Practice Fischer-Lynch-Paterson (FLP) Impossibility Theorem (Extended to Byzantine Faults) - 2.5 | Module 5: Consensus, Paxos and Recovery in Clouds | Distributed and Cloud Systems Micro Specialization
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2.5 - Fischer-Lynch-Paterson (FLP) Impossibility Theorem (Extended to Byzantine Faults)

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What does the FLP Impossibility Theorem state?

πŸ’‘ Hint: Think about the role of process crashes in consensus.

Question 2

Easy

Define Byzantine failures in the context of distributed systems.

πŸ’‘ Hint: Consider how this differs from a crash.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

What does the FLP theorem imply about consensus in distributed systems?

  • Consensus is always achievable
  • Consensus is impossible under certain failure conditions
  • Consensus depends solely on network speed

πŸ’‘ Hint: Recall the conditions that apply to the FLP theorem.

Question 2

True or False: All systems are able to achieve deterministic consensus regardless of failures.

  • True
  • False

πŸ’‘ Hint: Think about the implications of crashes and erroneous behaviors.

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Design a hypothetical asynchronous distributed system with a single Byzantine process. Explain how consensus can still be reached despite the risks and what methods could be employed.

πŸ’‘ Hint: Consider scenarios that allow for consistent communication.

Question 2

Critically assess the effectiveness of probabilistic consensus methods in systems affected by Byzantine failures. What are the potential weaknesses?

πŸ’‘ Hint: Think about the difference between guaranteed and probabilistic results.

Challenge and get performance evaluation