Programming simultaneous actions using common knowledge

Moses, Yoram; Tuttles, M. R.

doi:10.1007/bf01762112

Cited by 140 publications

(132 citation statements)

References 12 publications

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“…In addition, the lower bound proof itself is interesting because of the geometric proof technique we use, combining ideas due to Chaudhuri [Cha91,Cha93], Fischer and Lynch [FL82], Herlihy and Shavit [HS93], and Dwork, Moses, and Tuttle [DM90,MT88].…”

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confidence: 99%

Tight bounds for k -set agreement

Chaudhuri

Erlihy

Lynch

et al. 2000

J. ACM

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The Cambridge Research Laboratory was founded in 1987 to advance the state of the art in both core computing and human-computer interaction, and to use the knowledge so gained to support the Company's corporate objectives. We believe this is best accomplished through interconnected pursuits in technology creation, advanced systems engineering, and business development. We are actively investigating scalable computing; mobile computing; vision-based human and scene sensing; speech interaction; computer-animated synthetic persona; intelligent information appliances; and the capture, coding, storage, indexing, retrieval, decoding, and rendering of multimedia data. We recognize and embrace a technology creation model which is characterized by three major phases:The life blood of the Laboratory comes from the observations and imaginations of our research staff. It is here that challenging research problems are uncovered (through discussions with customers, through interactions with others in the Corporation, through other professional interactions, through reading, and the like) or that new ideas are born. For any such problem or idea, this phase culminates in the nucleation of a project team around a well articulated central research question and the outlining of a research plan. Focus:Once a team is formed, we aggressively pursue the creation of new technology based on the plan. This may involve direct collaboration with other technical professionals inside and outside the Corporation. This phase culminates in the demonstrable creation of new technology which may take any of a number of forms -a journal article, a technical talk, a working prototype, a patent application, or some combination of these. The research team is typically augmented with other resident professionals-engineering and business development-who work as integral members of the core team to prepare preliminary plans for how best to leverage this new knowledge, either through internal transfer of technology or through other means. Follow-through:We actively pursue taking the best technologies to the marketplace. For those opportunities which are not immediately transferred internally and where the team has identified a significant opportunity, the business development and engineering staff will lead early-stage commercial development, often in conjunction with members of the research staff. While the value to the Corporation of taking these new ideas to the market is clear, it also has a significant positive impact on our future research work by providing the means to understand intimately the problems and opportunities in the market and to more fully exercise our ideas and concepts in real-world settings.Throughout this process, communicating our understanding is a critical part of what we do, and participating in the larger technical community-through the publication of refereed journal articles and the presentation of our ideas at conferences-is essential. Our technical report series supports and facilitates broad and early dissemination of our...

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mentioning

confidence: 99%

Tight bounds for k -set agreement

Chaudhuri

Erlihy

Lynch

et al. 2000

J. ACM

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“…One nice property of full-information protocols is that every execution of a full-information protocol P has a compact representation called a communication graph MT88] as the round i edge from p to q, a n d w e refer to the node hp i ; 1i as the round i node for p since it represents to point a t w h i c h p sends its round i messages.…”

Section: The Modelmentioning

confidence: 99%

A tight lower bound for k-set agreement

Chaudhuri

Herlihy²,

Lynch³

et al.

Proceedings of 1993 IEEE 34th Annual Foundations of Computer Science

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We prove t i g h t bounds on the time neededto solve k-set agreement, a natural generalization of consensus. We analyze this problem in a synchronous, message-passing model where processors fail by crashing. We p r o ve a l o wer bound of bf=kc+1 rounds of communication for solutions to k-set agreement that tolerate f failures. This bound is tight, and shows that there is an inherent tradeo between the running time, the degree of coordination required, and the number of faults tolerated, even in idealized models like the synchronous model. The proof of this result is interesting because it is a geometric combination of other well-known proof techniques.

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“…Our lower bound is based on a well-known connection between simultaneous actions and common knowledge [DM90,MT88,MM08]. Rather than develop the logic of knowledge in detail here, we will employ a simple graph-theoretic interpretation of common knowledge that applies in our setting.…”

Section: Optimal Protocolsmentioning

confidence: 99%

“…Simultaneous decision tasks [DM90, MT88,MM08] are decision tasks in which all nonfaulty processes decide in the same round. Simultaneity is important when processes must coordinate their behavior in time.…”

Section: Introductionmentioning

confidence: 99%

Transforming worst-case optimal solutions for simultaneous tasks into all-case optimal solutions

Herlihy

Moses

Tuttle

2011

Proceedings of the 30th Annual ACM SIGACT-SIGOPS Symposium on Principles of Distributed Computing

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Decision tasks require that nonfaulty processes make decisions based on their input values. Simultaneous decision tasks require that nonfaulty processes decide in the same round. Most decision tasks have known worst-case lower bounds. Most also have known worst-case optimal protocols that halt in the number of rounds given by the worst-case lower bound, and some have early-stopping protocols that can halt earlier than the worst-case lower bound (sometimes in as early as two rounds). We consider what might be called earliest-possible protocols for simultaneous decision tasks. We present a new technique that converts worst-case optimal decision protocols into all-case optimal simultaneous decision protocols: For every behavior of the adversary, the all-case optimal protocol decides as soon as any protocol can decide in a run with the same adversarial behavior. Examples to which this can be applied include set consensus, condition-based consensus, renaming and order-preserving renaming. Some of these tasks can be solved significantly faster than the classical simultaneous consensus task. A byproduct of the analysis is a proof that improving on the worst-case bound for any simultaneous task by even a single round is as hard as reaching simultaneous consensus.

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Programming simultaneous actions using common knowledge

Cited by 140 publications

References 12 publications

Tight bounds for k -set agreement

Tight bounds for k -set agreement

A tight lower bound for k-set agreement

Transforming worst-case optimal solutions for simultaneous tasks into all-case optimal solutions

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