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2013 | Buch

Fault-Tolerant Search Algorithms

Reliable Computation with Unreliable Information

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SUCHEN

Über dieses Buch

Why a book on fault-tolerant search algorithms? Searching is one of the fundamental problems in computer science. Time and again algorithmic and combinatorial issues originally studied in the context of search find application in the most diverse areas of computer science and discrete mathematics. On the other hand, fault-tolerance is a necessary ingredient of computing. Due to their inherent complexity, information systems are naturally prone to errors, which may appear at any level – as imprecisions in the data, bugs in the software, or transient or permanent hardware failures. This book provides a concise, rigorous and up-to-date account of different approaches to fault-tolerance in the context of algorithmic search theory.

Thanks to their basic structure, search problems offer insights into how fault-tolerant techniques may be applied in various scenarios. In the first part of the book, a paradigmatic model for fault-tolerant search is presented, the Ulam—Rényi problem. Following a didactic approach, the author takes the reader on a tour of Ulam—Rényi problem variants of increasing complexity. In the context of this basic model, fundamental combinatorial and algorithmic issues in the design of fault-tolerant search procedures are discussed. The algorithmic efficiency achievable is analyzed with respect to the statistical nature of the error sources, and the amount of information on which the search algorithm bases its decisions. In the second part of the book, more general models of faults and fault-tolerance are considered. Special attention is given to the application of fault-tolerant search procedures to specific problems in distributed computing, bioinformatics and computational learning.

This book will be of special value to researchers from the areas of combinatorial search and fault-tolerant computation, but also to researchers in learning and coding theory, databases, and artificial intelligence. Only basic training in discrete mathematics is assumed. Parts of the book can be used as the basis for specialized graduate courses on combinatorial search, or as supporting material for a graduate or undergraduate course on error-correcting codes.

Inhaltsverzeichnis

Frontmatter
Chapter 1. Prologue: What This Book Is About
Abstract
The typical structure of a search problem is defined by a set of objects \(\mathcal{U}\), a family of tests \(\mathcal{T}\) which can be used to acquire information on the elements of \(\mathcal{U}\); a set of rules \(\mathcal{R}\) about the way the tests can be chosen or combined; and some performance measure \(\mathcal{M}\). The goal is to provide a strategy to select tests from \(\mathcal{T}\) according to the given rules \(\mathcal{R}\), in order to guarantee the correct identification of some initially unknown object in \(\mathcal{U}\), and optimize the given performance measure (e.g., worst case or average number of queries, time or space complexity, etc.).
Ferdinando Cicalese

The Ulam-Rényi Game and Its Variants

Frontmatter
Chapter 2. Fault-Tolerant Search à la Ulam-Rényi
Abstract
The problem of efficient search for an unknown element in a finite set S can be reformulated as a game between two players—one deciding the questions to be asked, and the other deciding the answering strategy that makes as hard as possible the first player’s task.
Ferdinando Cicalese
Chapter 3. Adaptive vs. Non-adaptive Search
Abstract
Led by Schalkwijk and Kailath, Berlekamp proposed the following model for information transmission over a noisy channel equipped with a noiseless and delayless feedback channel of large capacity: Suppose the source must send a message μ from a set \(\mathcal{M}\) of M many possible messages. Assume that the channel can only deliver bits, and that up to e of the bits can be distorted during transmission. In order to communicate the message to the receiver, the source sends a certain number n of bits over the noisy channel. In contrast with traditional e-error correcting codes, these n bits may adaptively depend on the information received by the source via the feedback channel.
Ferdinando Cicalese
Chapter 4. Weighted Errors over a General Channel
Abstract
In this chapter, we will analyze a variant of the Ulam-Rényi problem with q-ary questions where we assume that Carole’s lies are constrained to patterns agreed upon in advance and known to Paul. This is the case, e.g., when in the classical yes-no question game one stipulates that Carole can only lie if the correct answer to Paul’s question is yes, while she must answer sincerely whenever the correct answer to Paul’s question is no.
Ferdinando Cicalese
Chapter 5. Variations on a Theme of Ulam and Rényi: More Types of Questions and Lies
Abstract
In the search model investigated in the previous chapters, questions are allowed to be arbitrary subsets of the search space. Such an assumption implies an “expensive” representation of both the strategies and the states of the game: For a game over a search space of cardinality M = 2 m , one needs M bits for describing each query and each component of the state.
Ferdinando Cicalese

Other Models

Frontmatter
Chapter 6. Delays and Time Outs
Abstract
In this chapter we study the effect of delay on the efficiency of search procedures. In the models we are going to analyze, the delay itself is a source of uncertainty for the searching procedure. A classical assumption in the theory of search is that the information obtained by the execution of a test is available right after the test has been made, that is, a “yes/no” answer is immediately received after the question has been posed, and this knowledge can be used in the formulation of successive questions.
Ferdinando Cicalese
Chapter 7. Group Testing
Abstract
Group testing is a search model which first appeared in the context of a biomedical application, in the last years of the Second World War. It became clear that large amounts of money were spent on testing soldiers who would eventually be found not to be infected. Finding them healthy was obviously good news, nonetheless, the large amount of “useless” testing was also considered a waste of public funds which should be avoided, since the aim of testing the troops was to find the infected individuals.
Ferdinando Cicalese
Chapter 8. Resilient Search
Abstract
In this chapter we analyze a model of fault-tolerant search in which reiterating a question cannot help the search algorithm because the errors are due to permanent memory faults. A memory fault occurs if the correct value stored in a memory location changes because of some failure. The change can occur at any moment in a dynamic and unpredictable fashion. More failures can also occur simultaneously. Clearly, if a memory fault affects the result of a query, after this fault has occurred any instance of the query will produce the same faulty result.
Ferdinando Cicalese
Chapter 9. A Model for Learning
Abstract
Learning can be thought of as the activity which allows the learner to formulate the hypothesis likely to agree with previous observations. New observations might induce the learner to revise previous hypotheses, and thus to modify/improve the current state of knowledge in order to combine the new and the old observations. Observations are usually examples and counterexamples provided “randomly” to the learner. Alternatively, the learner may have the possibility to ask for the correct classification of an example chosen from a given pool. In many concrete applications the learning process is affected by noise. In this chapter we shall discuss several examples of learning in noisy environments, showing their relations to both Ulam-Rényi games and computational learning theories.
Ferdinando Cicalese
Backmatter
Metadaten
Titel
Fault-Tolerant Search Algorithms
verfasst von
Ferdinando Cicalese
Copyright-Jahr
2013
Verlag
Springer Berlin Heidelberg
Electronic ISBN
978-3-642-17327-1
Print ISBN
978-3-642-17326-4
DOI
https://doi.org/10.1007/978-3-642-17327-1

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