typically contain multitude of spatially distributed sensors and actuators operated simultaneously. So those systems are parallel and distributed in their essence. But mapping this parallelism onto the given distributed hardware architecture, brings in some additional requirements: safe multithreading, optimal process allocation, real-time scheduling of bus and network resources. Nowadays, fault tolerance methods and fast even online reconfiguration are becoming increasingly important. All those often conflicting requirements, make design and implementation of real-time distributed control systems an extremely difficult task, that requires substantial knowledge in several areas of control and computer science. Although many design methods have been proposed so far, none of them had succeeded to cover all important aspects of the problem at hand. [1] Continuous increase of production in embedded market, makes a simple and natural design methodology for real-time systems needed more then ever
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Software safety : a definition and some preliminary thoughts
Software safety is the subject of a research project in its initial stages at the University of California Irvine. This research deals with critical real-time software where the cost of an error is high, e.g. human life. In this paper software techniques having a bearing on safety are described and evaluated. Initial definitions of software safety concepts are presented along with some preliminary thoughts and research questions
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
On the engineering of crucial software
The various aspects of the conventional software development cycle are examined. This cycle was the basis of the augmented approach contained in the original grant proposal. This cycle was found inadequate for crucial software development, and the justification for this opinion is presented. Several possible enhancements to the conventional software cycle are discussed. Software fault tolerance, a possible enhancement of major importance, is discussed separately. Formal verification using mathematical proof is considered. Automatic programming is a radical alternative to the conventional cycle and is discussed. Recommendations for a comprehensive approach are presented, and various experiments which could be conducted in AIRLAB are described
Integrating R and Hadoop for Big Data Analysis
Analyzing and working with big data could be very diffi cult using classical
means like relational database management systems or desktop software packages
for statistics and visualization. Instead, big data requires large clusters
with hundreds or even thousands of computing nodes. Offi cial statistics is
increasingly considering big data for deriving new statistics because big data
sources could produce more relevant and timely statistics than traditional
sources. One of the software tools successfully and wide spread used for
storage and processing of big data sets on clusters of commodity hardware is
Hadoop. Hadoop framework contains libraries, a distributed fi le-system (HDFS),
a resource-management platform and implements a version of the MapReduce
programming model for large scale data processing. In this paper we investigate
the possibilities of integrating Hadoop with R which is a popular software used
for statistical computing and data visualization. We present three ways of
integrating them: R with Streaming, Rhipe and RHadoop and we emphasize the
advantages and disadvantages of each solution.Comment: Romanian Statistical Review no. 2 / 201
Rigorous Design of Fault-Tolerant Transactions for Replicated Database Systems using Event B
System availability is improved by the replication of data objects in a distributed database system. However, during updates, the complexity of keeping replicas identical arises due to failures of sites and race conditions among conflicting transactions. Fault tolerance and reliability are key issues to be addressed in the design and architecture of these systems. Event B is a formal technique which provides a framework for developing mathematical models of distributed systems by rigorous description of the problem, gradually introducing solutions in refinement steps, and verification of solutions by discharge of proof obligations. In this paper, we present a formal development of a distributed system using Event B that ensures atomic commitment of distributed transactions consisting of communicating transaction components at participating sites. This formal approach carries the development of the system from an initial abstract specification of transactional updates on a one copy database to a detailed design containing replicated databases in refinement. Through refinement we verify that the design of the replicated database confirms to the one copy database abstraction
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