Multiprocessor Environment Using Genetic Algorithm

Task Scheduling [1] is the allocation of resources over time to perform a collection of tasks. Real -time systems make use of scheduling algorithms to maximize the number of real -time tasks that can be processed without violating timing constraints. A scheduling algorithm provides a schedule for a task set that assigns tasks to processors and provides an ordered list of tasks. The schedule is said to be feasible if the timing constraints of all the tasks are met. Scheduling approaches can be classified according to the arrival time of tasks into static and dynamic and deterministic or stochastic scheduling. Task Scheduling in Multiprocessor is a term that can be stated as finding a schedule for a general task graph to be executed on a multiprocessor system so that the schedule length can be minimized. Task scheduling in multiprocessor systems also known as multiprocessor scheduling. Multiprocessor schedulin g problems can be classified into many different categories based on characteristics of the program and tasks to be scheduled, the multiprocessor system, and the availability of information. Multiprocessor scheduling [2] problems may be divided in two categories: Static and dynamic task scheduling. In this paper we di scuss the Multiprocessor Environment using geneti c Algorithm.