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The main purpose of this report is to provide information on Petri nets, including their, design, semantics, properties, and uses. The problem addressed is how to model and analyze systems that may be susceptible to unknown issues. By visualizing these issues, we can improve or modify the system. Petri nets are highly powerful tools that can solve several problems, including issues with workflow management, deadlock, data transmission in communication systems, manufacturing and production, software systems, and more. These things are widely used in different work fields such as engineering, project management, and computer science. It is important to solve these problems for maintaining system reliability, and optimal performance. Exploring all the uses and techniques of a Petri net, beginning with the basics and advancing to the more complex ideas, demonstrates just how effective they are. The results confirm that Petri nets are important for identifying systems that need improvement within their performance and components across multiple fields.
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ADLP: Accountable Data Logging Protocol for Publish-Subscribe Communication Systems
Reasoning about the decision-making process of modern autonomous systems becomes increasingly challenging as their software systems become more inexplicable due to complex data-driven processes. Yet, logs of data production and consumption among the software components can provide useful run-time evidence to analyze and diagnose faulty op- erations. Particularly when the system is run by a number of software components that were individually developed by different parties (e.g., open source, third-party vendor), it is imperative to find out where the problems originated and thus who should be responsible for the problems. However, software components may act unfaithfully or non-cooperatively to make the run-time evidence refutable or unusable. Hence, this paper presents Accountable Data Logging Protocol (ADLP), a mechanism to build accountability into data distribution among software components that are not necessarily cooperative or faithful in reporting the logs of their data production and consumption. We demonstrate an application of ADLP to a miniaturized self-driving car and show that it can be used in practice with at a moderate performance cost.
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- PAR ID:
- 10109072
- Date Published:
- Journal Name:
- IEEE 39th International Conference on Distributed Computing Systems
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/ICDCS.2019.00117
