October 2000
Intermediate to advanced
288 pages
9h 22m
English
book
Solutions to Parallel and Distributed Computing Problems: Lessons from Biological Sciences
by Albert Y. Zomaya, Fikret Ercal, Stephan Olariu
Content preview from Solutions to Parallel and Distributed Computing Problems: Lessons from Biological Sciences
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PREFACE
For some years now, techniques inspired by natural phenomena that are normally studied in biological sciences have gained great acceptance as efficient vehicles for solving a range of problems in a wide variety of disciplines. More recently, biologically inspired (bio-inspired, for short) techniques such as fuzzy logic, neural networks, simulated annealing, genetic algorithms, evolutionary computing models, and other bio-inspired techniques have been used to solve problems in a number of key areas in parallel and distributed computing.
Most if not all bio-inspired techniques have an inherently parallel structure. Thus, solutions based on such methods can be conveniently implemented on parallel computers. Furthermore, bio-inspired methods are considered to be “intelligent” because of their capability in adapting in situ in response to changes in the environment (e.g., solution space) that were not predicted in advance.
This compendium is composed of ten chapters that deal with the different issues and application possibilities that bio-inspired paradigms can offer in solving problems in parallel and distributed computing. The chapters present a range of subjects and applications. For example, Chapters 1 and 2 deal with the parallel and distributed computing of cellular automata and evolutionary algorithms, which are two very popular classes of bio-inspired methods. Speeding ...
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