Analysing randomized distributed algorithms

被引:0
|
作者
Norman, G [1 ]
机构
[1] Univ Birmingham, Sch Comp Sci, Birmingham B15 2TT, W Midlands, England
关键词
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Randomization is of paramount importance in practical applications and randomized algorithms are used widely, for example in co-ordinating distributed computer networks, message routing and cache management. The appeal of randomized algorithms is their simplicity and elegance. However, this comes at a cost: the analysis of such systems become very complex, particularly in the context of distributed computation. This arises through the interplay between probability and nondeterminism. To prove a randomized distributed algorithm correct one usually involves two levels: classical, assertion-based reasoning, and a probabilistic analysis based on a suitable probability space on computations. In this paper we describe a number of approaches which allows us to verify the correctness of randomized distributed algorithms.
引用
收藏
页码:384 / 418
页数:35
相关论文
共 50 条
  • [31] Algorithms for detecting and analysing autocatalytic sets
    Hordijk, Wim
    Smith, Joshua I.
    Steel, Mike
    ALGORITHMS FOR MOLECULAR BIOLOGY, 2015, 10
  • [32] Analysing distributed processes of provision and innovation
    Coombs, R
    Harvey, M
    Tether, BS
    INDUSTRIAL AND CORPORATE CHANGE, 2003, 12 (06) : 1125 - 1155
  • [33] Robust computation of aggregates in wireless sensor networks: Distributed randomized algorithms and analysis
    Chen, JY
    Pandurangan, G
    Xu, DY
    2005 Fourth International Symposium on Information Processing in Sensor Networks, 2005, : 348 - 355
  • [34] Randomized Gradient-Free Distributed Algorithms through Sequential Gaussian Smoothing
    Chen, Xing-Min
    Gao, Chao
    Zhang, Ming-Kun
    Qin, Yi-Da
    PROCEEDINGS OF THE 36TH CHINESE CONTROL CONFERENCE (CCC 2017), 2017, : 8407 - 8412
  • [35] Randomized algorithms for distributed computation of principal component analysis and singular value decomposition
    Huamin Li
    Yuval Kluger
    Mark Tygert
    Advances in Computational Mathematics, 2018, 44 : 1651 - 1672
  • [36] Robust computation of aggregates in wireless sensor networks: Distributed randomized algorithms and analysis
    School of Electrical and Computer Engineering, Purdue University, Box 165, West Lafayette, IN 47907, United States
    不详
    IEEE Trans Parallel Distrib Syst, 2006, 9 (987-1000):
  • [37] Distributed Randomized PageRank Algorithms Based on Web Aggregation over Unreliable Channels
    Ishii, Hideaki
    Tempo, Roberto
    Bai, Er-Wei
    49TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC), 2010, : 6602 - 6607
  • [38] Robust computation of aggregates in wireless sensor networks: Distributed randomized algorithms and analysis
    Chen, Jen-Yeu
    Pandurangan, Gopal
    Xu, Dongyan
    IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2006, 17 (09) : 987 - 1000
  • [39] Parallel I/O scheduling using randomized, distributed edge coloring algorithms
    Durand, D
    Jain, R
    Tseytlin, D
    JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, 2003, 63 (06) : 611 - 618
  • [40] Randomized algorithms for distributed computation of principal component analysis and singular value decomposition
    Li, Huamin
    Kluger, Yuval
    Tygert, Mark
    ADVANCES IN COMPUTATIONAL MATHEMATICS, 2018, 44 (05) : 1651 - 1672