Applying economic principles to grids is deemed promising to improve the overall value provided by such systems. End users can influence the allocation of resources by reporting valuations for these resources. Current market-based schedulers, however, are static, assume the availability of complete information about jobs (in particular with respect to processing times), and do not make use of the flexibility offered by advanced computing systems. In this paper, we present the implementation of economic resource allocation principles into MOSIX, a state-of-the-art management system for computing clusters and multi-cluster organizational grids. The system is designed so as to be able to work in large-scale settings with selfish agents. Facing incomplete information about jobs' characteristics, it dynamically allocates jobs to computing machines by leveraging preemption and job migration, two distinct features offered by MOSIX. We validate and showcase the behavior of our economic model by means of experiments in the real system.
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