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In highly heterogeneous and distributed systems, like Grids, it is rather difficult to provide QoS to the users. As reservations of resources may not always be possible, another possible way of enhancing the perceived QoS is by performing meta-scheduling of jobs in advance, where jobs are scheduled some time before they are actually executed. Thank to this, it is more likely that the appropriate resources are available to execute the job when needed. When using this type of scheduling, fragmentation appears and may become the cause of poor resource utilization. Because of that, some techniques are needed to perform rescheduling of tasks that may reduce the existing fragmentation. To this end, knowing the status of the system is a must. However, how to measure and quantify the existing fragmentation in a Grid system is a challenging task. This paper proposes different metrics aiming at measuring that fragmentation not only at resource level but also taking into account all the resources of the Grid environment as a whole. Finally, a performance evaluation of the proposed metrics over a real test bed is presented.