Abstract
This chapter presents a model for independent batch scheduling in Computational Grid that enables the aggregation of security requirements as additional scheduling criteria. Artificial Neural Network (ANN) module is an important component of this model. It is designed for supporting the security-aware evolutionary single- and multi-population grid schedulers. Based on a preliminary analysis of the trust levels of resources and security demand parameters of tasks, the neural network monitors the scheduling and task execution processes and generates the tasks-machines mapping “suggestions” based on the information about resource failures and the resulting tasks and machines characteristics. This information is used by the schedulers for an effective minimization of the scheduling objective function and the improvement of the system throughput.
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© 2012 Springer-Verlag GmbH Berlin Heidelberg
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Kołodziej, J. (2012). Security-Aware Independent Batch Scheduling in Computational Grids. In: Evolutionary Hierarchical Multi-Criteria Metaheuristics for Scheduling in Large-Scale Grid Systems. Studies in Computational Intelligence, vol 419. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28971-2_5
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DOI: https://doi.org/10.1007/978-3-642-28971-2_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28970-5
Online ISBN: 978-3-642-28971-2
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