The bandwidth-aware backup task scheduling strategy using SDN in Hadoop

被引:3
|
作者
Shang, Fengjun [1 ]
Chen, Xuanling [1 ]
Yan, Chenyun [1 ]
Li, Luzhong [1 ]
Zhao, Yuting [1 ]
机构
[1] Chongqing Univ Posts & Telecommun, Coll Comp Sci & Technol, Chongqing 400065, Peoples R China
关键词
Hadoop; Task scheduling; SDN; LATE; MapReduce;
D O I
10.1007/s10586-018-1736-8
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In the era of big data, the traditional capacity of computing and storage has been unable to meet the growing demand. In this case, Cloud Computing technology is emerging. Researching on task scheduling is a way from the perspective of resource allocation and management to improve performance of Hadoop system. In this paper, a speculative task scheduling strategy that based on SDN technology is improved. For LATE mechanism, some slow tasks are slower than speculative tasks. This is not only unable to reduce task turnaround time and a waste of system resources. In this paper, we join the slow task compared with the speculative task for the speculative task scheduling strategy of LATE. Wherein, the run time of speculative tasks contains the input data transfer time, real-time bandwidth corresponding to a bandwidth of the link. Based on this model, we propose a bandwidth-aware speculative task run time estimation model (BWRE) based on SDN, using this model to accurately speculative the backup task run time. And we use SDN to provide bandwidth guarantees for the speculative task. Finally, BWRE is verified by simulation experiments. Evaluation results show that BWRE outperforms the shortening job turnaround time by an average of 9.85%.
引用
收藏
页码:S5975 / S5985
页数:11
相关论文
共 50 条
  • [1] The bandwidth-aware backup task scheduling strategy using SDN in Hadoop
    Fengjun Shang
    Xuanling Chen
    Chenyun Yan
    Luzhong Li
    Yuting Zhao
    [J]. Cluster Computing, 2019, 22 : 5975 - 5985
  • [2] Bandwidth-Aware Scheduling With SDN in Hadoop: A New Trend for Big Data
    Qin, Peng
    Dai, Bin
    Huang, Benxiong
    Xu, Guan
    [J]. IEEE SYSTEMS JOURNAL, 2017, 11 (04): : 2337 - 2344
  • [3] Bandwidth-aware divisible task scheduling for cloud computing
    Lin, Weiwei
    Liang, Chen
    Wang, James Z.
    Buyya, Rajkumar
    [J]. SOFTWARE-PRACTICE & EXPERIENCE, 2014, 44 (02): : 163 - 174
  • [4] Bandwidth-Aware Data Placement Scheme for Hadoop
    Shabeera, T. P.
    Kumar, Madhu S. D.
    [J]. 2013 IEEE RECENT ADVANCES IN INTELLIGENT COMPUTATIONAL SYSTEMS (RAICS), 2013, : 64 - 67
  • [5] Bandwidth-aware energy efficient flow scheduling with SDN in data center networks
    Xu, Guan
    Dai, Bin
    Huang, Benxiong
    Yang, Jun
    Wen, Sheng
    [J]. FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2017, 68 : 163 - 174
  • [6] Bandwidth-aware multi round task scheduling algorithm for cloud computing
    Zhao, Tong
    Jing, Mei
    [J]. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2016, 31 (02) : 1053 - 1063
  • [7] BAHS: A Bandwidth-Aware Heterogeneous Scheduling Approach for SDN-based Cluster Systems
    Shen, Jingyun
    Luo, Zheng
    Wu, Chentao
    Li, Jie
    [J]. 2017 15TH IEEE INTERNATIONAL SYMPOSIUM ON PARALLEL AND DISTRIBUTED PROCESSING WITH APPLICATIONS AND 2017 16TH IEEE INTERNATIONAL CONFERENCE ON UBIQUITOUS COMPUTING AND COMMUNICATIONS (ISPA/IUCC 2017), 2017, : 638 - 645
  • [8] FAVE: Bandwidth-aware Failover in Virtualized SDN for Clouds
    Jin, Heesang
    Yang, Gyeongsik
    Yu, Bong-yeol
    Yoo, Chuck
    [J]. 2019 IEEE 12TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING (IEEE CLOUD 2019), 2019, : 505 - 507
  • [9] A Bandwidth-Aware Scheduling Strategy for P2P-TV Systems
    da Silva, Ana Paula Couto
    Leonardi, Emilio
    Mellia, Marco
    Meo, Michela
    [J]. P2P'08: EIGHTH INTERNATIONAL CONFERENCE ON PEER-TO-PEER COMPUTING, PROCEEDINGS, 2008, : 279 - 288
  • [10] On Mitigating Memory Bandwidth Contention through Bandwidth-Aware Scheduling
    Xu, Di
    Wu, Chenggang
    Yew, Pen-Chung
    [J]. PACT 2010: PROCEEDINGS OF THE NINETEENTH INTERNATIONAL CONFERENCE ON PARALLEL ARCHITECTURES AND COMPILATION TECHNIQUES, 2010, : 237 - 247