7 research outputs found

    Modelling of user requirements and behaviors in computational grids

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    In traditional distributed computing systems a few user types are found having ratherPeer ReviewedPostprint (published version

    A game-theoretic and hybrid genetic meta-heuristics model for security-assured scheduling of independent jobs in computational grids

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    Scheduling independent tasks in Computational Grids commonly arises in many Grid-enabled large scale applications. Much of current research in this domain is focused on the improvement of the efficiency of the Grid schedulers, both at global and local levels, which is the basis for Grid systems to leverage large computing capacities. However, unlike traditional scheduling, in Grid systems security requirements are very important to scheduling tasks/applications to Grid resources. The objective is thus to achieve efficient and secure allocation of tasks to machines. In this paper we propose a new model for secure scheduling at the Grid sites by combining game-theoretic and genetic-based meta-heuristic approaches. The game-theoretic model takes into account the realistic feature that Grid users usually perform independently of each other. The scheduling problem is then formalized as a noncooperative non-zero sum game with Nash equilibria as the solutions. The game cost function is minimized, at global and user levels, by using four genetic-based hybrid meta-heuristics. We have evaluated the proposed model through a static benchmark of instances, for which we have measured two basic metrics, namely the makespan and flowtime. The obtained results suggest that it is more resilient for the Grid users (and local schedulers) to tolerate some job delays defined as additional scheduling cost due to security requirements instead of taking a risk of allocating at unreliable resources.Peer ReviewedPostprint (published version

    A game-theoretic and hybrid genetic meta-heuristics model for security-assured scheduling of independent jobs in computational grids

    No full text
    Scheduling independent tasks in Computational Grids commonly arises in many Grid-enabled large scale applications. Much of current research in this domain is focused on the improvement of the efficiency of the Grid schedulers, both at global and local levels, which is the basis for Grid systems to leverage large computing capacities. However, unlike traditional scheduling, in Grid systems security requirements are very important to scheduling tasks/applications to Grid resources. The objective is thus to achieve efficient and secure allocation of tasks to machines. In this paper we propose a new model for secure scheduling at the Grid sites by combining game-theoretic and genetic-based meta-heuristic approaches. The game-theoretic model takes into account the realistic feature that Grid users usually perform independently of each other. The scheduling problem is then formalized as a noncooperative non-zero sum game with Nash equilibria as the solutions. The game cost function is minimized, at global and user levels, by using four genetic-based hybrid meta-heuristics. We have evaluated the proposed model through a static benchmark of instances, for which we have measured two basic metrics, namely the makespan and flowtime. The obtained results suggest that it is more resilient for the Grid users (and local schedulers) to tolerate some job delays defined as additional scheduling cost due to security requirements instead of taking a risk of allocating at unreliable resources.Peer Reviewe

    Modelling of user requirements and behaviors in computational grids

    No full text
    In traditional distributed computing systems a few user types are found having ratherPeer Reviewe

    A web interface for meta-heuristics based grid schedulers

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    The use of meta-heuristics for designing efficient Grid schedulers is currently a common approach. One issue related to Grid based schedulers is their evaluation under different Grid configurations, such as dynamics of tasks and machines, task arrival, scheduling policies, etc. In this paper we present a web application that interfaces the final user with several meta-heuristics based Grid schedulers. The application interface facilities for each user the remote evaluation of the different heuristics, the configuration of the schedulers as well as the configuration of the Grid simulator under which the schedulers are run. The simulation results and traces are graphically represented and stored at the server and can retrieved in different formats such as spreadsheet form or pdf files. Historical executions are as well kept enabling a full study of use cases for different types of Grid schedulers. Thus, through this application the user can extract useful knowledge about the behavior of different schedulers by simulating realistic conditions of Grid system without needing to install and configure any specific software.Peer Reviewe
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