Efficient data synchronization method on integrated computing environment

被引:0
作者
Daeyong Jung
Daewon Lee
Myungil Kim
Jaesung Kim
机构
[1] Korea Institute of Science and Technology Information (KISTI),Department of Supercomputing M&S Technology Development
[2] Seokyeong University,Department of Computer Engineering
[3] KISTI,Supercomputing Modeling and Simulation Center
来源
The Journal of Supercomputing | 2019年 / 75卷
关键词
Cluster computing; Cloud computing; Data synchronization; Integrated computing environment;
D O I
暂无
中图分类号
学科分类号
摘要
To execute scientific applications and simulations of enormous scale, the computing paradigm is evolving into one of cluster computing and cloud computing that can exploit the large number of available computing resources. To maximize the utilization of them, company or research center needs a scheduler engine and its data space to construct a cluster computing environment. However, if certain data space is shared, problems related to the security of node, the network traffic imbalance between nodes, and the data protection could arise. To solve these issues, a manager synchronizing the shared data space for the nodes that constitute a cluster computing environment is designed. The synchronization manager shares data in two ways: First, under the cluster environment, the full synchronization group can mount a specific directory space of the master node via NFS. It is used for the data which can be globally referenced. Second, the partial synchronization group delivers data to assigned workers through rsync. It can be used to locally share data for the isolation. The partial synchronization group is superior to full synchronization group in security and efficiency because data are shared in separate manner. By applying adequate data-sharing method, the designed manager efficiently mediate sharing data as purposed.
引用
收藏
页码:4252 / 4266
页数:14
相关论文
共 17 条
  • [1] Topcuoglu H(2002)Performance-effective and low-complexity task scheduling for heterogeneous computing IEEE Trans Parallel Distrib Syst 13 260-274
  • [2] Hariri S(2005)A taxonomy of scientific workflow systems for grid computing SIGMOD Rec 34 44-49
  • [3] Min-You Wu(2015)A platform based on kanban to build taxonomies and folksonomies for DMS and CSS J Convergence 6 1-8
  • [4] Yu J(2016)A survey of cloud-based network intrusion detection analysis Human-centric Comput Inform Sci 6 19-547
  • [5] Buyya R(2016)A security protection framework for cloud computing J Inf Process Syst 12 538-undefined
  • [6] Buschettu A(undefined)undefined undefined undefined undefined-undefined
  • [7] Sanna D(undefined)undefined undefined undefined undefined-undefined
  • [8] Concas G(undefined)undefined undefined undefined undefined-undefined
  • [9] Pani FE(undefined)undefined undefined undefined undefined-undefined
  • [10] Keegan N(undefined)undefined undefined undefined undefined-undefined