Abstract—Nowadays, multi-processor systems are being used
extensively in parallel computing. The effective scheduling
system for implementing parallel programs to achieve high
performance is crucial. The timing should be done in such a way
that the total execution time of the program with according to
time and tasks to be minimize communication between
processors. This is a NP-Hard problem which tasks graph
scheduling approaches based on deterministic methods are not
effective in this context while the use of evolutionary computing
and genetic algorithms to solve this problem effectively are
mainly. In this paper, a new genetic algorithm is proposed for
the problem of scheduling tasks graph which is able to spend less
time to get. This algorithm is based on a new approach to
minimize the length of the critical path and the cost of
communication between processors. In this paper, we calculate
the number of descendants for each node in which tries to
minimize the total execution time of the program.
Index Terms—Scheduling multi-processor, tasks graph,
algorithm genetic.
Mostafa Mahi is with the Department of Computer Engineering and
Information Technology, Payame Noor University, Tehran, Iran (e-mail:
mahi@pnu.ac.ir).
Halife Kodaz is with the Department of Computer Engineering, Selcuk
University, Konya, Turkey (e-mail: hkodaz@selcuk.edu.tr).
[PDF]
Cite:Mostafa Mahi and Halife Kodaz, "Genetic Algorithm with Descendants Idea for Scheduling Tasks Graph in the Multi-Processor Architecture," Journal of Advances in Computer Networks vol. 2, no. 1, pp. 10-13, 2014.
