Evolution and Optimum Seeking: The Sixth Generation
Evolution and Optimum Seeking: The Sixth Generation
Evaluation of Job-Scheduling Strategies for Grid Computing
GRID '00 Proceedings of the First IEEE/ACM International Workshop on Grid Computing
HyGLEAM - An Approach to Generally Applicable Hybridization of Evolutionary Algorithms
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
GLEAM - A System for Simulated `Intuitive Learning'
PPSN I Proceedings of the 1st Workshop on Parallel Problem Solving from Nature
Condor and preemptive resume scheduling
Grid resource management
Discovering performance bounds for grid scheduling by using evolutionary multiobjective optimization
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Tackling the grid job planning and resource allocation problem using a hybrid evolutionary algorithm
PPAM'07 Proceedings of the 7th international conference on Parallel processing and applied mathematics
Solving scheduling problems in grid resource management using an evolutionary algorithm
ODBASE'06/OTM'06 Proceedings of the 2006 Confederated international conference on On the Move to Meaningful Internet Systems: CoopIS, DOA, GADA, and ODBASE - Volume Part II
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The present contribution shall illustrate the necessity of planning and optimising resource allocation in a grid. Requirements to be met by a resource management system will be defined. These requirements are comparable with the requirements on planning systems in other fields, e.g. production planning systems. Here, various methods have already been developed for optimised planning. Suitable methods are Evolutionary Algorithms. Based on an example from the field of production planning, the performance of these methods is demonstrated and use in the GORBA resource broker shall be described.