A convergence algorithm to help enhance the performance of distributed systems on large networks

被引:7
|
作者
Wong, AKY [1 ]
Wong, JHC [1 ]
机构
[1] Hong Kong Polytech Univ, Dept Comp, Hong Kong, Peoples R China
关键词
large networks; communication channel; mean message response time; convergence algorithm; Central Limit Theorem; and flush limit;
D O I
10.1109/ISPAN.1999.778956
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The proposed convergence algorithm quickly and accurately predicts the mean message response time of a communication channel. From the predicted value the correct window size of the desired percentage of time-out tolerance in message transmission and response can be computed. A correct window size is a necessity for reducing excessive message retransmissions caused by time-outs. The convergence algorithm is particularly useful for enhancing the performance of time-critical distributed applications running on large networks such as the Internet. Prolonged delays in message response in these systems may lead to fatal errors. The discussion in this paper concentrates mainly on the theory and verification of the convergence algorithm. The simulation results have confirmed that the proposed algorithm is indeed a cost/effective solution for enhancing system performance. The simplicity of the convergence algorithm makes it worthwhile for practical implementation in real systems.
引用
收藏
页码:302 / 307
页数:6
相关论文
共 50 条
  • [1] Convergence algorithm to help enhance the performance of distributed systems on large networks
    Wong, Allan K.Y.
    Wong, Joseph H.C.
    Proceedings of the International Symposium on Parallel Architectures, Algorithms and Networks, I-SPAN, 1999, : 302 - 307
  • [2] A convergence algorithm for enhancing the performance of distributed applications running on sizeable networks
    Wong, AKY
    Wong, JHC
    COMPUTER SYSTEMS SCIENCE AND ENGINEERING, 2001, 16 (04): : 229 - 236
  • [3] Performance Evaluation of Distributed Energy Resource Management Algorithm in Large Distribution Networks
    Wang, Jing
    Huang, Jianqiao
    Zhou, Xinyang
    2021 IEEE POWER & ENERGY SOCIETY GENERAL MEETING (PESGM), 2021,
  • [4] Convergence of Distributed Accelerated Algorithm Over Unbalanced Directed Networks
    Li, Huaqing
    Lu, Qingguo
    Chen, Guo
    Huang, Tingwen
    Dong, Zhaoyang
    IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 51 (08): : 5153 - 5164
  • [5] Fast convergence distributed power control algorithm for WCDMA systems
    Lv, L
    Zhu, S
    Dong, S
    IEE PROCEEDINGS-COMMUNICATIONS, 2003, 150 (02): : 134 - 140
  • [6] Analysis of convergence performance of neural networks ranking algorithm
    Zhang, Yongquan
    Cao, Feilong
    NEURAL NETWORKS, 2012, 34 : 65 - 71
  • [7] Enhance performance of centroid algorithm in wireless sensor networks
    Chen, Min
    Liu, Hui
    Proceedings - 4th International Conference on Computational and Information Sciences, ICCIS 2012, 2012, : 1066 - 1068
  • [8] Convergence Analysis of Consensus based Distributed Filtering Algorithm in Sensor Networks
    Zhang Ya
    Tian Yu-Ping
    Cai Jun
    2015 34TH CHINESE CONTROL CONFERENCE (CCC), 2015, : 7592 - 7597
  • [9] Quantized Distributed Gradient Tracking Algorithm With Linear Convergence in Directed Networks
    Xiong, Yongyang
    Wu, Ligang
    You, Keyou
    Xie, Lihua
    IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2023, 68 (09) : 5638 - 5645
  • [10] Performance evaluation of communication networks for distributed systems
    Bitam, Melha
    Alla, Hassane
    INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY, 2006, 25 (04) : 218 - 226