
Be the first to like this
Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. If you continue browsing the site, you agree to the use of cookies on this website. See our User Agreement and Privacy Policy.
Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. If you continue browsing the site, you agree to the use of cookies on this website. See our Privacy Policy and User Agreement for details.
Published on
Algorithms developed for scheduling applications on heterogeneous multiprocessor system focus on a
single objective such as execution time, cost or total data transmission time. However, if more than one
objective (e.g. execution cost and time, which may be in conflict) are considered, then the problem becomes
more challenging. This project is proposed to develop a multiobjective scheduling algorithm using
Evolutionary techniques for scheduling a set of dependent tasks on available resources in a multiprocessor
environment which will minimize the makespan and reliability cost. A Nondominated sorting Genetic
AlgorithmII procedure has been developed to get the pareto optimal solutions. NSGAII is a Elitist
Evolutionary algorithm, and it takes the initial parental solution without any changes, in all iteration to
eliminate the problem of loss of some paretooptimal solutions.NSGAII uses crowding distance concept to
create a diversity of the solutions.
Clipping is a handy way to collect and organize the most important slides from a presentation. You can keep your great finds in clipboards organized around topics.
Be the first to comment