Add to ORKGThe paper proposes using genetic algorithms-based learning classifier system (CS) to solve multiprocessor scheduling problem. After initial mapping tasks of a parallel program into processors of a parallel system, the agents associated with tasks perform migration to nd an allocation providing the minimal execution time of the program. Decisions concerning agents' actions are produced by the CS, upon a presentation by an agent information about its current situation. Results of experimental study of the scheduler are presented
In scheduling, a set of machines in parallel is a setting that is important, from both the theoretic...
Task scheduling is essential for the suitable operation of multiprocessor systems. The aim of task s...
Abstract. The problem of multiprocessor scheduling consists in finding a schedule for a general task...
In this paper we propose an approach to solve multiprocessor scheduling problem with use of rule-bas...
This paper presents the development of genetic algorithm approach to schedule tasks on a multiproces...
The common problem of multiprocessor scheduling can be defined as allocating a task graph in a multi...
We have developed a genetic algorithm (GA) approach to the problem of task scheduling for multiproce...
We have developed a genetic algorithm (GA) approach to the problem of task scheduling for multiproce...
Nowadays, parallel and distributed based environments are used extensively; hence, for using these e...
This research focuses on the development of a learning-based heuristic for scheduling heterogeneous ...
Efficient multiprocessor task scheduling is a long-studied and difficult problem that continues to b...
System is using multiple processors for computing and information processing, is increasing rapidly ...
Multiprocessors have evolved as powerful computing tools for executing dynamic real time tasks. The ...
Multiprocessors have emerged as a powerful computing means for running real-time applications, espec...
This paper investigates parallel machine scheduling problems where the objectives are to minimize to...
In scheduling, a set of machines in parallel is a setting that is important, from both the theoretic...
Task scheduling is essential for the suitable operation of multiprocessor systems. The aim of task s...
Abstract. The problem of multiprocessor scheduling consists in finding a schedule for a general task...
In this paper we propose an approach to solve multiprocessor scheduling problem with use of rule-bas...
This paper presents the development of genetic algorithm approach to schedule tasks on a multiproces...
The common problem of multiprocessor scheduling can be defined as allocating a task graph in a multi...
We have developed a genetic algorithm (GA) approach to the problem of task scheduling for multiproce...
We have developed a genetic algorithm (GA) approach to the problem of task scheduling for multiproce...
Nowadays, parallel and distributed based environments are used extensively; hence, for using these e...
This research focuses on the development of a learning-based heuristic for scheduling heterogeneous ...
Efficient multiprocessor task scheduling is a long-studied and difficult problem that continues to b...
System is using multiple processors for computing and information processing, is increasing rapidly ...
Multiprocessors have evolved as powerful computing tools for executing dynamic real time tasks. The ...
Multiprocessors have emerged as a powerful computing means for running real-time applications, espec...
This paper investigates parallel machine scheduling problems where the objectives are to minimize to...
In scheduling, a set of machines in parallel is a setting that is important, from both the theoretic...
Task scheduling is essential for the suitable operation of multiprocessor systems. The aim of task s...
Abstract. The problem of multiprocessor scheduling consists in finding a schedule for a general task...