Decentralized scalable fairshare scheduling

This work addresses Grid fairshare allocation policy enforcement and presents Aequus, a decentralized system for Grid-wide fairshare job prioritization. The main idea of fairshare scheduling is to prioritize users with regard to predefined resource allocation quotas. The presented system builds on three contributions; a flexible tree-based policy model that allows delegation of policy definition, a job prioritization algorithm based on local enforcement of distributed fairshare policies, and a decentralized architecture for non-intrusive integration with existing scheduling systems. The system supports organization of users in virtual organizations and divides usage policies into local and global policy components that are defined by resource owners and virtual organizations. The architecture realization is presented in detail along with an evaluation of the system behavior in an emulated environment. In the evaluation, convergence noise types (mechanisms counteracting policy allocation convergence) are characterized and quantified, and the system is demonstrated to meet scheduling objectives and perform scalably under realistic operating conditions.