TopCluster: A hybrid cluster model to support dynamic deployment in Grid

  • Authors:

  • Gang Chen;Yongwei Wu;Jie Wu;Weimin Zheng

  • Affiliations:

  • Department of Computer Science and Technology, Tsinghua National Laboratory for Information Science and Technology (TNLIST), Tsinghua University, Beijing 100084, China and Research Institute of Ts ...;Department of Computer Science and Technology, Tsinghua National Laboratory for Information Science and Technology (TNLIST), Tsinghua University, Beijing 100084, China and Research Institute of Ts ...;Department of Computer and Information Sciences, Temple University, Philadelphia, PA 119122, United States;Department of Computer Science and Technology, Tsinghua National Laboratory for Information Science and Technology (TNLIST), Tsinghua University, Beijing 100084, China and Research Institute of Ts ...

  • Venue:
  • Journal of Computer and System Sciences
  • Year:
  • 2013

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Abstract

Cluster virtualization is a promising approach to construct customized execution environments for Grid users. However, Virtual-Machine Cluster (VCluster) comes with the cost of the overhead caused by virtual machines, which therefore degrades system performance. In this paper, we propose a novel hybrid cluster model, namely TopCluster. By exploiting a Hybrid Batch System (HyBS) mechanism, TopCluster can flexibly allocate both physical or virtualized resources via a unified front-end. To reduce the overhead caused by the dynamic deployment of virtual machines and applications, we also propose a value-based deployment strategy along with TopCluster. An XML-based Application Deployment Description Language (ADDL) is also newly proposed to describe properties, installation procedure, and configuration operations of applications. A prototype system has been implemented and a series of experiments was conducted to evaluate TopCluster by replaying a real world trace. Results show that TopCluster can averagely generate 24.6% and 46.8% higher system throughput, 26.3% and 110.6% higher resource utility, and 35.1% and 56.1% lower waiting time of jobs than two commonly applied cluster models in Grid: Traditional Physical Cluster (PCluster) and VCluster.