Hardware/software trade-offs for shared resources virtualization in mixed-criticality automotive multicore systems

2017 ◽  
Vol 59 (5) ◽  
Author(s):  
Timo Sandmann ◽  
Andre Richter ◽  
Johann Heyszl ◽  
Enno Lübbers
Keyword(s):  
Operating Systems ◽  
Resource Constraints ◽  
Hardware Support ◽  
Shared Resources ◽  
Trade Off ◽  
Context Switching ◽  
Trade Offs ◽  
Time Requirements ◽  
And Performance ◽  
Interrupt Handling

AbstractVirtualization plays an important role for embedded systems where hardware support can prove beneficial, but these systems also pose a challenge due to power, resource constraints; reliability, safety, real-time requirements; diversity of devices, and operating systems. Therefore a trade-off between flexibility, determinism and performance exists in the embedded application domain. As virtualization in software always incurs overhead due to context switching, interrupt handling, etc. the aim is to minimize the overhead and make execution more deterministic using hardware support.

scholarly journals A Review of Performance, Energy and Privacy of Intrusion Detection Systems for IoT

Electronics ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 629 ◽  
Author(s):  
Junaid Arshad ◽  
Muhammad Ajmal Azad ◽  
Roohi Amad ◽  
Khaled Salah ◽  
Mamoun Alazab ◽  
...  
Keyword(s):  
Intrusion Detection ◽  
Resource Constraints ◽  
Extensive Study ◽  
Intrusion Detection Systems ◽  
Detection Accuracy ◽  
Trade Off ◽  
Detection Systems ◽  
Computational Overhead ◽  
Significant Research ◽  
And Performance

Internet of Things (IoT) forms the foundation of next generation infrastructures, enabling development of future cities that are inherently sustainable. Intrusion detection for such paradigms is a non-trivial challenge which has attracted further significance due to extraordinary growth in the volume and variety of security threats for such systems. However, due to unique characteristics of such systems i.e., battery power, bandwidth and processor overheads and network dynamics, intrusion detection for IoT is a challenge, which requires taking into account the trade-off between detection accuracy and performance overheads. In this context, we are focused at highlighting this trade-off and its significance to achieve effective intrusion detection for IoT. Specifically, this paper presents a comprehensive study of existing intrusion detection systems for IoT systems in three aspects: computational overhead, energy consumption and privacy implications. Through extensive study of existing intrusion detection approaches, we have identified open challenges to achieve effective intrusion detection for IoT infrastructures. These include resource constraints, attack complexity, experimentation rigor and unavailability of relevant security data. Further, this paper is envisaged to highlight contributions and limitations of the state-of-the-art within intrusion detection for IoT, and aid the research community to advance it by identifying significant research directions.

scholarly journals Potential trade-off between vocal ornamentation and spatial ability in a songbird

2013 ◽  
Vol 9 (4) ◽  
pp. 20130344 ◽  
Author(s):  
Kendra B. Sewall ◽  
Jill A. Soha ◽  
Susan Peters ◽  
Stephen Nowicki
Keyword(s):  
Cognitive Abilities ◽  
Spatial Task ◽  
Repertoire Size ◽  
Trade Off ◽  
Trade Offs ◽  
Brain Structure And Function ◽  
And Performance ◽  
Song Control ◽  
And Function ◽  
The Relationship

Bird song is hypothesized to be a reliable indicator of cognition because it depends on brain structure and function. Song features have been found to correlate positively with measures of cognition, but the relationship between song and cognition is complicated because not all cognitive abilities are themselves positively correlated. If cognition is not a unitary trait, developmental constraints on brain growth could generate trade-offs between some aspects of cognition and song. To further clarify the relationship between song and cognition in song sparrows ( Melospiza melodia ), we examined repertoire size and performance on a spatial task. We found an inverse relationship between repertoire size and speed of spatial learning and suggest that a developmental trade-off between the hippocampus and song control nuclei could be responsible for this relationship. By attending to male song, females may learn about a suite of cognitive abilities; this study suggests that females may glean information about a male's cognitive weaknesses as well as his strengths.

Automatically Denormalizing Document Relationships

2017 ◽  
Author(s):  
Will Thompson
Keyword(s):  
Data Storage ◽  
Software Maintenance ◽  
Design Patterns ◽  
Unique Problem ◽  
Trade Off ◽  
Xml Databases ◽  
Trade Offs ◽  
Single Data ◽  
And Performance ◽  
Document Relationships

Native XML databases provide no exception to the problem that data may not be easily contained by any single data storage idiom. Many-to-many relationships, in particular, present a unique problem for documents, as strategies for joining across documents are a potential minefield of software maintenance and performance problems. Automatic denormalization shifts the responsibilty for managing relationships to write-time, making an explicit trade-off for simplicity and speed at runtime. This paper discusses existing strategies for managing relationships across documents and explores design patterns and use cases for performing automatic denormalization and their trade-offs.

scholarly journals The Best of Both Worlds: Mitigating Trade-offs Between Accuracy and User Burden in Capturing Mobile App Privacy Preferences

2020 ◽  
Vol 2020 (1) ◽  
pp. 195-215
Author(s):  
Daniel Smullen ◽  
Yuanyuan Feng ◽  
Shikun Aerin Zhang ◽  
Norman Sadeh
Keyword(s):  
Machine Learning ◽  
Operating Systems ◽  
Quantitative Assessment ◽  
Mobile Apps ◽  
Mobile App ◽  
Sensitive Data ◽  
Trade Off ◽  
Privacy Preferences ◽  
Trade Offs ◽  
Data Flows

AbstractIn today’s data-centric economy, data flows are increasingly diverse and complex. This is best exemplified by mobile apps, which are given access to an increasing number of sensitive APIs. Mobile operating systems have attempted to balance the introduction of sensitive APIs with a growing collection of permission settings, which users can grant or deny. The challenge is that the number of settings has become unmanageable. Yet research also shows that existing settings continue to fall short when it comes to accurately capturing people’s privacy preferences. An example is the inability to control mobile app permissions based on the purpose for which an app is requesting access to sensitive data. In short, while users are already overwhelmed, accurately capturing their privacy preferences would require the introduction of an even greater number of settings. A promising approach to mitigating this trade-off lies in using machine learning to generate setting recommendations or bundle some settings. This article is the first of its kind to offer a quantitative assessment of how machine learning can help mitigate this trade-off, focusing on mobile app permissions. Results suggest that it is indeed possible to more accurately capture people’s privacy preferences while also reducing user burden.

scholarly journals A NEW ANALYTICAL METHODOLOGY TO HANDLE TIME-COST TRADE-OFF PROBLEM WITH CONSIDERING QUALITY LOSS COST UNDER INTERVAL-VALUED FUZZY UNCERTAINTY

2019 ◽  
Vol 25 (2) ◽  
pp. 277-299 ◽  
Author(s):  
Mohammad Hossein Haghighi ◽  
Seyed Meysam Mousavi ◽  
Jurgita Antuchevičienė ◽  
Vahid Mohagheghi
Keyword(s):  
Critical Path ◽  
Quality Loss ◽  
Time Cost ◽  
Analytical Methodology ◽  
New Approach ◽  
Trade Off ◽  
Trade Offs ◽  
And Performance ◽  
Interval Valued

This paper proposes a new framework in addressing time-cost trade-off problem (TCTP) under uncertainty. First critical path analysis is carried out based on developing a new interval-valued fuzzy (IVF)-program evaluation and review technique (PERT) approach. Then, non-conformance risks that influence on execution quality of activities are identified and evaluated based on a new approach that considers probability of risk along with impacts on time, cost, and performance. Then, a new mathematical model under IVF uncertainty is presented to decrease project total time while considering time, cost and quality loss cost that is determined in form of rework or modification cost. Finally, the approach categorizes the activities in three groups based on their level of criticality. Outcome of this methodology is a scheduling that addresses time, cost and quality trade-offs in addition to categorizing activities in different groups based on being on the critical path. Therefore, the project manager not only gets a scheduling based on the TCTP with considering quality loss cost but also has a knowledge of activities that require extra attentions. To show the steps of this methodology, an existing application from the literature is adopted and solved.

scholarly journals Functional Trade-offs in the Mechanical Design of Integrated Products - Impact on Robustness and Optimisability

2019 ◽  
Vol 1 (1) ◽  
pp. 3491-3500
Author(s):  
Nökkvi S. Sigurdarson ◽  
Tobias Eifler ◽  
Martin Ebro
Keyword(s):  
Design Process ◽  
Lead Time ◽  
Mechanical Design ◽  
Functional Design ◽  
Trade Off ◽  
Trade Offs ◽  
Final Design ◽  
And Performance ◽  
Geometric Variation ◽  
Sweet Spots

AbstractIt is generally accepted in industry and academia that trade-offs between functional design objectives are an inevitable factor in the development of mechanical systems. These trade-offs can have a large influence on the achievable robustness and performance of the final design, with many products only functioning in narrow sweet-spots between different objectives. As a result, the design process of multi- functional products can be prolonged when designers concurrently attempt to find sweet-spots between a number of potentially interdependent trade-offs. This paper will show that designers only have six different approaches available when attempting to manage a trade-off while trying to ensure robustness and a sufficient performance. These fall within one of three categories; accept, optimise, or redesign. Selecting the wrong approach, can result in consequences downstream which can be difficult to predict, amongst others a lack of robustness to geometric variation, constrained performance, and long development lead time. This points to a substantial potential in the synthesis of design methods that support the identification and management of trade-offs in early product development.

scholarly journals The Mystery of a Marine Monster: Morphological and Performance Modifications in the World’s only Marine Lizard, the Galápagos Marine Iguana

2020 ◽  
Author(s):  
Kate A. Berry ◽  
Juan Pablo Muñoz-Pérez ◽  
Cristina P. Vintimilla-Palacios ◽  
Christofer J. Clemente
Keyword(s):  
Marine Environment ◽  
Ecological Niches ◽  
Aquatic Environments ◽  
Terrestrial Environment ◽  
Aquatic Life ◽  
Trade Off ◽  
Trade Offs ◽  
Extant Species ◽  
And Performance ◽  
Marine Iguana

AbstractReptiles have repeatedly invaded and thrived in aquatic environments throughout history, however fewer than 8% of the 6000 extant species are primarily aquatic. The Galápagos Marine Iguana (Amblyrhynchus cristatus), the world’s only marine lizard, may have had one of the most unique and challenging transitions to aquatic life. Curiously, previous studies have identified relatively few physiological adaptations in Marine Iguanas, however, little is known about the extent of morphological specialisation and performance trade-offs associated with the marine environment. By examining the morphology and locomotory performance of the Marine Iguana in comparison to their closely related mainland ancestors, the Black Spiny-tailed iguana (Ctenosaura similis) and Green Iguana (Iguana iguana), we found variation reflected specialisation to ecological niches. However, variation was more pronounced among subspecies of Marine Iguana, suggesting that little morphological or performance modification is required for iguanids to successfully invade aquatic environments, thus raising the question why there are so few extant aquatic reptilian lineages. We found that specialisation for the marine environment resulted in a trade-off in sprint speed in a terrestrial environment, similar to that seen in extant crocodilians. Reduced performance in a terrestrial environment likely poses little risk to large-bodied apex predators, whereas in iguanids, a performance trade-off would likely incur increased predation. As such, we suggest that this may explain why iguanids and other ancestral lineages have not undergone transitions to aquatic life. Additionally, we found that the magnitude of morphological and performance variation was more pronounced between subspecies of Marine Iguana than between iguanid species.Summary StatementThe Marine Iguana has undergone a unique evolutionary transition to aquatic behaviour, we explore the extent of morphological and performance specialisation required and why there are so few extant marine reptiles.

Dual Goals for Speed and Accuracy on the Same Performance Task

2012 ◽  
Vol 11 (3) ◽  
pp. 118-126 ◽  
Author(s):  
Olive Emil Wetter ◽  
Jürgen Wegge ◽  
Klaus Jonas ◽  
Klaus-Helmut Schmidt
Keyword(s):  
Memory Scanning ◽  
Performance Task ◽  
Performance Tasks ◽  
Trade Off ◽  
Test Experiment ◽  
Trade Offs ◽  
New Finding ◽  
Sternberg Paradigm ◽  
Speed Accuracy ◽  
Speed And Accuracy

In most work contexts, several performance goals coexist, and conflicts between them and trade-offs can occur. Our paper is the first to contrast a dual goal for speed and accuracy with a single goal for speed on the same task. The Sternberg paradigm (Experiment 1, n = 57) and the d2 test (Experiment 2, n = 19) were used as performance tasks. Speed measures and errors revealed in both experiments that dual as well as single goals increase performance by enhancing memory scanning. However, the single speed goal triggered a speed-accuracy trade-off, favoring speed over accuracy, whereas this was not the case with the dual goal. In difficult trials, dual goals slowed down scanning processes again so that errors could be prevented. This new finding is particularly relevant for security domains, where both aspects have to be managed simultaneously.

The Effects of Decision Time on Perceptions of Decisions and Decision Makers in (Moral) Trade-Off Scenarios

2019 ◽  
Author(s):  
Anna Katharina Spälti ◽  
Mark John Brandt ◽  
Marcel Zeelenberg
Keyword(s):  
Decision Process ◽  
Decision Time ◽  
Decision Makers ◽  
Process Information ◽  
Total N ◽  
Trade Off ◽  
Financial Gain ◽  
Trade Offs ◽  
Sacred Values ◽  
Moral Context

People often have to make trade-offs. We study three types of trade-offs: 1) "secular trade-offs" where no moral or sacred values are at stake, 2) "taboo trade-offs" where sacred values are pitted against financial gain, and 3) "tragic trade-offs" where sacred values are pitted against other sacred values. Previous research (Critcher et al., 2011; Tetlock et al., 2000) demonstrated that tragic and taboo trade-offs are not only evaluated by their outcomes, but are also evaluated based on the time it took to make the choice. We investigate two outstanding questions: 1) whether the effect of decision time differs for evaluations of decisions compared to decision makers and 2) whether moral contexts are unique in their ability to influence character evaluations through decision process information. In two experiments (total N = 1434) we find that decision time affects character evaluations, but not evaluations of the decision itself. There were no significant differences between tragic trade-offs and secular trade-offs, suggesting that the decisions structure may be more important in evaluations than moral context. Additionally, the magnitude of the effect of decision time shows us that decision time, may be of less practical use than expected. We thus urge, to take a closer examination of the processes underlying decision time and its perception.

Predicting Undesired Treatment Outcome in Mental Healthcare: Machine Learning Study (Preprint)

2019 ◽  
Author(s):  
Kasper Van Mens ◽  
Joran Lokkerbol ◽  
Richard Janssen ◽  
Robert de Lange ◽  
Bea Tiemens
Keyword(s):  
Machine Learning ◽  
Treatment Outcome ◽  
Mental Health Treatment ◽  
Mental Healthcare ◽  
Machine Learning Algorithms ◽  
Gradient Boosting ◽  
Trade Off ◽  
Trade Offs ◽  
Outcome Monitoring ◽  
Extreme Gradient Boosting

BACKGROUND It remains a challenge to predict which treatment will work for which patient in mental healthcare. OBJECTIVE In this study we compare machine algorithms to predict during treatment which patients will not benefit from brief mental health treatment and present trade-offs that must be considered before an algorithm can be used in clinical practice. METHODS Using an anonymized dataset containing routine outcome monitoring data from a mental healthcare organization in the Netherlands (n = 2,655), we applied three machine learning algorithms to predict treatment outcome. The algorithms were internally validated with cross-validation on a training sample (n = 1,860) and externally validated on an unseen test sample (n = 795). RESULTS The performance of the three algorithms did not significantly differ on the test set. With a default classification cut-off at 0.5 predicted probability, the extreme gradient boosting algorithm showed the highest positive predictive value (ppv) of 0.71(0.61 – 0.77) with a sensitivity of 0.35 (0.29 – 0.41) and area under the curve of 0.78. A trade-off can be made between ppv and sensitivity by choosing different cut-off probabilities. With a cut-off at 0.63, the ppv increased to 0.87 and the sensitivity dropped to 0.17. With a cut-off of at 0.38, the ppv decreased to 0.61 and the sensitivity increased to 0.57. CONCLUSIONS Machine learning can be used to predict treatment outcomes based on routine monitoring data.This allows practitioners to choose their own trade-off between being selective and more certain versus inclusive and less certain.

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