Xianwen Hao

China Mobile Group Design Institute Co. Ltd., Peping, Beijing, China

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Publications (8)1.75 Total impact

  • Tingwei Chen · Hongning Zhu · Yu Dai · Xianwen Hao
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    ABSTRACT: To narrow the scope of rescheduling tasks is one of the effective ways to improve the grid dependent tasks rescheduling efficiency. For how to determine the scope which should improve the efficiency of rescheduling problem as far as possible without affecting the application performance, this paper proposed the rescheduling tasks spread domain concept and its method of computation. Beginning with a minimum tasks set to rescheduling, the computing process is oriented by resource share conflict and data transmission dependent of tasks, and limited by the degree of task to optimize the performance of the whole application. Experimentation results show that static scheduling strategy could maintain the performance advantages compare with the dynamic strategy, thus the efficiency of proposed rescheduling tasks spread domain is validated.
    No preview · Article · Nov 2013 · Applied Mathematics & Information Sciences
  • Xianwen Hao · Yu Dai · Bin Zhang · Tingwei Chen
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    ABSTRACT: The dynamic and heterogeneous nature of grid resources is a great challenge to static scheduling strategies of dependent tasks. A new static scheduling model based on RT-RAG (reduced task-resource assignment graph) and algorithm are proposed which are more suitable for the grid heterogeneity and support unified scheduling/rescheduling process. The (re) scheduling problem based on the model is thus regarded as an optimization selection problem of RT-RAGs. The experimentation shows that the static scheduling algorithm has better adaptability to grid dynamic and heterogeneity and keeps greatly its superiority up in comparison to the dynamic one and it is also better than the AHEFT algorithm based on the DAG task graph model, especially in case of great resources heterogeneity.
    No preview · Article · Jul 2008 · Dongbei Daxue Xuebao/Journal of Northeastern University
  • Xianwen Hao · Yu Dai · Bin Zhang · Tingwei Chen
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    ABSTRACT: This paper focuses on the task migration enabling grid workflow application rescheduling problem, presents a reduced task graph model, and implements a performance oriented rescheduling algorithm based on immune genetic algorithm. The experiment shows that, compared with Adaptive Heterogeneous Earliest Finish Time static rescheduling algorithm and the classical dynamic Max-Min scheduling algorithm, the performance advantage of the proposed rescheduling algorithm is obvious, on the one hand because of the performance contribution of global optimization and task migration, and on the other hand because of the efficiency contribution of task graph reduction and immune genetic algorithm’s convergent speed. It also shows that task migration improves grid application’s adaptability of dynamics further.
    No preview · Chapter · Apr 2008
  • Tingwei Chen · Bin Zhang · Xianwen Hao
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    ABSTRACT: In Grid computing, an application will be decomposed into a set of dependent tasks. In the Grid environment where resources have different capability and resources are interconnected over the world, the dependence among tasks affects the scheduling strategy greatly. This paper uses a Task-Resource Assignment Graph (T-RAG) to represent a potential resource assignment plan. And a dependent tasks scheduling model based on Best Task-Resource Assignment Graph (BT-RAG) construction is proposed which maps the dependent tasks scheduling problem into a graph construction problem. The BT-RAG is obtained and such graph is the optimal scheduling plan which determines the resource assignment plan and the execution order of tasks. Finally, the task scheduling algorithm based on the proposed scheduling model is implemented. Compared with HEFT algorithm, the proposed algorithm shows better performance in the situation of a large body of data transported among tasks.
    No preview · Conference Paper · Jan 2008
  • Tingwei Chen · Bin Zhang · Xianwen Hao
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    ABSTRACT: Studies the task scheduling in grid environment and proposes a task scheduling mechanism, i.e. each and every possible task scheduling scheme is expressed as a task-resource assignment graph, thus converting the task scheduling problem into a graphically optimal selection problem. Then, to find the optimal solution quickly and accurately, a task scheduling algorithm based on immune genetic algorithm is proposed to implement the optimal selection. This algorithm takes the longest path in the task-resource assignment graph as an antigen and every task-resource assignment as a corresponding antibody. Experimental results show that the approach proposed is effective in the capability of global optimization and significantly improves the convergence rate.
    No preview · Article · Mar 2007 · Dongbei Daxue Xuebao/Journal of Northeastern University
  • Tingwei Chen · Bin Zhang · Xianwen Hao · Yu Dai
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    ABSTRACT: Task scheduling is one of the core steps to effectively exploit the capabilities of resources in the grid. The task scheduling problem is an NP-complete problem. This paper studied on the task scheduling problem in grid environment and proposed a task scheduling mechanism, which expressed each possible task scheduling scheme as a task-resource assignment graph (T-RAG) and thus mapped the task scheduling problem into a graph optimal selection problem. Moreover, in order to find the optimal solution quickly and accurately, a task scheduling algorithm based on particle swarm optimization (PSO) was proposed. This algorithm regards the longest path of the task-resource assignment graph as fitness value and encodes every task-resource assignment as a particle. Finally, the experimentation shows that the approach proposed in this paper is effective to solve task scheduling problem
    No preview · Conference Paper · Aug 2006
  • Xianwen Hao · Yu Dai · Bin Zhang · Tingwei Chen · Lei Yang
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    ABSTRACT: The dynamics nature of grid environment brings challenges for applications to offer nontrivial QoS on distributed, heterogeneous resources. It’s a better way to select the suitable grid resources constrained by QoS. In this paper we propose the application QoS model and metrics as the standard of resource selection. We also give consideration of the existence of data dependence between the tasks composing an application and apply it to the QoS model. And we solve the resource selection problem efficiently using novel neural networks.
    No preview · Conference Paper · May 2006
  • Source
    Tingwei Chen · Bin Zhang · Xianwen Hao · Haidong Zheng
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    ABSTRACT: In this paper we presented a novel approach to semantic resource discovery in the Grid, Where different organizations may use different ontologies to describe the resource and application requirements. We do not require a central ontology for resource description and matching. The relation matrix is defined to describe relations between concepts in any two ontologies. Then, a method of rewriting resource queries based on the relation matrix is presented to solve the ontology heterogeneity problem. It rewrites the resource queries in one ontology to approximate queries in another ontology based on the relations between concepts. Machines can process this procedure automatically.
    Full-text · Conference Paper · Jan 2005

Publication Stats

30 Citations
1.75 Total Impact Points

Institutions

  • 2013
    • China Mobile Group Design Institute Co. Ltd.
      Peping, Beijing, China
  • 2006-2008
    • Northeastern University
      Boston, Massachusetts, United States
    • Northeastern University (Shenyang, China)
      • College of Information Science and Engineering
      Feng-t’ien, Liaoning, China