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.