• 中国精品科技期刊
  • CCF推荐A类中文期刊
  • 计算领域高质量科技期刊T1类
Advanced Search
Li Lei, Wang Huaimin, and Shi Dianxi. A High Performance Total Order Broadcast Algorithm[J]. Journal of Computer Research and Development, 2007, 44(9): 1449-1455.
Citation: Li Lei, Wang Huaimin, and Shi Dianxi. A High Performance Total Order Broadcast Algorithm[J]. Journal of Computer Research and Development, 2007, 44(9): 1449-1455.

A High Performance Total Order Broadcast Algorithm

More Information
  • Published Date: September 14, 2007
  • Total order broadcast is an important group communication primitive for building fault-tolerant distributed applications, and it guarantees that all members in a communication group receive messages in the same order even if some members are faulty. The existing total order broadcast algorithms can not achieve both low latency and high throughput at the same time, and lack adaptability for the communication patterns of applications, and thus they are not suitable for high performance computing environments. In analyzed in this paper are the ordering mechanisms in some existing typical algorithms, and the key factors that affect the performance of total order broadcast algorithms are pointed out. Then a novel algorithm is proposed, which builds the total order using the leader/followers pattern and is driven by block detection mechanism. It works as follows: each group member can send messages at any time, but only messages from the current leader are delivered, and if the leader remains inactive, it will issue a special request to change the leadership to one of the active follower members. Simulation experiments are performed and the results show that the new algorithm achieves good performance in terms of both latency and throughput, and is much more efficient under bursty message arrival pattern.
  • Related Articles

    [1]An Zhongqi, Zhang Yunyao, Xing Jing, Huo Zhigang. Optimization of the Key-Value Storage System Based on Fused User-Level I/O[J]. Journal of Computer Research and Development, 2020, 57(3): 649-659. DOI: 10.7544/issn1000-1239.2020.20180799
    [2]An Zhongqi, Du Hao, Li Qiang, Huo Zhigang, Ma Jie. Memcached Optimization on High Performance I/O Technology[J]. Journal of Computer Research and Development, 2018, 55(4): 864-874. DOI: 10.7544/issn1000-1239.2018.20160890
    [3]Yang Lipeng, Che Yonggang. HDF5 Based Parallel I/O Techniques for Multi-Zone Structured Grids CFD Applications[J]. Journal of Computer Research and Development, 2015, 52(4): 861-868. DOI: 10.7544/issn1000-1239.2015.20131920
    [4]Wang Zhan, Cao Zheng, Liu Xiaoli, Su Yong, Li Qiang, An Xuejun, Sun Ninghui. A Multi-Root I/O Resource Pooling Method Based on Single-Root I/O Virtualization[J]. Journal of Computer Research and Development, 2015, 52(1): 83-93. DOI: 10.7544/issn1000-1239.2015.20131182
    [5]Wang Jianzong, Chen Yanjun, Xie Changsheng. Research on I/O Resource Scheduling Algorithms for Utility Optimization Towards Cloud Storage[J]. Journal of Computer Research and Development, 2013, 50(8): 1657-1666.
    [6]Li Mingqiang and Shu Jiwu. A Survey of Studies on Self-Similarity in I/O Workloads[J]. Journal of Computer Research and Development, 2008, 45(6).
    [7]Chen Yongran, Qi Xingyun, and Dou Wenhua. A Performance Model of I/O-Intensive Parallel Applications[J]. Journal of Computer Research and Development, 2007, 44(4): 707-713.
    [8]Xia Nan, Zhang Yaoxue, Yang Shanlin, Wang Xiaohui. IOMan: An I/O Management Method Supporting Multi-OS Remote Boot and Running[J]. Journal of Computer Research and Development, 2007, 44(2): 317-325.
    [9]Tang Jianqi, Fang binxing, Hu Mingzeng, and Wang Wei. Research on I/O Optimizations in Out-of-Core Computation[J]. Journal of Computer Research and Development, 2005, 42(10): 1820-1825.
    [10]Cao Qiang and Xie Changsheng. Applying Aggregate I/O to Improve Performance of Network Storage[J]. Journal of Computer Research and Development, 2005, 42(4): 544-550.

Catalog

    Article views (799) PDF downloads (838) Cited by()

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return