An Architecture for a Dependable Distributed Sensor System

Zug, Sebastian; Dietrich, André; Kaiser, Jörg

doi:10.1109/tim.2010.2085871

Cited by 17 publications

(8 citation statements)

References 38 publications

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“…Sensor dependability, in turn, is a function of their ability to provide accurate measurements, to be resistant to environmental factors and events, and to properly transmit these measurements [69]. Currently, only limited research has been devoted to smart sensor architectures that incorporate fault detection and isolation [20,77], thus present sensor deployments may have only moderate dependability. Dependability may also be threatened because sensors cannot be equipped with a direct, permanent source of power [61].…”

Section: Sensor Dependabilitymentioning

confidence: 99%

Social media enabled human sensing for smart cities

Doran

Severin

Gokhale

et al. 2015

AIC

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Smart city initiatives rely on real-time measurements and data collected by a large number of heterogenous physical sensors deployed throughout a city. Physical sensors, however, are fraught with interoperability, dependability, management, and political challenges. Furthermore, these sensors are unable to sense the opinions and emotional reactions of citizens that invariably impact smart city initiatives. Yet everyday, millions of dwellers and visitors of a city share their observations, thoughts, feelings, and experiences, or in other words, their perceptions about their city through social media updates. This paper reasons why "human sensors", namely, citizens that share information about their surroundings via social media can supplement, complement, or even replace the information measured by physical sensors. We present a methodology based on probabilistic language modeling to extract and visualize such perceptions that may be relevant to smart cities from social media updates. Using more than six million geo-tagged tweets collected over regions that feature widely varying geographical, social, cultural, and political characteristics and tweet densities, we illustrate the potential of social media enabled human sensing to address diverse smart city challenges.

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Section: Sensor Dependabilitymentioning

confidence: 99%

Social media enabled human sensing for smart cities

Doran

Severin

Gokhale

et al. 2015

AIC

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“…Approaches comparable to ours are the sensor fusion architectures proposed by Elmenreich [5], Hightower et al [6] and Zug et al [7]. Elmenreich's approach was developed in the context of the Time-Triggered Architecture [8] and does not take jitter into account.…”

Section: Related Workmentioning

confidence: 98%

Design by uncertainty: Towards the use of measurement uncertainty in real-time systems

Ulbrich

Franzmann

Scheler

et al. 2012

7th IEEE International Symposium on Industrial Embedded Systems (SIES'12)

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Abstract-Real-time systems usually incorporate a wide variety of challenges: A control engineer, for example, aims for the highest possible control quality achievable. Here, one key element is to minimise the uncertainty of the measurements. This, to put it simple, is the noise of sensor data, which has a negative effect on control. Although measurement uncertainty is well treated in control theory, it is usually ignored in common real-time architectures where temporal properties are the prevalent criteria. Consequently, the communication between control engineers and real-time specialists is rather one way, revolving around deadlines and sampling periods. However, on closer examination, many real-time properties are derived from the measurement uncertainty aspired by the control engineer. Conversely, temporal variations, virtually inevitable in practice, can be represented as measurement uncertainty as well.Tackling the measurement uncertainty should therefore be an interdisciplinary task: The control system respects the actual run-time conditions instead of estimating them. Likewise, the real-time system considers measurement uncertainty rather than blindly sticking to deadlines. In this paper we present an uncertainty-centric approach to leverage measurement uncertainty in real-time architectures, not only at design time but also at run-time. Using measurement uncertainty as an explicit interface minimises the gap between real-time specialists and control engineers and facilitates a modular and flexible system design. Our preliminary results are promising and show the ease of use and the applicability to existing systems.

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“…In KARYON we performed a failure mode analysis for different sensors and identified several fault modes that were categorized along five main dimensions: delay faults, sporadic offset faults, permanent offset faults, stochastic offset faults and stuck-at faults. The details of these results are provided in [42].…”

Section: A Failure Semantics In Sensor-based Systemsmentioning

confidence: 99%

The KARYON project: Predictable and safe coordination in cooperative vehicular systems

Casimiro¹,

Kaiser

Schiller

et al. 2013

2013 43rd Annual IEEE/IFIP Conference on Dependable Systems and Networks Workshop (DSN-W)

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KARYON, a kernel-based architecture for safety-critical control, is a European project that proposes a new perspective to improve performance of smart vehicle coordination. The key objective of KARYON is to provide system solutions for predictable and safe coordination of smart vehicles that autonomously cooperate and interact in an open and inherently uncertain environment. One of the main challenges is to ensure high performance levels of vehicular functionality in the presence of uncertainties and failures. This paper describes some of the steps being taken in KARYON to address this challenge, from the definition of a suitable architectural pattern to the development of proof-of-concept prototypes intended to show the applicability of the KARYON solutions. The project proposes a safety architecture that exploits the concept of architectural hybridization to define systems in which a small local safety kernel can be built for guaranteeing functional safety along a set of safety rules. KARYON is also developing a fault model and fault semantics for distributed, continuous-valued sensor systems, which allows abstracting specific sensor faults and facilitates the definition of safety rules in terms of quality of perception. Solutions for improved communication predictability are proposed, ranging from network inaccessibility control at lower communication levels to protocols for assessment of cooperation state at the process level. KARYON contributions include improved simulation and fault-injection tools for evaluating safety assurance according to the ISO 26262 safety standard. The results will be assessed using selected use cases in the automotive and avionic domains.

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An Architecture for a Dependable Distributed Sensor System

Cited by 17 publications

References 38 publications

Social media enabled human sensing for smart cities

Social media enabled human sensing for smart cities

Design by uncertainty: Towards the use of measurement uncertainty in real-time systems

The KARYON project: Predictable and safe coordination in cooperative vehicular systems

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