Batch mode scheduling in grid systems

Despite recent advances, grid and P2P systems remain difficult for many users to bring to real-world applications. One difficulty is the lack of schedulers for such systems. In this work, we consider the allocations of jobs to resources using batch mode methods. These methods are able to provide fast planning by exploring characteristics of distributed and highly heterogeneous systems. In evaluating these methods, four parameters of the system are measured: makespan, flowtime, resource utilisation and matching proximity. These methods were tested using the benchmark model of Braun et al. (2001) for distributed heterogeneous systems. Based on the computational results, we evaluate the performance of these methods with regard to the four considered metrics. Also, we evaluate the usefulness of batch methods when grid characteristics, such as degree of consistency of computing and heterogeneity of jobs and resources, are known in advance. We observe that batch mode methods are beneficial to grid scheduling services, for adaptively providing these services according to the grid infrastructure characteristics.