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Scheduling in Parallel Computing Systems: Fuzzy and Annealing
Techniques advocates the viability of using fuzzy and annealing
methods in solving scheduling problems for parallel computing
systems. The book proposes new techniques for both static and
dynamic scheduling, using emerging paradigms that are inspired by
natural phenomena such as fuzzy logic, mean-field annealing, and
simulated annealing. Systems that are designed using such
techniques are often referred to in the literature as intelligent'
because of their capability to adapt to sudden changes in their
environments. Moreover, most of these changes cannot be anticipated
in advance or included in the original design of the system.
Scheduling in Parallel Computing Systems: Fuzzy and Annealing
Techniques provides results that prove such approaches can become
viable alternatives to orthodox solutions to the scheduling
problem, which are mostly based on heuristics. Although heuristics
are robust and reliable when solving certain instances of the
scheduling problem, they do not perform well when one needs to
obtain solutions to general forms of the scheduling problem. On the
other hand, techniques inspired by natural phenomena have been
successfully applied for solving a wide range of combinatorial
optimization problems (e.g. traveling salesman, graph
partitioning). The success of these methods motivated their use in
this book to solve scheduling problems that are known to be
formidable combinatorial problems. Scheduling in Parallel Computing
Systems: Fuzzy and Annealing Techniques is an excellent reference
and may be used for advanced courses on the topic.
Scheduling in Parallel Computing Systems: Fuzzy and Annealing
Techniques advocates the viability of using fuzzy and annealing
methods in solving scheduling problems for parallel computing
systems. The book proposes new techniques for both static and
dynamic scheduling, using emerging paradigms that are inspired by
natural phenomena such as fuzzy logic, mean-field annealing, and
simulated annealing. Systems that are designed using such
techniques are often referred to in the literature as intelligent'
because of their capability to adapt to sudden changes in their
environments. Moreover, most of these changes cannot be anticipated
in advance or included in the original design of the system.
Scheduling in Parallel Computing Systems: Fuzzy and Annealing
Techniques provides results that prove such approaches can become
viable alternatives to orthodox solutions to the scheduling
problem, which are mostly based on heuristics. Although heuristics
are robust and reliable when solving certain instances of the
scheduling problem, they do not perform well when one needs to
obtain solutions to general forms of the scheduling problem. On the
other hand, techniques inspired by natural phenomena have been
successfully applied for solving a wide range of combinatorial
optimization problems (e.g. traveling salesman, graph
partitioning). The success of these methods motivated their use in
this book to solve scheduling problems that are known to be
formidable combinatorial problems. Scheduling in Parallel Computing
Systems: Fuzzy and Annealing Techniques is an excellent reference
and may be used for advanced courses on the topic.
The tool for visualization is Microsoft Visual C++. This popular
software has the standard C++ combined with the Microsoft
Foundation Classes (MFC) libraries for Windows visualization. This
book explains how to create a graph interactively, solve problems
in graph theory with minimum number of C++ codes, and provide
friendly interfaces that makes learning the topics an interesting
one. Each topic in the book comes with working Visual C++ codes
which can easily be adapted as solutions to various problems in
science and engineering.
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