An ant colony optimization (ACO) algorithm is proposed to improve grid resource scheduling, for the performance of grid scheduling affects the applications of grid platform directly. According to the updating rule of local and global pheromone, ACO achieves load balance by incorporating resource-oriented trust mechanism. The evaluation criterion of system safety covers both direct and indirect trust of the resource nodes, thus increasing the reliability and validity of the grid system. The rescheduling mechanism is designed to guarantee the successful task completion at the single node failure, and increase the successful task ratio and fault-tolerant of the grid system.
Published in:
Genetic and Evolutionary Computing, 2009. WGEC '09. 3rd International Conference on
Date of Conference: 14-17 Oct. 2009