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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/78770

    Title: Eventual strong consensus with fault detection in the presence of dual failure mode on processors under dynamic networks
    Authors: Cheng, Chien-Fu;Tsai, Kuo-Tang
    Contributors: 淡江大學資訊工程學系
    Keywords: Distributed system;Fault-tolerant;Strong consensus;Fault detection;Early stopping;Dynamic network
    Date: 2012-07-01
    Issue Date: 2012-10-22 10:22:36 (UTC+8)
    Publisher: London: Academic Press
    Abstract: The fault tolerance capability and reliability of a distributed system can be enhanced if the Strong Consensus (SC) problem can be properly addressed. Most of the extant SC protocols are designed for static networks. Besides, the number of rounds of message exchange required by all of the extant SC protocols is determined by the total number of processors in the network rather than by the actual number of faulty processors in the network. Even if there is only a few or no faulty processor in the network, the SC protocols may waste a lot of time and memory space on many unnecessary rounds of message exchange. Thus, this paper revisits the SC problem in dynamic networks and uses two rules, Detection Rule for Malicious fault in dynamic network (DRMdyn) and Early Stopping Rule for Strong Consensus protocol in dynamic networks (ESRSCdyn), to reduce the time consumption and space complexity of SC protocols. DRMdyn is a rule that detects malicious processors, and ESRSCdyn is a rule that determines whether the messages collected are enough for reaching a strong consensus. To be succinct, the proposed SC protocol can not only work in dynamic networks consisting of both dormant processors and malicious processors (dual failure mode) but also ensure that all correct processors reach a SC value within fewer rounds of message exchange than required by the extant SC protocols.
    Relation: Journal of Network and Computer Applications 35(4), pp.1260–1276
    DOI: 10.1016/j.jnca.2012.01.011
    Appears in Collections:[Graduate Institute & Department of Computer Science and Information Engineering] Journal Article

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