Fuzzy logic model for dynamic multiprocessor scheduling

In this paper, we propose a dynamic task scheduling technique based on fuzzy logic. The main objective of the work is to implement load balancing in scheduling tasks on a network of processing elements. The fuzzy engine we propose is capable of processing inputs from incomplete and ambiguous data that arises from the current state of the processors. In the model, an arriving task is placed in a central queue based on the first-come-first-serve rule. When the task is ready to be assigned, its information is passed to the processors for bidding. One processor acts as the global scheduler to monitor the overall activities, while all others have local schedulers for managing their own activities. The latter supplies information on its current state and follows whatever decision given by the former. The two components work together and the global scheduler uses the fuzzy logic mechanism in making decision on the task assignment. Our experimental work shows promising results in achieving the objectiv