Randomized Testing of Byzantine Fault Tolerant Algorithms

Winter, Levin N.; Buse, Florena; Graaf, Daan de; Gleissenthall, Klaus v.; Ozkan, Burcu Kulahcioglu

doi:10.1145/3586053

Cited by 6 publications

(1 citation statement)

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“…The tuples are replicated on demand using the reactive replication scheme, which provides strong consistency. Winter et al 44 introduced an effective automated testing tool to detect the error in byzantine fault tolerant (BFT) algorithms using randomized testing. The randomized test case generator also detected vulnerability in Practical Byzantine Fault Tolerance (PBFT).…”

Section: Background and Related Workmentioning

confidence: 99%

A Fault‐tolerant model for tuple space coordination in distributed environments

Kirti,

Maurya,

Yadav

2023

Concurrency and Computation

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SummaryIn distributed systems, tuple space is one of the coordination models that significantly maximizes system performance against failure due to its space and time decoupling features. With the growing popularity of distributed computing and increasing complexity in the network, host and link failure occurs frequently, resulting in poor system performance. This article proposes a fault‐tolerant model named Tuple Space Replication (TSR) for tuple space coordination in distributed environments. The model introduces a multi‐agent system that consists of multiple hosts. Each host in a multi‐agent system comprises an agent space with a tuple space for coordination. In this model, we introduce three novel fault‐tolerant algorithms for tuple space primitives to provide coordination among hosts with tolerance to multiple links and hosts failure. The first algorithm is given for out() operation to insert tuples in the tuple space. The second algorithm is presented for rdp() operation to read any tuple from the tuple space. The third algorithm is given for inp() operation to delete or withdraw tuples from the tuple space. These algorithms use less number of messages to ensure consistency in the system. The message complexity of the proposed algorithms is analyzed and found O(n) for out(), O(1) for rdp(), and O(n) for inp() operations which is comparable and better than existing works, where n is the number of hosts. The testbed experiment reveals that the proposed TSR model gives performance improvement up to 88%, 70.94%, and 63.80% for out(), rdp(), and inp() operations compared to existing models such as FT‐SHE, LBTS, DEPSPACE, and E‐DEPSPACE.

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Section: Background and Related Workmentioning

confidence: 99%