Horae: causal consistency model based on hot data governance

2021 ◽  
Author(s):  
Junfeng Tian ◽  
Qianyu Yang
Keyword(s):  
Data Governance ◽  
Model Based ◽  
Consistency Model ◽  
Causal Consistency

scholarly journals New geometric design consistency model based on operating speed profiles for road safety evaluation

2013 ◽  
Vol 61 ◽  
pp. 33-42 ◽  
Author(s):  
Francisco J. Camacho-Torregrosa ◽  
Ana M. Pérez-Zuriaga ◽  
J. Manuel Campoy-Ungría ◽  
Alfredo García-García
Keyword(s):  
Road Safety ◽  
Safety Evaluation ◽  
Geometric Design ◽  
Operating Speed ◽  
Model Based ◽  
Consistency Model ◽  
Design Consistency

Strict Timed Causal Consistency as a Hybrid Consistency Model in the Cloud Environment

2020 ◽  
Vol 105 ◽  
pp. 259-274
Author(s):  
Hesam Nejati Sharif Aldin ◽  
Hossein Deldari ◽  
Mohammad Hossein Moattar ◽  
Mostafa Razavi Ghods
Keyword(s):  
Cloud Environment ◽  
Consistency Model ◽  
Causal Consistency

scholarly journals Convergence Through a Weak Consistency Model

2018 ◽  
Vol 8 (2) ◽  
Author(s):  
Francisco J. Torres-Rojas ◽  
Esteban Meneses
Keyword(s):  
Real Time ◽  
Distributed System ◽  
Weak Consistency ◽  
Consistency Model ◽  
Causal Consistency ◽  
Shared Objects

Given a distributed system with several shared objects and many processes concurrently updating and reading them, it is convenient that the system achieves convergence on the value of these objects. Such property can be guaranteed depending on the consistency model being employed. Causal Consistency is a weak consistency model that is easy and cheap to implement. However, due to the lack of real-time considerations, this model cannot offer convergence. A solution for overcoming that problem is to include time aspects within the framework of the model. This is the aim of Timed Causal Consistency.

scholarly journals New Consistency Model Based on Inertial Operating Speed Profiles for Road Safety Evaluation

2018 ◽  
Vol 144 (4) ◽  
pp. 04018006 ◽  
Author(s):  
David Llopis-Castelló ◽  
Francesco Bella ◽  
Francisco Javier Camacho-Torregrosa ◽  
Alfredo García
Keyword(s):  
Road Safety ◽  
Safety Evaluation ◽  
Operating Speed ◽  
Model Based ◽  
Consistency Model

scholarly journals Checking Robustness Between Weak Transactional Consistency Models

2021 ◽  
pp. 87-117
Author(s):  
Sidi Mohamed Beillahi ◽  
Ahmed Bouajjani ◽  
Constantin Enea
Keyword(s):  
Distributed Systems ◽  
Polynomial Time ◽  
Reduction Theory ◽  
Proof Technique ◽  
Reachability Problem ◽  
Snapshot Isolation ◽  
Trade Offs ◽  
Consistency Model ◽  
Causal Consistency ◽  
Consistency Models

AbstractConcurrent accesses to databases are typically encapsulated in transactions in order to enable isolation from other concurrent computations and resilience to failures. Modern databases provide transactions with various semantics corresponding to different trade-offs between consistency and availability. Since a weaker consistency model provides better performance, an important issue is investigating the weakest level of consistency needed by a given program (to satisfy its specification). As a way of dealing with this issue, we investigate the problem of checking whether a given program has the same set of behaviors when replacing a consistency model with a weaker one. This property known as robustness generally implies that any specification of the program is preserved when weakening the consistency. We focus on the robustness problem for consistency models which are weaker than standard serializability, namely, causal consistency, prefix consistency, and snapshot isolation. We show that checking robustness between these models is polynomial time reducible to a state reachability problem under serializability. We use this reduction to also derive a pragmatic proof technique based on Lipton’s reduction theory that allows to prove programs robust. We have applied our techniques to several challenging applications drawn from the literature of distributed systems and databases.

scholarly journals Empirical Study on Urban Waterlogging Data Governance Model Based on DID

2021 ◽  
Vol 781 (3) ◽  
pp. 032062
Author(s):  
Chaohua Yan ◽  
Weike Chen ◽  
Yangyang Yang ◽  
Jing Dong ◽  
Risheng Qiao
Keyword(s):  
Empirical Study ◽  
Data Governance ◽  
Model Based ◽  
Governance Model

Representation, abstraction, and simple-minded sophisticates

2020 ◽  
Vol 43 ◽  
Author(s):  
Peter Dayan
Keyword(s):  
Decision Theory ◽  
Predictive Coding ◽  
Bayesian Decision Theory ◽  
Bayesian Decision ◽  
Model Based ◽  
Model Free

Abstract Bayesian decision theory provides a simple formal elucidation of some of the ways that representation and representational abstraction are involved with, and exploit, both prediction and its rather distant cousin, predictive coding. Both model-free and model-based methods are involved.

Quantitative Model-Based Image Analysis of NuMa Distribution Links Nuclear Organization with Cell Phenotype

2001 ◽  
Vol 7 (S2) ◽  
pp. 578-579
Author(s):  
David W. Knowles ◽  
Sophie A. Lelièvre ◽  
Carlos Ortiz de Solόrzano ◽  
Stephen J. Lockett ◽  
Mina J. Bissell ◽  
...  
Keyword(s):  
Image Analysis ◽  
Mammary Epithelial Cells ◽  
Nuclear Organization ◽  
Critical Role ◽  
Quantitative Model ◽  
Mammary Epithelial ◽  
Cell Phenotype ◽  
Proliferating Cells ◽  
Mitotic Apparatus ◽  
Model Based

The extracellular matrix (ECM) plays a critical role in directing cell behaviour and morphogenesis by regulating gene expression and nuclear organization. Using non-malignant (S1) human mammary epithelial cells (HMECs), it was previously shown that ECM-induced morphogenesis is accompanied by the redistribution of nuclear mitotic apparatus (NuMA) protein from a diffuse pattern in proliferating cells, to a multi-focal pattern as HMECs growth arrested and completed morphogenesis . A process taking 10 to 14 days.To further investigate the link between NuMA distribution and the growth stage of HMECs, we have investigated the distribution of NuMA in non-malignant S1 cells and their malignant, T4, counter-part using a novel model-based image analysis technique. This technique, based on a multi-scale Gaussian blur analysis (Figure 1), quantifies the size of punctate features in an image. Cells were cultured in the presence and absence of a reconstituted basement membrane (rBM) and imaged in 3D using confocal microscopy, for fluorescently labeled monoclonal antibodies to NuMA (fαNuMA) and fluorescently labeled total DNA.

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