NASA Technical Reports Server (Ntrs) 20030071083: Monitoring and Modeling Performance of Communications in computational grids by NASA Technical Reports Server (Ntrs); published by
NASA Technical Reports Server (Ntrs) 20030071083: Monitoring and Modeling Performance of Communications in computational grids by NASA Technical Reports Server (Ntrs); published by
NASA Technical Reports Server (Ntrs) 20020052408: a System for Monitoring and Management of computational grids by NASA Technical Reports Server (Ntrs); published by
NASA Technical Reports Server (Ntrs) 20020052408: a System for Monitoring and Management of computational grids by NASA Technical Reports Server (Ntrs); published by
NASA Technical Reports Server (Ntrs) 20110023966: Software for Refining or Coarsening computational grids by NASA Technical Reports Server (Ntrs); published by
NASA Technical Reports Server (Ntrs) 20110023966: Software for Refining or Coarsening computational grids by NASA Technical Reports Server (Ntrs); published by
NASA Technical Reports Server (Ntrs) 20020044137: Nas Grid Benchmarks: a Tool for Measuring Performance of computational grids by NASA Technical Reports Server (Ntrs); published by
NASA Technical Reports Server (Ntrs) 20020044137: Nas Grid Benchmarks: a Tool for Measuring Performance of computational grids by NASA Technical Reports Server (Ntrs); published by
To achieve high quality of service (QoS) on computational grids, the QoS-aware job scheduling is investigated for a hierarchical decentralized grid architecture that consists of multilevel schedulers. An integrated ...
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To achieve high quality of service (QoS) on computational grids, the QoS-aware job scheduling is investigated for a hierarchical decentralized grid architecture that consists of multilevel schedulers. An integrated QoS-aware job dispatching policy is proposed, which correlates priorities of incoming jobs used for job selecting at the local scheduler of the grid node with the job dispatching policies at the global scheduler for computational grids. The stochastic high-level Petri net (SHLPN) model of a two-level hierarchy computational grid architecture is presented, and a model refinement is made to reduce the complexity of the model solution. A performance analysis technique based on the SHLPN is proposed to investigate the QoS-aware job scheduling policy. Numerical results show that the QoS-aware job dispatching policy outperforms the QoS-unaware job dispatching policy in balancing the high-priority jobs, and thus enables priority-based QoS.
Fault tolerance is an important property in computational grids since the resources are geographically distributed. Job checkpointing is one of the most common utilized techniques for providing fault tolerance in comp...
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Fault tolerance is an important property in computational grids since the resources are geographically distributed. Job checkpointing is one of the most common utilized techniques for providing fault tolerance in computational grids. The efficiency of checkpointing depends on the choice of the checkpoint interval. Inappropriate checkpointing interval can delay job execution. In this paper, a fault-tolerant scheduling system based on checkpointing technique is presented and evaluated. When scheduling a job, the system uses both average failure time and failure rate of grid resources combined with resources response time to generate scheduling decisions. The system uses the failure rate of the assigned resources to calculate the checkpoint interval for each job. Extensive simulation experiments are conducted to quantify the performance of the proposed system. Experiments have shown that the proposed system can considerably improve throughput, turnaround time, grid load and failure tendency of computational grids.
computational grids (CGs) aim to offer pervasive access to a diverse collection of geographically distributed resources owned by different serf-interested agents or organizations. These agents may manipulate the res...
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computational grids (CGs) aim to offer pervasive access to a diverse collection of geographically distributed resources owned by different serf-interested agents or organizations. These agents may manipulate the resource allocation algorithm in their own benefit, and their selfish behavior may lead to severe performance degradation and poor efficiency. In this paper, game theory is introduced to solve the problem of barging for resource collection in heterogeneous distributed systems. By using the Cournot model that is an important model in static and complete information games, the algorithm is optimized in order to maximize the benefit. It can be seen that the approach is more suitable to the real situation and has practical use. Validity of the solutions is shown.
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 sc...
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ISBN:
(纸本)9781424459179;9780769539676
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.
作者:
Yves CaniouGhislain CharrierFrédéric DesprezUniversité de Lyon
allée d'Italie Lyon Cedex France and UCBL and CNRS (Jfli) Laboratoire de l'Informatique du Parallélisme (LIP) ÉNS Lyon Lyon Cedex France Université de Lyon
Lyon Cedex France and INRIA ÉNS Lyon Lyon Cedex France Université de Lyon
allée d'Italie Lyon Cedex France and INRIA Laboratoire de l'Informatique du Parallélisme (LIP) ÉNS Lyon allée d'Italie Lyon Cedex France
Grid services often consist of remote sequential or rigid parallel application executions. However, moldable parallel applications, linear algebra solvers for example, are of great interest but requires dynamic tuning...
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ISBN:
(纸本)9781920682989
Grid services often consist of remote sequential or rigid parallel application executions. However, moldable parallel applications, linear algebra solvers for example, are of great interest but requires dynamic tuning which has mostly to be done interactively if performances are needed. Thus, their grid execution depends on a remote and transparent submission to a possibly different batch scheduler on each site, and means an automatic tuning of the job according to the local *** this paper we study the benefits of having a middleware able to automatically submit and reallocate requests from one site to another when it is also able to configure the services by tuning their number of processors and their walltime. In this context, we evaluate the benefits of such mechanisms on two multi-cluster Grid setups, where the platform is either composed of several heterogeneous dedicated clusters, or non dedicated ones. Different scenarios are explored using simulations of real cluster traces from different *** show that a simple method is good and often the best. Indeed, it is faster and thus can take more jobs into account while having a small execution time. Moreover, users can expect more jobs finishing sooner and a gain on the average job response time between 10% and 40% in most cases if this reallocation mechanism combined to auto-tuning capabilities is implemented in a Grid framework. The implementation and the maintenance of this heuristic coupled to the migration mechanism in a Grid middleware is also simpler because less transfers are involved.
Managing resources in large scale distributed systems -"computational grids", is a complex and time sensitive process. The computational resources being shared vary in type and complexity, and resource prope...
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ISBN:
(纸本)0909925828
Managing resources in large scale distributed systems -"computational grids", is a complex and time sensitive process. The computational resources being shared vary in type and complexity, and resource properties can change over time. An approach based on interacting software agents is presented, where each resource manager and resource requester is modelled as a BDI (Belief-Desire-Intention) agent. The proposed approach can help resolve conflicts that arise during resource discovery and application scheduling, and enables site autonomy to be maintained. The modelling and detection of conflicts is important in the context of this work, to enable each resource and application to respond to changes in the environment. We propose a BDI based framework that can be used to model agents that represent resources and applications - and outline properties that each must maintain.
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