A trust model-based task scheduling algorithm for data-intensive application

被引:2
|
作者
Xu Y. [1 ]
Qu W. [1 ]
机构
[1] College of Information Science and Technology, Dalian Maritime University, Dalian
来源
Proceedings - 2011 6th Annual ChinaGrid Conference, ChinaGrid 2011 | 2011年
关键词
data-intensive; Min-Min; task scheduling; trust;
D O I
10.1109/ChinaGrid.2011.16
中图分类号
学科分类号
摘要
With the increase of data-intensive application, the amount of data that the task requires becomes much larger and the task scheduling performance is greatly affected by the data transfer overhead. In grid, establishing trust model is considered to be an important measure of improving the grid security. Therefore, considering the two problems above, this paper improves the Min-Min algorithm and proposes trust model-based Min-Min scheduling algorithm. This algorithm consists of three phases: data file selecting, task scheduling and data scheduling. Two salient features of this algorithm are: 1) in selecting task-required data files, it considers file server's trust degree and data transmission time, it selects the data file with bigger trust value and smaller data transmission time, 2) in data transmission time calculating and transmission path selecting, it adopts the shortest path algorithm-Dijkstra. The experiment results show that although this scheduling algorithm extends the task completion time, the success rate of task execution is apparently raised. © 2011 IEEE.
引用
收藏
页码:227 / 233
页数:6
相关论文
共 50 条
  • [1] A hybrid evolutionary algorithm for task scheduling and data assignment of data-intensive scientific workflows on clouds
    Teylo, Luan
    de Paula, Ubiratam
    Frota, Yuri
    de Oliveira, Daniel
    Drummond, Lucia M. A.
    FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2017, 76 : 1 - 17
  • [2] A Data-Intensive Workflow Scheduling Algorithm for Grid Computing
    Xu, Meng
    Cui, Lizhen
    Wang, Haiyang
    Bi, Yanbing
    Bian, Ji
    FOURTH CHINAGRID ANNUAL CONFERENCE, PROCEEDINGS, 2009, : 110 - 115
  • [3] Data-Intensive Task Scheduling for Heterogeneous Big Data Analytics in IoT System
    Li, Xin
    Wang, Liangyuan
    Abawajy, Jemal H.
    Qin, Xiaolin
    Pau, Giovanni
    You, Ilsun
    ENERGIES, 2020, 13 (17)
  • [4] A novel scheduling algorithm for data-intensive workflow in virtualised clouds
    Li F.
    International Journal of Networking and Virtual Organisations, 2019, 20 (03) : 284 - 300
  • [5] Approximation algorithms and heuristics for task scheduling in data-intensive distributed systems
    Povoa, Marcelo G.
    Xavier, Eduardo C.
    INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH, 2018, 25 (05) : 1417 - 1441
  • [6] Deadline based scheduling for data-intensive applications in clouds
    Fu Xiong
    Cang Yeliang
    Zhu Lipeng
    Hu Bin
    Deng Song
    Wang Dong
    The Journal of China Universities of Posts and Telecommunications, 2016, (06) : 8 - 15
  • [7] Disk Cache-Aware Task Scheduling For Data-Intensive and Many-Task Workflow
    Tanaka, Masahiro
    Tatebe, Osamu
    2014 IEEE INTERNATIONAL CONFERENCE ON CLUSTER COMPUTING (CLUSTER), 2014, : 167 - 175
  • [8] A New Data-Intensive Task Scheduling in OptorSim, an Open Source Grid Simulator
    Moghadam, Mahshid Helali
    Babamir, Seyyed Morteza
    2016 2ND INTERNATIONAL CONFERENCE ON OPEN SOURCE SOFTWARE COMPUTING (OSSCOM), 2016,
  • [9] Algorithm of Scheduling for Data-intensive Computing Operations onto GPU Cluster
    Tang X.-C.
    Zhu Z.-Y.
    Mao A.-Q.
    Fu Y.
    Li Z.-H.
    Ruan Jian Xue Bao/Journal of Software, 2022, 33 (12): : 4429 - 4451
  • [10] A Trust Evaluation Mechanism for Collaboration of Data-Intensive Services in Cloud
    Huang, Longtao
    Deng, Shuiguang
    Li, Ying
    Wu, Jian
    Yin, Jianwei
    Li, Gexin
    APPLIED MATHEMATICS & INFORMATION SCIENCES, 2013, 7 : 121 - 129