285,087 research outputs found
Distributed Real-Time Emulation of Formally-Defined Patterns for Safe Medical Device Control
Safety of medical devices and of their interoperation is an unresolved issue
causing severe and sometimes deadly accidents for patients with shocking
frequency. Formal methods, particularly in support of highly reusable and
provably safe patterns which can be instantiated to many device instances can
help in this regard. However, this still leaves open the issue of how to pass
from their formal specifications in logical time to executable emulations that
can interoperate in physical time with other devices and with simulations of
patient and/or doctor behaviors. This work presents a specification-based
methodology in which virtual emulation environments can be easily developed
from formal specifications in Real-Time Maude, and can support interactions
with other real devices and with simulation models. This general methodology is
explained in detail and is illustrated with two concrete scenarios which are
both instances of a common safe formal pattern: one scenario involves the
interaction of a provably safe pacemaker with a simulated heart; the other
involves the interaction of a safe controller for patient-induced analgesia
with a real syringe pump.Comment: In Proceedings RTRTS 2010, arXiv:1009.398
AI Solutions for MDS: Artificial Intelligence Techniques for Misuse Detection and Localisation in Telecommunication Environments
This report considers the application of Articial Intelligence (AI) techniques to
the problem of misuse detection and misuse localisation within telecommunications
environments. A broad survey of techniques is provided, that covers inter alia
rule based systems, model-based systems, case based reasoning, pattern matching,
clustering and feature extraction, articial neural networks, genetic algorithms, arti
cial immune systems, agent based systems, data mining and a variety of hybrid
approaches. The report then considers the central issue of event correlation, that
is at the heart of many misuse detection and localisation systems. The notion of
being able to infer misuse by the correlation of individual temporally distributed
events within a multiple data stream environment is explored, and a range of techniques,
covering model based approaches, `programmed' AI and machine learning
paradigms. It is found that, in general, correlation is best achieved via rule based approaches,
but that these suffer from a number of drawbacks, such as the difculty of
developing and maintaining an appropriate knowledge base, and the lack of ability
to generalise from known misuses to new unseen misuses. Two distinct approaches
are evident. One attempts to encode knowledge of known misuses, typically within
rules, and use this to screen events. This approach cannot generally detect misuses
for which it has not been programmed, i.e. it is prone to issuing false negatives.
The other attempts to `learn' the features of event patterns that constitute normal
behaviour, and, by observing patterns that do not match expected behaviour, detect
when a misuse has occurred. This approach is prone to issuing false positives,
i.e. inferring misuse from innocent patterns of behaviour that the system was not
trained to recognise. Contemporary approaches are seen to favour hybridisation,
often combining detection or localisation mechanisms for both abnormal and normal
behaviour, the former to capture known cases of misuse, the latter to capture
unknown cases. In some systems, these mechanisms even work together to update
each other to increase detection rates and lower false positive rates. It is concluded
that hybridisation offers the most promising future direction, but that a rule or state
based component is likely to remain, being the most natural approach to the correlation
of complex events. The challenge, then, is to mitigate the weaknesses of
canonical programmed systems such that learning, generalisation and adaptation
are more readily facilitated
Formal Modeling of Connectionism using Concurrency Theory, an Approach Based on Automata and Model Checking
This paper illustrates a framework for applying formal methods techniques, which are symbolic in nature, to specifying and verifying neural networks, which are sub-symbolic in nature. The paper describes a communicating automata [Bowman & Gomez, 2006] model of neural networks. We also implement the model using timed automata [Alur & Dill, 1994] and then undertake a verification of these models using the model checker Uppaal [Pettersson, 2000] in order to evaluate the performance of learning algorithms. This paper also presents discussion of a number of broad issues concerning cognitive neuroscience and the debate as to whether symbolic processing or connectionism is a suitable representation of cognitive systems. Additionally, the issue of integrating symbolic techniques, such as formal methods, with complex neural networks is discussed. We then argue that symbolic verifications may give theoretically well-founded ways to evaluate and justify neural learning systems in the field of both theoretical research and real world applications
PALS-Based Analysis of an Airplane Multirate Control System in Real-Time Maude
Distributed cyber-physical systems (DCPS) are pervasive in areas such as
aeronautics and ground transportation systems, including the case of
distributed hybrid systems. DCPS design and verification is quite challenging
because of asynchronous communication, network delays, and clock skews.
Furthermore, their model checking verification typically becomes unfeasible due
to the huge state space explosion caused by the system's concurrency. The PALS
("physically asynchronous, logically synchronous") methodology has been
proposed to reduce the design and verification of a DCPS to the much simpler
task of designing and verifying its underlying synchronous version. The
original PALS methodology assumes a single logical period, but Multirate PALS
extends it to deal with multirate DCPS in which components may operate with
different logical periods. This paper shows how Multirate PALS can be applied
to formally verify a nontrivial multirate DCPS. We use Real-Time Maude to
formally specify a multirate distributed hybrid system consisting of an
airplane maneuvered by a pilot who turns the airplane according to a specified
angle through a distributed control system. Our formal analysis revealed that
the original design was ineffective in achieving a smooth turning maneuver, and
led to a redesign of the system that satisfies the desired correctness
properties. This shows that the Multirate PALS methodology is not only
effective for formal DCPS verification, but can also be used effectively in the
DCPS design process, even before properties are verified.Comment: In Proceedings FTSCS 2012, arXiv:1212.657
Towards an HLA Run-time Infrastructure with Hard Real-time Capabilities
Our work takes place in the context of the HLA standard and its application in real-time systems context. The HLA standard is inadequate for taking into consideration the different constraints involved in real-time computer systems. Many works have been invested in order to providing real-time capabilities to Run Time Infrastructures (RTI) to run real time simulation. Most of these initiatives focus on major issues including QoS guarantee, Worst Case Transit Time (WCTT) knowledge and scheduling services provided by the underlying operating systems. Even if our ultimate objective is to achieve real-time capabilities for distributed HLA federations executions, this paper describes a preliminary work focusing on achieving hard real-time properties for HLA federations running on a single computer under Linux operating systems. Our paper proposes a novel global bottom up approach for designing real-time Run time Infrastructures and a formal model for validation of uni processor to (then) distributed real-time simulation with CERTI
Feedback Control Goes Wireless: Guaranteed Stability over Low-power Multi-hop Networks
Closing feedback loops fast and over long distances is key to emerging
applications; for example, robot motion control and swarm coordination require
update intervals of tens of milliseconds. Low-power wireless technology is
preferred for its low cost, small form factor, and flexibility, especially if
the devices support multi-hop communication. So far, however, feedback control
over wireless multi-hop networks has only been shown for update intervals on
the order of seconds. This paper presents a wireless embedded system that tames
imperfections impairing control performance (e.g., jitter and message loss),
and a control design that exploits the essential properties of this system to
provably guarantee closed-loop stability for physical processes with linear
time-invariant dynamics. Using experiments on a cyber-physical testbed with 20
wireless nodes and multiple cart-pole systems, we are the first to demonstrate
and evaluate feedback control and coordination over wireless multi-hop networks
for update intervals of 20 to 50 milliseconds.Comment: Accepted final version to appear in: 10th ACM/IEEE International
Conference on Cyber-Physical Systems (with CPS-IoT Week 2019) (ICCPS '19),
April 16--18, 2019, Montreal, QC, Canad
Towards adaptive multi-robot systems: self-organization and self-adaptation
Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The development of complex systems ensembles that operate in uncertain environments is a major challenge. The reason for this is that system designers are not able to fully specify the system during specification and development and before it is being deployed. Natural swarm systems enjoy similar characteristics, yet, being self-adaptive and being able to self-organize, these systems show beneficial emergent behaviour. Similar concepts can be extremely helpful for artificial systems, especially when it comes to multi-robot scenarios, which require such solution in order to be applicable to highly uncertain real world application. In this article, we present a comprehensive overview over state-of-the-art solutions in emergent systems, self-organization, self-adaptation, and robotics. We discuss these approaches in the light of a framework for multi-robot systems and identify similarities, differences missing links and open gaps that have to be addressed in order to make this framework possible
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