Is Consensus Really Universal?: Difference between revisions

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Created page with "Title: Is Consensus Really Universal? Research Question: Can we determine if consensus, a fundamental concept in distributed computing, is truly universal? Methodology: The researchers analyzed the assumptions underlying Herlihy's universality result for consensus. They focused on the concept of naming, which assumes that each process has a unique identifier known to all. They proposed probabilistic protocols for systems with asynchronous processes communicating via a..."
 
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Title: Is Consensus Really Universal?
Title: Is Consensus Really Universal?


Research Question: Can we determine if consensus, a fundamental concept in distributed computing, is truly universal?
Research Question: Can we implement any data structure in a fault-tolerant manner using consensus and shared memory?


Methodology: The researchers analyzed the assumptions underlying Herlihy's universality result for consensus. They focused on the concept of naming, which assumes that each process has a unique identifier known to all. They proposed probabilistic protocols for systems with asynchronous processes communicating via a shared memory, even in the presence of crash failures. They used a strong adversary model, assuming that the adversary decides which process moves next based on the entire past history of the protocol execution.
Methodology: The researchers studied the problem of consensus, where a set of asynchronous processes communicate via a shared memory. They considered two basic assumptions: naming (the existence of distinct IDs known to all) and randomization (the availability of unbiased random bits).


Results: The researchers found that naming is a necessary assumption for Herlihy's universality result. They also discovered that naming with randomization is universal, meaning that any other data structure can be implemented in a wait-free manner. This is a counterintuitive result, as it challenges the common belief that consensus is necessary for universality.
Results: The researchers found that naming is a hidden, but necessary, assumption of Herlihy's universality result for consensus. They also showed that naming is harder than consensus and brought to light some important differences between popular shared memory models.


Implications: The findings suggest that the universality of consensus may not be as absolute as previously thought. The researchers' results provide a more nuanced understanding of the relationship between consensus and the implementation of other data structures in distributed computing systems. This could lead to more efficient and resilient protocols in the future.
Implications: This research has implications for the distributed computing community. It clarifies the assumptions needed for consensus to be universally applicable and highlights the complexity of naming in such systems. It also provides insights into the differences between popular shared memory models.


Link to Article: https://arxiv.org/abs/0201006v1
Link to Article: https://arxiv.org/abs/0201006v2
Authors:  
Authors:  
arXiv ID: 0201006v1
arXiv ID: 0201006v2


[[Category:Computer Science]]
[[Category:Computer Science]]
[[Category:Consensus]]
[[Category:Consensus]]
[[Category:Universality]]
[[Category:Shared]]
[[Category:They]]
[[Category:Memory]]
[[Category:Universal]]
[[Category:Naming]]
[[Category:Researchers]]
[[Category:Research]]

Latest revision as of 03:49, 24 December 2023

Title: Is Consensus Really Universal?

Research Question: Can we implement any data structure in a fault-tolerant manner using consensus and shared memory?

Methodology: The researchers studied the problem of consensus, where a set of asynchronous processes communicate via a shared memory. They considered two basic assumptions: naming (the existence of distinct IDs known to all) and randomization (the availability of unbiased random bits).

Results: The researchers found that naming is a hidden, but necessary, assumption of Herlihy's universality result for consensus. They also showed that naming is harder than consensus and brought to light some important differences between popular shared memory models.

Implications: This research has implications for the distributed computing community. It clarifies the assumptions needed for consensus to be universally applicable and highlights the complexity of naming in such systems. It also provides insights into the differences between popular shared memory models.

Link to Article: https://arxiv.org/abs/0201006v2 Authors: arXiv ID: 0201006v2

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