Distributed Systems 2.1: The two generals problem

Summary

In this lecture, we explore system models for distributed systems, focusing on how assumptions impact algorithm design. Using classic thought experiments like the Two Generals and Byzantine Generals problems, the challenges of achieving consensus and certainty in distributed systems are illustrated. These models show how failures like message loss or delayed communication hinder coordination. The lecture also connects these concepts to real-world scenarios, such as online shopping systems, where safeguards like refunds or rechecking transaction statuses resolve uncertainties. Ultimately, the Two Generals problem highlights the fundamental difficulty of ensuring reliable outcomes in distributed systems.

Takeaways

• 😀 Distributed systems are systems where multiple nodes or components communicate and coordinate to perform a task, but they are prone to failures such as network issues and node crashes.
• 😀 System models in distributed systems describe the assumptions made about failure scenarios, such as which types of failures are possible and which are not.
• 😀 The two generals problem illustrates the challenge of coordinating actions (e.g., attack timing) when communication is unreliable, and messages may be lost or delayed.
• 😀 In the two generals problem, the generals cannot be sure if the other general will attack at the same time due to potential message loss, leading to uncertainty in the system.
• 😀 The issue of 'no common knowledge' is central to the two generals problem, where neither party can be certain of the other's intentions, leading to infinite chains of messages with no final agreement.
• 😀 The Byzantine generals problem extends the two generals problem by considering more complex scenarios where messages may be altered or corrupted, introducing even greater uncertainty.
• 😀 In real-world systems like online shopping, similar coordination issues arise, such as ensuring a payment is processed only if the goods are dispatched and vice versa, despite the risk of message loss.
• 😀 Online systems use safeguards such as refunds and re-checking transactions to handle uncertainty and resolve potential issues caused by message failure or delay.
• 😀 Practical distributed systems often rely on second-level safeguards, such as retry mechanisms and fallback strategies, to ensure reliability and correctness in the presence of uncertain communication.
• 😀 The takeaways from the two generals problem and its application to real-world systems highlight the inherent challenges of distributed systems and the need for designing robust, fault-tolerant algorithms.

Q & A

What is the main focus of this lecture?

The main focus of this lecture is to explore system models for distributed systems, which are essential for designing algorithms that can handle failures in a distributed environment.

Why is it important to have precise system models in distributed systems?

System models are crucial because they help designers account for potential failures, such as node crashes or network failures, by specifying the types of failures that are assumed to be possible or impossible.

What are the Two Generals Problem and the Byzantine Generals Problem?

The Two Generals Problem is a thought experiment about two generals trying to coordinate an attack, where message delivery is unreliable. The Byzantine Generals Problem extends this scenario by introducing the possibility of malicious behavior, making it even harder to achieve consensus in a distributed system.

How does the Two Generals Problem illustrate challenges in distributed systems?

The problem illustrates the challenge of uncertainty in communication: if messages are lost, it becomes impossible for the two generals to be certain that they will attack simultaneously, as there is no way to confirm whether messages have been received.

What is the key issue in the Two Generals Problem from the perspective of General One?

The key issue for General One is whether or not they will receive a response from General Two. Without a response, General One cannot be sure whether General Two will attack at the same time.

What are the possible scenarios that could occur when General One sends a message?

Two possible scenarios are: either General One's initial message is received by General Two but the response is lost, or the initial message is lost and never reaches General Two. In both cases, General One does not know whether General Two received the message.

Why can't General One simply attack without waiting for a response from General Two?

If General One attacks without receiving a response, there is a risk that General Two will not attack, leading to failure. Without confirmation from General Two, General One cannot be certain that both armies will coordinate their attack.

How does this problem relate to real-world systems like online shopping?

The Two Generals Problem is similar to the challenge faced by online shops and payment services. The shop wants to dispatch goods only if the payment is successful, but communication failures between the shop and the payment service could result in either goods being shipped without payment or payment being processed without goods being delivered.

How do real-world systems, such as online shops, handle the uncertainty of message delivery?

In practice, systems use safeguards to mitigate the uncertainty. For example, if a payment was charged but the goods were not dispatched, the shop can refund the payment. Alternatively, the shop can check with the payment service later to confirm whether the payment was processed.

What lesson does the Two Generals Problem teach about distributed systems?

The Two Generals Problem teaches that in distributed systems, achieving complete certainty about the status of actions is often impossible due to unreliable communication. Systems must be designed with mechanisms to handle uncertainty, such as retries, timeouts, and failure recovery strategies.