Design and Analysis of Distributed Algorithms (Wiley Series on Parallel and Distributed Computing)

Design And Analyze algorithms for distributed computing environments

Design and Analysis of Distributed Algorithms focuses on developing problem-solving skills and fully exploiting design tools and techniques. Moreover, the author helps readers develop the analytical tools and skills needed to evaluate the costs of complex designs and protocols.
This text is based on a simple and fully reactive computational model that allows for intuitive comprehension and logical designs. The principles and techniques that users learn can be applied to any distributed computing environment (e.g., distributed systems, communication networks, data networks, grid networks, internet, etc.). Based on a method developed and refined during the author's twenty years of teaching experience, the text provides a wealth of unique material and learning aids that enable the reader to learn how to design algorithms and protocols to solve problems and perform tasks efficiently in a distributed computing environment.

Features include:

* Emphasis on developing problem-solving skills and fully leveraging design tools and techniques with a straightforward, easy-to-follow writing style
* Chapter on distributed data and structures, an important area not covered in comparable texts
* Detailed coverage of synchronous computations, a necessary element for "energy aware" computing
* Theoretical and experimental exercises in each chapter that allow readers to apply their newfound skills

All algorithms and protocols presented in the text, as well as those in the exercises, are easily and immediately programmable. References at the end of each chapter lead readers to additional materials for further study.
A natural textbook for upper-level undergraduates and graduate students, with its emphasis on problem solving, this book is also ideal for system-protocol designers and communications software engineers and developers. It will enable them to understand the principles of how to design workable, efficient protocols in any distributed computing environment.

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Computing Patterns in Strings (ACM Press Books)

Computing Patterns in Strings by B. Smyth is a very useful book. String algorithms is a separate discipline in Europe (France, UK, Italy etc.) and in many other places in the world. However, in North America, this is not the case and the research and the results are scattered among many disciplines and many books. Thus most significant books on the topics concerning string algorithms are not of North American provenance. Smyth's book provide the reader with a comprehensive up-to-date overview of the discipline, rather than covering a few topics. The author exhibits a witty and readable style and, except for a few errors one always has to expect in a book covering so many algorithms and a well-founded reader can easily spot and disregard, the book is an excellent introduction to the discipline. I can highly recommend it to anyone seriously considering extending his/her knowledge of computer science. I certainly enjoyed it.

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Classification Algorithms for Codes and Designs

This book considers one of the basic problems in discrete mathematics: given a collection of constraints, describe up to isomorphism all the objects that meet them. Only a handful of classification results for combinatorial objects are dated before the mid-20th century; indeed, it is through modern computers and recent developments in algorithms that this topic has flourished and matured. This book is the first comprehensive reference on combinatorial classification algorithms, with emphasis on both the general theory and application to central families of combinatorial objects, in particular, codes and designs. The accompanying DVD provides an exhaustive catalogue of combinatorial objects with small parameters. The book will be of great interest to researchers and can be used as course material for graduate courses in both computer science and mathematics.

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Beginning Algorithms (Wrox Beginning Guides)

Packed with detailed explanations and instructive examples, the book begins by offering you some fundamental data structures and then goes on to explain various sorting algorithms. You'll then learn efficient practices for storing and searching by way of hashing, trees, sets, and maps. The authors also share tips on optimization techniques and ways to avoid common performance pitfalls. In the end, you'll be prepared to build the algorithms and data structures most commonly encountered in day-to-day software development.

What you will learn from this book


* The basics of algorithms, such as iteration and recursion
* Elementary data structures such as lists, stacks, and queues
* Basic and advanced sorting algorithms including insertion sort, quicksort, and shell sort
* Advanced data structures such as binary trees, ternary trees, and heaps
* Algorithms for string searching, string matching, hashing, and computational geometry
* How to use test-driven development techniques to ensure your code works as intended
* How to dramatically improve the performance of your code with hands-on techniques for profiling and optimization



Who this book is for

This book is for anyone who develops applications, or is just beginning to do so, and is looking to understand algorithms and data structures. An understanding of computer programming is beneficial.

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Approximation Algorithms

This book covers the dominant theoretical approaches to the approximate solution of hard combinatorial optimization and enumeration problems. It contains elegant combinatorial theory, useful and interesting algorithms, and deep results about the intrinsic complexity of combinatorial problems. Its clarity of exposition and excellent selection of exercises will make it accessible and appealing to all those with a taste for mathematics and algorithms. Richard Karp,University Professor, University of California at Berkeley Following the development of basic combinatorial optimization techniques in the 1960s and 1970s, a main open question was to develop a theory of approximation algorithms. In the 1990s, parallel developments in techniques for designing approximation algorithms as well as methods for proving hardness of approximation results have led to a beautiful theory. The need to solve truly large instances of computationally hard problems, such as those arising from the Internet or the human genome project, has also increased interest in this theory. The field is currently very active, with the toolbox of approximation algorithm design techniques getting always richer. It is a pleasure to recommend Vijay Vazirani's well-written and comprehensive book on this important and timely topic. I am sure the reader will find it most useful both as an introduction to approximability as well as a reference to the many aspects of approximation algorithms. László Lovász, Senior Researcher, Microsoft Research

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Analysis of Algorithms : An Active Learning Approach

The goal of Analysis of Algorithms is to raise awareness of the effect that algorithms have on the efficiency of a program and to develop the necessary skills to analyze general algorithms used in programs. The text presents the material with the expectation that it can be used with active and cooperative learning methodology, based on the premise that students learn more effectively and retain more information longer when they are active participants in the learning process. Developed to offer students multiple opportunities for active and cooperative learning. To accomplish this, the chapters are clear and complete to encourage students to prepare by reading before class, and the text is filled with exciting examples and exercises that look at the efficiency of various algorithms to solve a problem.

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Algorithms: Design Techniques and Analysis (Lecture Notes Series on Computing, Vol 7)

The book represents a well written, consistent and easy to follow view on the area of algorithm analysis. It gives an excellent overview of various mathematical and computer science areas, including but not limited to combinatorial geometry, NP-problems, complexity theory, graph theory, algorithm analysis, dynamic programming and even computational geometry.

Most of the chapters are intended for a senior level undergraduate and graduate student, but some (such as part 4 devoted to complexity problems) are more suitable for "mature" audience and require some preliminary knowledge in the area.

I found chapters on sorting, data structures, recursion and functional programming well written and structured, and examples to be practical as well as informative.

Sections on amortized analysis, randomized algorithms, approximation algorithms and iteration improvement deal with current directions in the algorithmic research and provide an excellent overview of the "state-of-the-art" in these areas. I also enjoyed reading through the section on greedy algorithms (shortest path and minimum spanning tree problems).

Section on computational complexity and analysis of the relationship between complexity classes seems to be a bit complicated, those who are interested in this area should probably do some preliminary reading.

The last section on computational geometry (my area of expertise) and applications of Voronoi diagrams could be extended, but even in the current state it givs a pretty good idea of what computational geometry is all about.

Overall, I give to this book a "5 star" review and recommend it for anyone who is seriously interested in learning exactly how algorithm design and analysis work. I thoroughly enjoyed reading this book and can only wish that author would write more books like that in the future!

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Algorithms on Strings, Trees and Sequences: Computer Science and Computational Biology

Traditionally an area of study in computer science, string algorithms have, in recent years, become an increasingly important part of biology, particularly genetics. This volume is a comprehensive look at computer algorithms for string processing. In addition to pure computer science, Gusfield adds extensive discussions on biological problems that are cast as string problems and on methods developed to solve them. This text emphasizes the fundamental ideas and techniques central to today's applications. New approaches to this complex material simplify methods that up to now have been for the specialist alone. With over 400 exercises to reinforce the material and develop additional topics, the book is suitable as a text for graduate or advanced undergraduate students in computer science, computational biology, or bio-informatics.

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Algorithms in Java, Third Edition (Parts 1-4)

Sedgewick has a real gift for explaining concepts in a way that makes them easy to understand. The use of real programs in page-size (or less) chunks that can be easily understood is a real plus. The figures, programs, and tables are a significant contribution to the learning experience of the reader; they make this book distinctive.
--William A. Ward, University of South Alabama

This edition of Robert Sedgewick's popular work provides current and comprehensive coverage of important algorithms for Java programmers. Michael Schidlowsky and Sedgewick have developed new Java implementations that both express the methods in a concise and direct manner and provide programmers with the practical means to test them on real applications.

Many new algorithms are presented, and the explanations of each algorithm are much more detailed than in previous editions. A new text design and detailed, innovative figures, with accompanying commentary, greatly enhance the presentation. The third edition retains the successful blend of theory and practice that has made Sedgewick's work an invaluable resource for more than 400,000 programmers!

This particular book, Parts 1-4, represents the essential first half of Sedgewick's complete work. It provides extensive coverage of fundamental data structures and algorithms for sorting, searching, and related applications. Although the substance of the book applies to programming in any language, the implementations by Schidlowsky and Sedgewick also exploit the natural match between Java classes and abstract data type (ADT) implementations.

Highlights:


* Java class implementations of more than 100 important practical algorithms
* Emphasis on ADTs, modular programming, and object-oriented programming
* Extensive coverage of arrays, linked lists, trees, and other fundamental data structures
* Thorough treatment of algorithms for sorting, selection, priority queue ADT implementations, and symbol table ADT implementations (search algorithms)
* Complete implementations for binomial queues, multiway radix sorting, randomized BSTs, splay trees, skip lists, multiway tries, B trees, extendible hashing, and many other advanced methods
* Quantitative information about the algorithms that gives you a basis for comparing them
* More than 1,000 exercises and more than 250 detailed figures to help you learn properties of the algorithms



Whether you are learning the algorithms for the first time or wish to have up-to-date reference material that incorporates new programming styles with classic and new algorithms, you will find a wealth of useful information in this book.

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Algorithms for Fuzzy Clustering: Methods in c-Means Clustering with Applications (Studies in Fuzziness and Soft Computing)

The main subject of this book is the fuzzy c-means proposed by Dunn and Bezdek and their variations including recent studies. A main reason why we concentrate on fuzzy c-means is that most methodology and application studies in fuzzy clustering use fuzzy c-means, and hence fuzzy c-means should be considered to be a major technique of clustering in general, regardless whether one is interested in fuzzy methods or not. Unlike most studies in fuzzy c-means, what we emphasize in this book is a family of algorithms using entropy or entropy-regularized methods which are less known, but we consider the entropy-based method to be another useful method of fuzzy c-means. Throughout this book one of our intentions is to uncover theoretical and methodological differences between the Dunn and Bezdek traditional method and the entropy-based method. We do note claim that the entropy-based method is better than the traditional method, but we believe that the methods of fuzzy c-means become complete by adding the entropy-based method to the method by Dunn and Bezdek, since we can observe natures of the both methods more deeply by contrasting these two.

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Algorithms and Theory of Computation Handbook

In addition to traditional topics, this comprehensive compendium of algorithms, data structures, and theory of computation covers:
- applications areas where algorithms and data structuring techniques are of special importance
- graph drawing
- robot algorithms
- VLSI layoutovision and image processing algorithms
- scheduling
- electronic cash
- data compression
- dynamic graph algorithms
- on-line algorithms
- multidimensional data structures
- cryptography
- advanced topics in combinatorial optimization and parallel/distributed computing

Unique coverage of Algorithms and Theory of Computation Handbook makes it an essential reference for researchers and practitioners in these applications areas.

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Algorithms & Data Structures : The Science Of Computing (Electrical and Computer Engineering Series)

While many computer science textbooks are confined to teaching programming code and languages, Algorithms and Data Structures: The Science of Computing takes a step back to introduce and explore algorithms -- the content of the code. Focusing on three core topics: design (the architecture of algorithms), theory (mathematical modeling and analysis), and the scientific method (experimental confirmation of theoretical results), the book helps students see that computer science is about problem solving, not simply the memorization and recitation of languages. Unlike many other texts, the methods of inquiry are explained in an integrated manner so students can see explicitly how they interact. Recursion and object oriented programming are emphasized as the main control structure and abstraction mechanism, respectively, in algorithm design. Designed for the CS2 course, the book includes text exercises and has laboratory exercises at the supplemental Web site.

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The Spirit of Computing (3rd Edition)

This book presents the concepts, methods, and results that are fundamental to the science of computing. The book begins with the basic ideas of algorithms such as the structure and the methods of data manipulation, and then moves on to demonstrate how to design an accurate and efficient algorithm. Inherent limitations to algorithmic design are also discussed throughout the second part of the text. The third edition features an introduction to the object-oriented paradigm along with new approaches to computation. Anyone interested in being introduced to the theory of computer science.

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A Programmer's Companion to Algorithm Analysis

Focusing on practical issues, A Programmer's Companion to Algorithm Analysis bridges the gap between algorithms and software programs. This book explains the fundamental differences between the computational model assumed for algorithms and the real architectures in which programs execute. It highlights the pitfalls that can occur when implementing an algorithm as software and offers suggestions to solve these problems. The book also explores the interactions among program, compiler, and run-time support system, contrasting this with the simpler model assumed for algorithms. Intended for software developers and programmers, it places particular emphasis on the implications of the memory hierarchy on program efficiency.

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A Programmer's Companion to Algorithm Analysis

Focusing on practical issues, A Programmer's Companion to Algorithm Analysis bridges the gap between algorithms and software programs. This book explains the fundamental differences between the computational model assumed for algorithms and the real architectures in which programs execute. It highlights the pitfalls that can occur when implementing an algorithm as software and offers suggestions to solve these problems. The book also explores the interactions among program, compiler, and run-time support system, contrasting this with the simpler model assumed for algorithms. Intended for software developers and programmers, it places particular emphasis on the implications of the memory hierarchy on program efficiency.


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