Scheduling Algorithms Based on Resource Fragmentation for Advance Reservation Tasks

Abstract

Advance reservation is an important method to guarantee the quality of service in Grid-like distributed systems. However, reserved jobs will make resource into fragments and decrease utilization. In order to minimize the negative effects of advance reservations, the authors analyzed the generation of resource fragments during reservation and investigated their influence on advance reservation requests in a quantitative way. Based on the quantification, two new scheduling algorithms, Resource Fragment-aware Best Fit (FSB) and Resource Fragment-aware Worst Fit (FSW), were proposed and their performances were investigated via comprehensive simulations. In simulation, mean job size, deadline factor, system load and sever number were chosen as control factors, and the performances of the algorithms were analyzed in terms of job acceptance rate, resource utilization and slowdown. We also compared FSB and FSW with Best Fit, First Fit, Min_LIP and Min_TIP. The simulations show that FSW and FSB can provide higher job acceptance rate, especially under heavy system load.