Multi-agent Based Simulations of Block-Free Distributed Ledgers

Bottone, Michele; Raimondi, Franco; Primiero, Giuseppe

doi:10.1109/waina.2018.00149

Cited by 19 publications

(7 citation statements)

References 5 publications

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“…The results indicate that agents with low latency and high connection degrees have a higher probability of having their transactions accepted in the network. Another multi-agent tangle simulator [98] built with NetLogo simulates both random uniform and MCMC tip selection in a visualized and interactive way.…”

Section: ) Dagsimmentioning

confidence: 99%

Performance Evaluation of Blockchain Systems: A Systematic Survey

et al. 2020

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Blockchain has been envisioned to be a disruptive technology with potential for applications in various industries. As more and more different blockchain platforms have emerged, it is essential to assess their performance in different use cases and scenarios. In this paper, we conduct a systematic survey on the blockchain performance evaluation by categorizing all reviewed solutions into two general categories, namely, empirical analysis and analytical modelling. In the empirical analysis, we comparatively review the current empirical blockchain evaluation methodologies, including benchmarking, monitoring, experimental analysis and simulation. In analytical modelling, we investigate the stochastic models applied to performance evaluation of mainstream blockchain consensus algorithms. Through contrasting, comparison and grouping different methods together, we extract important criteria that can be used for selecting the most suitable evaluation technique for optimizing the performance of blockchain systems based on their identified bottlenecks. Finally, we conclude the survey by presenting a list of possible directions for future research.

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Section: ) Dagsimmentioning

confidence: 99%

Performance Evaluation of Blockchain Systems: A Systematic Survey

et al. 2020

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“…While semantic approaches and constraints on sharing abilities of online platforms are difficult and inconvenient, such a method would focus on determining which information sources are most trustworthy, by reasoning on their knowledgeability, popularity and reputation. This model can be further implemented in a distributed ledger structure for trustworthiness assessment in public debates, developing the DAG structure considered in Bottone, Raimondi, and Primiero (2018). The blockchain technology seems not to have yet been tested in this context.…”

Section: Discussionmentioning

confidence: 99%

A logic of negative trust

Primiero

2020

Journal of Applied Non-Classical Logics

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We present a logic to model the behaviour of an agent trusting or not trusting messages sent by another agent. The logic formalizes trust as a consistency checking function with respect to currently available information. Negative trust is modelled in two forms: distrust as the rejection of incoming inconsistent information; mistrust, as revision of previously held information becoming undesirable in view of new incoming inconsistent information, which the agent wishes to accept. We provide a natural deduction calculus, a relational semantics and prove soundness and completeness results. We overview a number of applications which have been investigated for the proof-theoretical formulation of the logic. Consider the following modified example: Example 1.5 (Intentional Untrust Multiplication). Alice does not trust φ from Bob: she believes he sends her intentionally false information. Bob does not trust ¬φ from Carol: he believes she sends him intentionally false information. Assume Alice is aware of that, should she trust ¬φ from Carol? The question whether Alice is safe in assuming the original ¬φ to be valid is now specified more precisely, and the related epistemic action of distrust, reformulating the previous notion from Definition 1.2, has the following intuitive semantics: Definition 1.3 (Distrust). If Alice reads φ from Bob, and φ is inconsistent with Alice's profile, Alice distrusts φ and writes ¬φ. A distinct case for trust misplacement can be formulated as follows: Example 1.6 (Unintentional Untrust Multiplication). Alice reads φ from Bob, false in view of her current information: she believes she has unintentionally held false information ¬φ. Bob has received φ from Carol, who can confirm it to Alice. Should Alice trust φ from Carol? This operation has an intuitive semantic meaning which underpins an act of trust (of the new information) but leads to an act of negative trust (of the old information held): Definition 1.4 (Mistrust). If Alice reads φ from Bob, φ is inconsistent with Alice's profile and Alice wants to maintain consistency, then she mistrusts ¬φ. To accept or reject such contradicting information (i.e, to distrust or mistrust the received information) might depend on the number and role of other agents available for confirmation, or from selected parameters.

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“…The analysis results reveled that agents (play a similar role as miners) with lower latency and higher connection degrees exhibit higher chances that their trans-actions will be accepted by the network. Another multiagent tangle simulator [125] is developed in collaboration with NetLogo. It simulates random uniform as well as Markov Chain Monte Carlo (MCMC) tip selection, while providing visuals (i.e., GUI) and an interactive experience during simulation.…”

Section: B Performance Testingmentioning

confidence: 99%

Blockchain Testing: Challenges, Techniques, and Research Directions

Lal¹,

Marijan²

2021

Preprint

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Specific testing solutions targeting blockchain-based software are gaining huge attention as blockchain technologies are being increasingly incorporated into enterprise systems. As blockchain-based software enters production systems, it is paramount to follow proper engineering practices, to ensure the required level of testing, and assess the readiness of the developed system. The existing research aims at addressing the testing related issues and challenges of engineering blockchain-based software by providing suitable techniques and tools. However, like any emerging discipline, the best practices and tools for testing blockchain-based systems are not yet sufficiently developed. In this paper, we provide a comprehensive survey on testing of Blockchain-based Applications (BC-Apps). First, we provide a discussion on identified challenges that are associated with BC-App testing. Second, we use a layered approach to discuss the state-of-the-art testing efforts in the area of BC technologies. In particular, we present an overview of the existing testing tools and techniques that provide testing solutions either for different components at various layers of the BC-App stack or across the whole stack. Third, we provide a set of future research directions based on the identified BC testing challenges and gaps in the literature review of existing testing solutions for BC-Apps. Moreover, we reflect on the specificity of BC-based software development procedure, which makes some of the existing tools or techniques inadequate, and call for the definition of standardised testing procedures and techniques for BC-Apps. The aim of our study is to highlight the importance of BC-based software testing and to pave the way for a disciplined, testable, and verifiable BC software development.

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Multi-agent Based Simulations of Block-Free Distributed Ledgers

Cited by 19 publications

References 5 publications

Performance Evaluation of Blockchain Systems: A Systematic Survey

Performance Evaluation of Blockchain Systems: A Systematic Survey

A logic of negative trust

Blockchain Testing: Challenges, Techniques, and Research Directions

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