  The use of meta-schedulers for resource management in large-scale distributed
systems often leads to a hierarchy of schedulers. In this paper, we discuss why
existing meta-scheduling hierarchies are sometimes not sufficient for Grid
systems due to their inability to re-organise jobs already scheduled locally.
Such a job re-organisation is required to adapt to evolving loads which are
common in heavily used Grid infrastructures. We propose a peer-to-peer
scheduling model and evaluate it using case studies and mathematical modelling.
We detail the DIANA (Data Intensive and Network Aware) scheduling algorithm and
its queue management system for coping with the load distribution and for
supporting bulk job scheduling. We demonstrate that such a system is beneficial
for dynamic, distributed and self-organizing resource management and can assist
in optimizing load or job distribution in complex Grid infrastructures.
