Evolution and Optimum Seeking: The Sixth Generation
Evolution and Optimum Seeking: The Sixth Generation
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
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The subject of this paper is the resource management for a grid system that is primarily intended to support computationally expensive tasks like simulations and optimisations on a grid. Applications are represented as workflows that can be decomposed into single grid jobs. The main task of the resource management is resource brokering to optimise a global schedule for all requesting grid jobs and all requested resources. 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 (EA). Consequently, a global optimising resource broker (GORBA) is proposed that deploys EA. The paper focuses on the concept of GORBA and the implementation of GORBA prototype.