820 research outputs found
Quantitative Verification: Formal Guarantees for Timeliness, Reliability and Performance
Computerised systems appear in almost all aspects of our daily lives, often in safety-critical scenarios such as embedded control systems in cars and aircraft
or medical devices such as pacemakers and sensors. We are thus increasingly reliant on these systems working correctly, despite often operating in unpredictable or unreliable environments. Designers of such devices need ways to guarantee that they will operate in a reliable and efficient manner.
Quantitative verification is a technique for analysing quantitative aspects of a system's design, such as timeliness, reliability or performance. It applies formal methods, based on a rigorous analysis of a mathematical model of the system, to automatically prove certain precisely specified properties, e.g. ``the airbag will always deploy within 20 milliseconds after a crash'' or ``the probability of both sensors failing simultaneously is less than 0.001''.
The ability to formally guarantee quantitative properties of this kind is beneficial across a wide range of application domains. For example, in safety-critical systems, it may be essential to establish credible bounds on the probability with which certain failures or combinations of failures can occur. In embedded control systems, it is often important to comply with strict constraints on timing or resources. More generally, being able to derive guarantees on precisely specified levels of performance or efficiency is a valuable tool in the design of, for example, wireless networking protocols, robotic systems or power management algorithms, to name but a few.
This report gives a short introduction to quantitative verification, focusing in particular on a widely used technique called model checking, and its generalisation to the analysis of quantitative aspects of a system such as timing, probabilistic behaviour or resource usage.
The intended audience is industrial designers and developers of systems such as those highlighted above who could benefit from the application of quantitative verification,but lack expertise in formal verification or modelling
Quality of Context in Context-Aware Systems
Context-aware Systems (CASs) are becoming increasingly popular and can be found in the areas of wearable computing, mobile computing, robotics, adaptive and intelligent user interfaces. Sensors are the corner stone of context capturing however, sensed context data are commonly prone to imperfection due to the technical limitations of sensors, their availability, dysfunction, and highly dynamic nature of environment. Consequently, sensed context data might be imprecise, erroneous, conflicting, or simply missing. To limit the impact of context imperfection on the behavior of a context-aware system, a notion of Quality of Context (QoC) is used to measure quality of any information that is used as context information. Adaptation is performed only if the context data used in the decision-making has an appropriate quality level. This paper reports an analytical review for state of the art quality of context in context-aware systems and points to future research directions
Zigbee over tinyos: Implementation and experimental challenges
The IEEE 802.15.4/Zigbee protocols are a promising technology for Wireless
Sensor Networks (WSNs). This paper shares our experience on the implementation and
use of these protocols and related technologies in WSNs. We present problems and
challenges we have been facing in implementing an IEEE 802.15.4/ZigBee stack for
TinyOS in a two-folded perspective: IEEE 802.15.4/ZigBee protocol standards
limitations (ambiguities and open issues) and technological limitations (hardware and
software). Concerning the former, we address challenges for building scalable and
synchronized multi-cluster ZigBee networks, providing a trade-off between timeliness
and energy-efficiency. On the latter issue, we highlight implementation problems in terms
of hardware, timer handling and operating system limitations. We also report on our
experience from experimental test-beds, namely on physical layer aspects such as
coexistence problems between IEEE 802.15.4 and 802.11 radio channels
Efficient information distribution in the Internet of Medical Things (IoMT)
Towards the world of Internet of Things, people utilize knowledge from sensor
streams in various kinds of smart applications including, but not limited to smart
medical information systems. The number of sensed devices is rapidly increasing
along with the amount of sensing data. Consequently, the bottleneck problem
at the local gateway has become a huge concern given the critical loss and delay
intolerant nature of medical data. Orthogonally to the existing solutions, we
propose sensor data prioritization mechanism to enhance the information quality
while utilizing resources using Value of Information (VoI) at the application
level. Our approach adopts signal processing techniques and information theory
related concepts to assess the VoI. We introduce basic yet convenient ways to
enhance the efficiency of medical information systems, not only when considering
the resource consumption, but also when performing updates, by selecting
appropriate delay for wearable sensors to send data at optimal VoI. Our analysis
shows some interesting results about the correlation and dependency of different
sensor signals, that we use for the value assesment. This preliminary analysis
could be an initiative for further investigation of VoI in medical data transmission
using more advanced methods.Towards the world of Internet of Things, people utilize knowledge from sensor
streams in various kinds of smart applications including, but not limited to smart
medical information systems. The number of sensed devices is rapidly increasing
along with the amount of sensing data. Consequently, the bottleneck problem
at the local gateway has become a huge concern given the critical loss and delay
intolerant nature of medical data. Orthogonally to the existing solutions, we
propose sensor data prioritization mechanism to enhance the information quality
while utilizing resources using Value of Information (VoI) at the application
level. Our approach adopts signal processing techniques and information theory
related concepts to assess the VoI. We introduce basic yet convenient ways to
enhance the efficiency of medical information systems, not only when considering
the resource consumption, but also when performing updates, by selecting
appropriate delay for wearable sensors to send data at optimal VoI. Our analysis
shows some interesting results about the correlation and dependency of different
sensor signals, that we use for the value assesment. This preliminary analysis
could be an initiative for further investigation of VoI in medical data transmission
using more advanced methods
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