Consistency Violations Research Articles

Violation of projective consistency in structure-from-motion: a role for skin motion?

Violation of projective consistency in structure-from-motion: a role for skin motion?

Value the Recent Past: Approximate Causal Consistency for Partially Replicated Systems

In wide-area distributed systems, data replication provides fault tolerance and low latency. Causal consistency in such systems is an interesting consistency model. Most existing works assume the data is fully replicated because this greatly simplifies the design of the algorithms to implement causal consistency. Recently, we proposed causal consistency under partial replication because it reduces the number of messages used under a wide range of workloads. One drawback of partial replication is that its meta-data tends to be relatively large when the message size is small. In this paper, we propose an algorithm Approx-Opt-Track which provides approximate causal consistency whereby we can reduce the meta-data at the cost of some violations of causal consistency. The amount of violations can be made arbitrarily small by controlling a tunable parameter, that we call credits. We present the analytic data to show the performance of Approx-Opt-Track. We then give simulation results to show the potential benefit of Approx-Opt-Track, viz., its ability to provide almost the same guarantees as causal consistency, at a smaller cost.

Don’t Trust the Cloud, Verify

Cloud services have turned remote computation into a commodity and enable convenient online collaboration. However, they require that clients fully trust the service provider in terms of confidentiality, integrity, and availability. Toward reducing this dependency, this article introduces VICOS , a protocol for verification of integrity and consistency for cloud object storage that enables a group of mutually trusting clients to detect data integrity and consistency violations for a cloud object storage service. It aims at services where multiple clients cooperate on data stored remotely on a potentially misbehaving service. VICOS enforces the consistency notion of fork-linearizability, supports wait-free client semantics for most operations, and reduces the computation and communication overhead compared to previous protocols. VICOS is based on a generic authenticated data structure. Moreover, its operations cover the hierarchical name space of a cloud object store, supporting a real-world interface and not only a simplistic abstraction. A prototype of VICOS that works with the key-value store interface of commodity cloud storage services has been implemented, and an evaluation demonstrates its advantage compared to existing systems.

A Novel Heuristic Auditor for Revealing Strong Consistency Violations in Cloud

A Novel Heuristic Auditor for Revealing Strong Consistency Violations in Cloud

Overcoming the Fear of Water at the Initial Stage of Learning to Swim

The article deals with the fear of children of primary school age to open water, which appears at the initial stage of teaching swimming and is a serious obstacle to mastering the skills of swimming. Analysis of the scientific researches indicate a lack of reasonable methods of overcoming fears associated with the water during swimming training and scientific methodological developments in the prevention and overcoming fears associated with water, which leads to certain problems and violations of logical consistency in teaching swimming. The following empirical methods as questionnaires, interviews, pedagogical observations are used. The article presents the results of a study of this problem, especially: the results of the survey of primary school children who arrived at the base of the summer camp «Lastochka» in Skadovsk of Kherson region in 2016 during the month of June as well as conversations and observations with them that took place in real conditions of training swimming. This study provided the opportunity to determine the origin of fear causes of primary school age children, to reveal the reasons and statistics of accidents at open water, to identify factors fear of open water of primary school age children. The article indicates signs of the most important physical symptoms associated with the fear of open water. Methodical recommendations developed to overcome fears at the initial stage of swimming lessons in open water based on the principles of psychological impact on the minds of everyone as well as the use of innovative techniques while swimming. Methodical recommendations focus on the preparation and organization of lessons with children of primary school age, with the problem of fear of open water. They aim to overcome fear and to achieve the main goals of the swimming lessons in the summer camp to teach swimming every child.

An experimental study on tuning the consistency of NoSQL systems

SummaryThe eventual consistency model has been widely adopted in NoSQL systems. By tolerating weak consistency, these systems attain high throughput and availability while sustaining side effects on user experience and developer friendliness. Trading off consistency from latency has been a common consensus. An important but widely ignored problem is how to control the consistency of an existing system without the necessity of modifying the system implementation. In this paper, we present a systematic study on the client‐centric consistency of a NoSQL system, Cassandra, and disclose how the consistency can be substantially enhanced by tuning the system configurations when users use partial quorum settings. We use session guarantee as the consistency model and analyze the root cause of consistency violation, testifying that the length of the write queue is a reasonable indicator for consistency quantification. For inconsistency mitigation, we show through extensive experiments how the consistency is affected by the read and write processes of the system, and how the consistency can be improved by tuning system configurations. In particular, we provide developers with recommended configurations by changing the write thread number and the fine‐grained quorum setting for enhanced consistency control. Because consistency anomalies do not occur uniformly, we discuss how to stabilize the consistency by analyzing system logs.

CMB lens sample covariance and consistency relations

Gravitational lensing information from the two and higher point statistics of the CMB temperature and polarization fields are intrinsically correlated because they are lensed by the same realization of structure between last scattering and observation. Using an analytic model for lens sample covariance, we show that there is one mode, separately measurable in the lensed CMB power spectra and lensing reconstruction, that carries most of this correlation. Once these measurements become lens sample variance dominated, this mode should provide a useful consistency check between the observables that is largely free of sampling and cosmological parameter errors. Violations of consistency could indicate systematic errors in the data and lens reconstruction or new physics at last scattering, any of which could bias cosmological inferences and delensing for gravitational waves. A second mode provides a weaker consistency check for a spatially flat universe. Our analysis isolates the additional information supplied by lensing in a model independent manner but is also useful for understanding and forecasting CMB cosmological parameter errors in the extended $\Lambda$CDM parameter space of dark energy, curvature and massive neutrinos. We introduce and test a simple but accurate forecasting technique for this purpose that neither double counts lensing information nor neglects lensing in the observables.

Addenda: “General spin precession and betatron oscillation in storage ring”

We give the geralized expression of spin precession of extended bunch particles having both anomalous magnetic and electric dipole moments in storage ring in higher order than the previous work and in the presence of ${\bf E}$ field as well as ${\bf B}$ field. These addenda are essential since some experiments consider the focusing field in the second order of the beam extent and in the presence of both ${\bf B}$ and ${\bf E}$ fields . It is shown that some focusing fields with constant magnitude of the velocity considered in many literatures lead to the violation of self consistency.

Be patient when measuring hyperbolic discounting: Stationarity, time consistency and time invariance in a field experiment

Hyperbolic discounting is one potential reason why savings remain low among the poor. Most evidence of hyperbolic discounting is based on violations of either stationarity or time consistency. Stationarity is violated when intertemporal choices differ for trade-offs in the near versus the more distant future. Time consistency is violated if the optimal allocation for specific dates changes over time. Both types of choice reversals may however also result from time-varying discount rates. Hyperbolic discounting is an unambiguous explanation for choice reversals only if the same individuals violate both stationarity and time consistency. Our field experiment in Nigeria examines the extent to which this is the case. The experiment measured both stationarity and time consistency for the same participants. Violations of the two rarely coincide, especially among more liquidity-constrained participants. Thus, in a context of liquidity constraints, eliciting only one type of choice reversal is insufficient to identify hyperbolic discounting.

The Consistency Assumption for Causal Inference in Social Epidemiology: When a Rose is Not a Rose.

The assumption that exposures as measured in observational settings have clear and specific definitions underpins epidemiologic research and allows us to use observational data to predict outcomes in interventions. This leap between exposures as measured and exposures as intervened upon is typically supported by the consistency assumption. The consistency assumption has received extensive attention in risk factor epidemiology but relatively little emphasis in social epidemiology. However, violations of the consistency assumption may be especially important to consider when understanding how social and economic exposures influence health. Efforts to clarify the definitions of our exposures, thus bolstering the consistency assumption, will help guide interventions to improve population health and reduce health disparities. This article focuses on the consistency assumption as considered within social epidemiology. We explain how this assumption is articulated in the causal inference literature and give examples of how it might be violated for three common exposure in social epidemiology research: income, education and neighborhood characteristics. We conclude that there is good reason to worry about consistency assumption violations in much of social epidemiology research. Theoretically motivated explorations of mechanisms along with empirical comparisons of research findings under alternative operationalizations of exposure can help identify consistency violations. We recommend that future social epidemiology studies be more explicit to name and discuss the consistency assumption when describing the exposure of interest, including reconciling disparate results in the literature.

Towards consistence and convergence of conservative SPH approximations

Typical conservative smoothed particle hydrodynamics (SPH) approximations of the gradient of a scalar field introduce two errors: one (smoothing error) is due to smoothing of the gradient by an integration associated with a kernel function; the other (integration error) is due to approximating the integration by summation over all particles within the kernel support. When particles are not on a uniform grid, the integration error leads to violation of zero-order consistency, i.e. the inability to reproduce a constant field. In this paper we confirm that partition of unity is the condition under which the conservative SPH approximation achieves both consistence and convergence. We show that this condition can be achieved by relaxing a particle distribution under a constant pressure field and invariant particle volume. The resulting particle distribution is very similar to that is typical for liquid molecules. We further show that with two different typical kernel functions the SPH approximation, upon satisfying the partition of unity property, is able to achieve very high-order of the integration error, which previously could be shown only with particles on a uniform grid. The background pressure used in a weakly compressible SPH simulation implies a self-relaxation mechanism, which explains that convergence with respect to increasing particle numbers could be obtained in SPH simulations, although not predicted by previous numerical analysis. Furthermore, by relating the integration error to the background pressure, we explain why the previously proposed transport-velocity formulation of SPH (S. Adami et al. (2013) [1]) is able to achieve unprecedented accuracy and stability.

Post-Silicon Validation of Multiprocessor Memory Consistency

Shared-memory chip-multiprocessor (CMP) architectures define memory consistency models that establish the ordering rules for memory operations from multiple threads. Validating the correctness of a CMP's implementation of its memory consistency model requires extensive monitoring and analysis of memory accesses while multiple threads are executing on the CMP. In this paper, we present a low overhead solution for observing, recording and analyzing shared-memory interactions for use in an emulation and/or post-silicon validation environment. Our approach leverages portions of the CMP's own data caches, augmented only by a small amount of hardware logic, to log information relevant to memory accesses. After transferring this information to a central memory location, we deploy our own analysis algorithm to detect any possible memory consistency violations. We build on the property that a violation corresponds to a cycle in an appropriately defined graph representing memory interactions. The solution we propose allows a designer to choose where to run the analysis algorithm: 1) on the CMP itself; 2) on a separate processor residing on the validation platform; or 3) off-line on a separate host machine. Our experimental results show an 83% bug detection rate, in our testbed CMP, over three distinct memory consistency models, namely: relaxed-memory order, total-store order, and sequential consistency. Finally, note that our solution can be disabled in the final product, leading to zero performance overhead and a per-core area overhead that is smaller than the size of a physical integer register file in a modern processor.

Hybrid Static–Dynamic Analysis for Statically Bounded Region Serializability

Data races are common. They are difficult to detect, avoid, or eliminate, and programmers sometimes introduce them intentionally. However, shared-memory programs with data races have unexpected, erroneous behaviors. Intentional and unintentional data races lead to atomicity and sequential consistency (SC) violations, and they make it more difficult to understand, test, and verify software. Existing approaches for providing stronger guarantees for racy executions add high run-time overhead and/or rely on custom hardware. This paper shows how to provide stronger semantics for racy programs while providing relatively good performance on commodity systems. A novel hybrid static--dynamic analysis called \emph{EnfoRSer} provides end-to-end support for a memory model called \emph{statically bounded region serializability} (SBRS) that is not only stronger than weak memory models but is strictly stronger than SC. EnfoRSer uses static compiler analysis to transform regions, and dynamic analysis to detect and resolve conflicts at run time. By demonstrating commodity support for a reasonably strong memory model with reasonable overheads, we show its potential as an always-on execution model.

Hybrid Static–Dynamic Analysis for Statically Bounded Region Serializability

Data races are common. They are difficult to detect, avoid, or eliminate, and programmers sometimes introduce them intentionally. However, shared-memory programs with data races have unexpected, erroneous behaviors. Intentional and unintentional data races lead to atomicity and sequential consistency (SC) violations, and they make it more difficult to understand, test, and verify software. Existing approaches for providing stronger guarantees for racy executions add high run-time overhead and/or rely on custom hardware. This paper shows how to provide stronger semantics for racy programs while providing relatively good performance on commodity systems. A novel hybrid static--dynamic analysis called \emph{EnfoRSer} provides end-to-end support for a memory model called \emph{statically bounded region serializability} (SBRS) that is not only stronger than weak memory models but is strictly stronger than SC. EnfoRSer uses static compiler analysis to transform regions, and dynamic analysis to detect and resolve conflicts at run time. By demonstrating commodity support for a reasonably strong memory model with reasonable overheads, we show its potential as an always-on execution model.

On the determination of noise parameters of low‐noise transistor devices

AbstractIn this paper, we discuss the experimental determination of noise parameters for high‐electron‐mobility transistor (HEMT) devices and analyze the problems encountered with conventional extraction techniques. HEMT devices are distinguished by a very small minimum noise figure of only a fraction of a dB, and this minimum noise is accomplished with a source reflection coefficient very close to the edge of the Smith chart. These properties impede a direct experimental determination of the optimum noise impedance by means of a tuner, and it has to be extrapolated from measurements of a large number of tuner states. Common linear regression techniques are found to yield erroneous results and even may fail completely to determine the noise parameters. We develop criteria to check the uncertainty of the result from the linear regression and show that, in general, the result needs to be examined for consistency. The occasional failure of extraction is traced back to a consistency violation in the conditions the elements of the correlation matrix need to satisfy. A new iterative technique is suggested for the extraction of noise parameters that warrants consistency. Moreover, a correction of the receiver gain is found to be necessary to obtain a good reproduction of the measured power patterns by the extracted noise parameters. This fact was attributed to thermal drift of the receiver. Copyright © 2015 John Wiley & Sons, Ltd.

Efficient Correction of Anomalies in Snapshot Isolation Transactions

Transactional memory systems providing snapshot isolation enable concurrent access to shared data without incurring aborts on read-write conflicts. Reducing aborts is extremely relevant as it leads to higher concurrency, greater performance, and better predictability. Unfortunately, snapshot isolation does not provide serializability as it allows certain anomalies that can lead to subtle consistency violations. While some mechanisms have been proposed to verify the correctness of a program utilizing snapshot isolation transactions, it remains difficult to repair incorrect applications. To reduce the programmer’s burden in this case, we present a technique based on dynamic code and graph dependency analysis that automatically corrects existing snapshot isolation anomalies in transactional memory programs. Our evaluation shows that corrected applications retain the performance benefits characteristic of snapshot isolation over conventional transactional memory systems.

Be Patient When Measuring Hyperbolic Discounting: Stationarity, Time Consistency and Time Invariance in a Field Experiment

Most experimental evidence of hyperbolic discounting is based on violations of either stationarity or time consistency. Stationarity is violated when intertemporal choices differ for trade-offs in the near versus the more distant future. Time consistency on the other hand is violated if the optimal allocation for specific dates changes over time. Both types of choice reversals may however also result from time-varying discount rates. Hyperbolic discounting is an unambiguous explanation for choice reversals only if individuals simultaneously violate both stationarity and time consistency. Our field experiment examines the extent to which this is the case. At different points in time, the same participants allocated a future gift over sooner-smaller and later-larger rewards with varying front-end delays. We find that most violations of time consistency do not coincide with violations of stationarity. Random noise in decision-making alone does not explain this finding. Instead, we find a significant association between individual violations and changes in household wealth, in particular for participants with less access to credit. We conclude that in a context of liquidity constraints, eliciting violations of either stationarity or time consistency alone is insufficient to identify hyperbolic discounting.

Commentary: from estimation to translation: interpreting mediation analysis results in perinatal epidemiology.

Commentary: from estimation to translation: interpreting mediation analysis results in perinatal epidemiology.

Stored-heat assessments: a review in the light of field experience

<p><strong>Abstract.</strong> Stored-heat or volumetric assessments of geothermal resources are appealingly simple: the resource being exploited is heat. A stored-heat calculation simply computes the amount of heat in the resource, similarly to computing the amount of ore in an ore body. The method has theoretical support in numerical simulations of resource production. While there are significant unknowns in any resource, some of these can be covered by probabilistic approaches, notably a Monte Carlo method. The Australian Geothermal Reporting Code represents one specification of such stored-heat assessments. <br><br> However the experience of recent decades, with the development of significant numbers of geothermal resources, has shown that the method is highly unreliable and usually biased high. The tendency to overestimates, in particular, has led to the reduced credibility of the method. An example is quoted where simple application of the apparently simple rules gives a ridiculous result. Much of the problem lies in the "recovery factor", the proportion of the resource that can actually be exploited, where comparison with actual performance shows past values have been in all cases too high, as is the current version of the Australian code. <br><br> There are further problems, usually overlooked, in the way that the reservoir volume and "cutoff temperature" are defined. Differing approaches mean that results between different reports are not comparable. The different approaches also imply unrecognised assumptions about the physical processes controlling reservoir depletion. The failure of Monte Carlo methods is similarly due to unrecognised violation of logical consistency in the use of probabilities. <br><br> The net effect of these problems is that the method is not a simple means to generate a rough resource estimate, and it often generates faulty results. Usually, such results are overestimates. Monte Carlo methods do not provide a protection against these errors. <br><br> The Australian Geothermal Reporting Code should be used for hydrothermal systems with an average recovery factor of 10%. With this average, results are subject to an error of ±70%. For enhanced geothermal systems (EGS), the recovery factor should be a few percent.</p>

Simulation integration: using multidatabase systems concepts

This paper considers the challenge of designing a framework that supports the integration of multiple existing simulation models into an integrated simulation environment (multisimulation). We aim to facilitate the process of fusing together the independently created simulators into an integrated simulation environment wherein we can model and execute complex scenarios involving multiple simulators. In this paper, we focus on solutions for the synchronization problem in multisimulation to orchestrate consistent information flow through multiple simulators. In particular, we provide: (1) a transaction-based approach to modeling the synchronization problem in multisimulations by mapping it to a problem similar to multidatabase concurrency; we express multisimulation synchronization as a scheduling problem where the goal is to generate “correct schedules” for time advancement and data exchange across simulators that meets the dependencies without loss of concurrency; (2) a hybrid scheduling strategy which adapts itself to the “right” level of pessimism/optimism based on the state of the execution and underlying dependencies. We also develop two key optimizations: (a) efficient checkpointing/rollback techniques; and (b) relaxation model for dependencies which guarantees bounded violation of consistency to support higher levels of concurrency. We evaluate our proposed techniques via a detailed case study from the emergency response domain by integrating three disparate simulators: a fire simulator (CFAST), an evacuation simulator (Drillsim) and a communication simulator (LTEsim).