事件驱动故障诊断和分区检测(ED-FDPD)算法

Hiteshi Aglawe, P. Bhore, Supriya Kelkar, Radhika Mahajan, Pooja Gambhir
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引用次数: 0

摘要

在分布式计算系统中,故障检测是一个需要自适应和高效的难题。本文提出了一种新的分布式系统事件驱动故障诊断与分区检测(ED-FDPD)算法。ED-FDPD适用于任意拓扑结构。这是一种顺序算法,在每个系统上定期执行,以最少的测试次数检测故障节点。该算法的t-可诊断性为(N-1),其中,N为网络中的节点数。ED-FDPD允许在诊断周期中识别新节点。此外,修复后的故障节点可以在诊断周期内重新进入。系统中可能存在易受攻击的节点,当这些节点出现故障时,可能会在网络中造成分区。这些脆弱节点的检测也被纳入每个诊断周期。即使网络分区后,诊断周期也不会停止。在每个诊断周期结束后,将全网故障节点、无故障节点和脆弱节点信息告知管理员。
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Event Driven Fault Diagnosis and Partition Detection (ED-FDPD) Algorithm
Fault detection in a distributed computing system is a challenge that needs to be adaptive and efficient. Here, a new algorithm, namely "Event Driven Fault Diagnosis and Partition Detection (ED-FDPD) Algorithm for distributed systems" is proposed. ED-FDPD is applicable to any arbitrary topology. This is a sequential algorithm which gets executed periodically on each system to detect faulty nodes with minimum number of tests. The t-diagnosibility of this algorithm is (N-1) where, ‘N’ denotes the number of nodes in the network. ED-FDPD allows new nodes to be recognized in a diagnostic cycle. Also, repaired faulty nodes can reenter during a diagnostic cycle. There may be vulnerable nodes in the system which when becoming faulty can create a partition in the network. Detection of such vulnerable nodes is also incorporated in every diagnostic cycle. The diagnostic cycle does not stop even after the partitioning of the network. Administrator is informed about faulty, fault-free and vulnerable nodes in the entire network after the end of every diagnostic cycle.
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