Impact of laxity on scheduling with advance reservations in grids

Advance reservations (ARs) were introduced for application level dynamic scheduling of resources in a grid infrastructure. Previous research shows that ARs can meet their objectives but at a significant performance cost. We argue that laxity in the reservation window of an AR can help improve the performance of AR scheduling. Scheduling ARs with laxities is an NP-hard problem and in this paper we briefly discuss our scalable algorithm for AR scheduling. Based on simulation, the paper investigates in detail the effect laxity on the system performance.