Resource reservations in advance are a mature concept for the allocation of various resources, particularly in grid environments. Common grid tool kits support advance reservations and assign jobs to resources at admission time. In such a distributed environment, it is necessary to develop carefully tailored failure recovery mechanisms that provide seamless transparent migration of jobs from one resource to another. As the migration of running jobs is difficult, an important issue in advance reservation, i.e., planning based, management infrastructures is to determine the duration of a failure in order to remap jobs that are already allocated to a currently failed resource but not yet active. As shown in previous work, underestimations of the failure duration and as a consequence the remapping of too few jobs results in an increased amount of job terminations. In order to overcome this drawback, we propose a load-based computation of the jobs to be remapped. A centralized and a distributed version of the strategy are presented, showing it is not necessary to have knowledge beyond the local allocation on the failed resource. These load-based strategies achieve effective remapping of jobs while avoiding - inevitably inaccurate - estimations of the failure duration.
['Lars-Olof Burchard', 'Barry Linnert', 'Jörg Schneider']
A distributed load-based failure recovery mechanism for advance reservation environments