Algoritmos de escalonamento gangue com estratégias de migracão em um ambiente MCMCA

Abstract

Over the past decade, the fast advance of network technologies, hardware and middleware, as well as software resource sophistication has contributed to the emergence of new computational models. Consequently, there was a capacity increasing for efficient and effective use of resources distributed aiming to integrate them, in order to provide a widely distributed environment, which computational capacity could be used to solve complex computer problems. The two most challenging aspects of distributed systems are resource management and task scheduling. This work contributes to minimize such problems by (i) the use of migration techniques; (ii) implementing a multicore multicluster simulation environment with mechanisms for load balancing with the purpose of analyzing the system in different contexts; (iii) plus, the gang scheduling implementation algorithms will be analyzed through the use of metrics, in order to measure the schedulers performance in different situations. Thus, the results showed a better use of resources, implying operating costs reduction.