11 research outputs found
Toward composing variable structure models and their interfaces: a case of intensional coupling definitions
In this thesis, we investigate a combination of traditional component-based and variable structure modeling. The focus is on a structural consistent specification of couplings in modular, hierarchical models with a variable structure. For this, we exploitintensional definitions, as known from logic, and introduce a novel intensional coupling definition, which allows a concise yet expressive specification of complex communication and interaction patterns in static as well as variable structure models, without the need to worryabout structural consistency.In der Arbeit untersuchen wir ein Zusammenbringen von klassischer komponenten-basierter und variabler Strukturmodellierung. Der Fokus liegt dabei auf der Spezifikation von strukturkonsistenten Kopplungen in modular-hierarchischen Modellen mit einer variablen Struktur. DafĆ¼r nutzen wir intensionale Definitionen, wie sie aus der Logik bekannt sind, und fĆ¼hren ein neuartiges Konzept von intensionalen Kopplungen ein, welches kompakte gleichzeitig ausdrucksstarke Spezifikationen von komplexen Kommunikations- und Interaktionsmuster in statischen und variablen Strukturmodellen erlaubt
Energy-aware design of hardware and software for ultra-low-power systems
Future visions of the Internet of Things and Industry 4.0
demand for large scale deployments of mobile devices while removing
the numerous disadvantages of using batteries: degradation, scale, weight,
pollution, and costs. However, this requires computing platforms with extremely
low energy consumptions, and thus employ ultra-low-power hardware, energy
harvesting solutions, and highly efficient power-management hardware and
software.
The goal of these power management solutions is to either achieve power
neutrality, a condition where energy harvest and energy consumption equalize
while maximizing the service quality, or to enhance power efficiency for
conserving energy reserves. To reach these goals, intelligent power-management
decisions are needed that utilize precise energy data.
This thesis discusses the measurement of energy in embedded systems, both
online and by external equipment, and the utilization of the acquired data for
modeling the power consumption states of each involved hardware component.
Furthermore, a method is shown to use the resulting models by instrumenting
preexisting device drivers.
These drivers enable new functionalities, such as online energy accounting and
energy application interfaces, and facilitate intelligent power management
decisions.
In order to reduce additional efforts for device driver reimplementation and
the violation of the separation of concerns paradigm, the approach shown
in this thesis synthesizes instrumentation aspects for an
aspect oriented programming language, so that the original device-driver
source code remains unaffected.
Eventually, an automated process of energy measurement and data
analysis is presented. This process is able to yield precise energy models
with low manual effort. In combination with the instrumentation synthesis of
aspect code, this method enables an accelerated creation process for energy
models of ultra-low-power systems. For all proposed methods,
empirical accuracy and overhead measurements are presented.
To support the claims of the author, first practical energy aware and
wireless-radio networked applications are showcased: An energy-neutral light
sensor, a photovoltaic-powered seminar-room door plate, and a sensor network
experiment testbed for research and education
Higher Order Mutation Testing
Mutation testing is a fault-based software testing technique that has been studied widely for over three decades. To date, work in this field has focused largely on first order mutants because it is believed that higher order mutation testing is too computationally expensive to be practical. This thesis argues that some higher order mutants are potentially better able to simulate real world faults and to reveal insights into programming bugs than the restricted class of first order mutants. This thesis proposes a higher order mutation testing paradigm which combines valuable higher order mutants and non-trivial first order mutants together for mutation testing. To overcome the exponential increase in the number of higher order mutants a search process that seeks fit mutants (both first and higher order) from the space of all possible mutants is proposed. A fault-based higher order mutant classification scheme is introduced. Based on different types of fault interactions, this approach classifies higher order mutants into four categories: expected, worsening, fault masking and fault shifting. A search-based approach is then proposed for locating subsuming and strongly subsuming higher order mutants. These mutants are a subset of fault mask and fault shift classes of higher order mutants that are more difficult to kill than their constituent first order mutants. Finally, a hybrid test data generation approach is introduced, which combines the dynamic symbolic execution and search based software testing approaches to generate strongly adequate test data to kill first and higher order mutants
Parallel and Distributed Computing
The 14 chapters presented in this book cover a wide variety of representative works ranging from hardware design to application development. Particularly, the topics that are addressed are programmable and reconfigurable devices and systems, dependability of GPUs (General Purpose Units), network topologies, cache coherence protocols, resource allocation, scheduling algorithms, peertopeer networks, largescale network simulation, and parallel routines and algorithms. In this way, the articles included in this book constitute an excellent reference for engineers and researchers who have particular interests in each of these topics in parallel and distributed computing
Towards Simulation and Emulation of Large-Scale Computer Networks
Developing analytical models that can accurately describe behaviors of Internet-scale networks is difficult. This is due, in part, to the heterogeneous structure, immense size and rapidly changing properties of today\u27s networks. The lack of analytical models makes large-scale network simulation an indispensable tool for studying immense networks. However, large-scale network simulation has not been commonly used to study networks of Internet-scale. This can be attributed to three factors: 1) current large-scale network simulators are geared towards simulation research and not network research, 2) the memory required to execute an Internet-scale model is exorbitant, and 3) large-scale network models are difficult to validate. This dissertation tackles each of these problems.
First, this work presents a method for automatically enabling real-time interaction, monitoring, and control of large-scale network models. Network researchers need tools that allow them to focus on creating realistic models and conducting experiments. However, this should not increase the complexity of developing a large-scale network simulator. This work presents a systematic approach to separating the concerns of running large-scale network models on parallel computers and the user facing concerns of configuring and interacting with large-scale network models.
Second, this work deals with reducing memory consumption of network models. As network models become larger, so does the amount of memory needed to simulate them. This work presents a comprehensive approach to exploiting structural duplications in network models to dramatically reduce the memory required to execute large-scale network experiments.
Lastly, this work addresses the issue of validating large-scale simulations by integrating real protocols and applications into the simulation. With an emulation extension, a network simulator operating in real-time can run together with real-world distributed applications and services. As such, real-time network simulation not only alleviates the burden of developing separate models for applications in simulation, but as real systems are included in the network model, it also increases the confidence level of network simulation. This work presents a scalable and flexible framework to integrate real-world applications with real-time simulation
RFID Technology in Intelligent Tracking Systems in Construction Waste Logistics Using Optimisation Techniques
Construction waste disposal is an urgent issue
for protecting our environment. This paper proposes a
waste management system and illustrates the work
process using plasterboard waste as an example, which
creates a hazardous gas when land filled with household
waste, and for which the recycling rate is less than 10%
in the UK. The proposed system integrates RFID
technology, Rule-Based Reasoning, Ant Colony
optimization and knowledge technology for auditing
and tracking plasterboard waste, guiding the operation
staff, arranging vehicles, schedule planning, and also
provides evidence to verify its disposal. It h relies on
RFID equipment for collecting logistical data and uses
digital imaging equipment to give further evidence; the
reasoning core in the third layer is responsible for
generating schedules and route plans and guidance, and
the last layer delivers the result to inform users. The
paper firstly introduces the current plasterboard
disposal situation and addresses the logistical problem
that is now the main barrier to a higher recycling rate,
followed by discussion of the proposed system in terms
of both system level structure and process structure.
And finally, an example scenario will be given to
illustrate the systemās utilization
SystĆØme informatique d'aide Ć la modĆ©lisation mathĆ©matique basĆ© sur un langage de programmation dĆ©diĆ© pour les systĆØmes dynamiques discrets stochastiques.Application aux modĆØles de croissance de plantes.
In agriculture, in order to predict crop yield or to reduce inputs, mathematical models of plant growth open new perspectives by simulating crop growth in interaction with the environment. In this thesis we will particularly focus on āmechanisticā models based on the description of ecophysiological and archictectural processes in plants.Since the first attempts, in the seventies, the scientific community has created a large number of models with va- rious objectives : for instance, CERES, STICS, APSIM, LNAS as crop models and LIGNUM, ADEL, GreenLab, MAppleT as functional-structural models.These models have to be designed and evaluated with a rigourous process in several steps, according to what is usually described as āgood modelling practicesā. The methods involved in the different steps are : sensitivity and uncertainty analysis, parameter estimation, model selection, data assimilation, optimal control ... According to the configuration of the study case, various algorithms can be used at each of these steps. The state-of-the-art software systems generally focus on one aspect of the global workflow, but very few focus on the workflow itself and propose the whole chain of mathematical methodologies adapted to the type of models and configurations faced in plant growth modelling : stochastic and nonlinear dynamical models involving a lot of processes and parameters, heterogeneous and irregular system observations.This thesis considers the formalization of stochastic dynamical models, of statistical methods and algorithms dedicated to their study and of the interface between models and algorithms to generate the analysis workflow. We deduce the conception of a software platform which allows modelers (or more exactly modelling teams, since the activity is quite complex) to create and validate crop/plant models by using a single language and dedicated statistical tools. Our system facilitates model design, sensitivity and uncertainty analysis, parameter estimation and evaluation from experimental data and optimization.Our research is at the heart of āquantitative agronomyā which combines agronomy, modeling, statistics and computer science. We describe and formalize the type of models faced in agronomy and plant sciences and how we simulate them. We detail the good modelling practices workflow and which algorithms are available at all steps. Thanks to this formalization and tools, model studies can be conducted in an easier and more efficient way. It is illustrated on several test cases, particularly for the LNAS and STICS models. Based on this conception and results, we also discuss the possibility to deduce an ontology and a domain-specific language in order to improve the communication between experts. Finally, we conclude about the perspectives in terms of community platforms, first generally for modellers, and second more specifically in quantitative agronomy.Afin de preĢvoir les rendements ou reĢduire la consommation dāintrants nous pouvons, en exploitant les donneĢes expeĢrimentales, creĢer des modeĢles matheĢmatiques afin de simuler la croissance des cultures en fonction des caracteĢristiques de lāenvironnement. Dans cette optique, cette theĢse sāinteĢresse particulieĢrement aux modeĢles dits āmeĢcanistesā.Des premieĢres tentatives, dans les anneĢes 70, aĢ nos jours, il y a eu pleĢthore de nouveaux modeĢles creĢeĢs, aĢ diffeĢrentes eĢchelles, afin dāeĢtudier certains pheĢnomeĢnes dans les cultures ou au sein des plantes. On peut par exemple citer : CERES, STICS, APSIM, LNAS pour les modeĢles dits de culture ou LIGNUM, ADEL, GreenLab, MAppleT, pour les modeĢles dits structure-fonction.Ces modeĢles neĢcessitent dāeĢtre creĢeĢs et eĢvalueĢs en conduisant une analyse rigoureuse posseĢdant de nombreuses eĢtapes et dont chacune est composeĢe de plusieurs algorithmes complexes. Cette eĢtude devrait sāinscrire dans une deĢmarche dite de bonnes pratiques de modeĢlisation, āGood Modelling Practicesā. On peut citer comme fonctionnaliteĢs : lāanalyse de sensibiliteĢ, lāestimation parameĢtrique, lāanalyse dāincertitude, lāassimilation de donneĢes, la seĢlection de modeĢles, le controĢle optimal ... En fonction de la configuration du cas, chacune de ces fonctionnaliteĢs peut faire appel aĢ un grand nombre dāalgorithmes avec chacun des caracteĢristiques propres. On retrouve dans lāeĢtat de lāart des plateformes qui sāoccupent souvent dāune fonctionnaliteĢ mais treĢs rarement qui sāattaquent aĢ lāensemble de la chaiĢne de travail.Cette theĢse propose une formalisation des modeĢles dynamiques stochastiques (cadre adapteĢ aĢ la modeĢlisation des plantes), de meĢthodes et algorithmes statistiques deĢdieĢs aĢ leur eĢtude et de lāinterfacĢ§age entre les modeĢles et les algorithmes dans cette chaiĢne de travail. Nous en deĢduisons la conception dāun systeĢme informatique (ou plateforme logicielle) permettant dāaider les modeĢlisateurs, ou plutoĢt les eĢquipes de modeĢlisation tant lāactiviteĢ est complexe et transverse, afin de creĢer et valider des modeĢles agronomiques par le truchement dāun langage deĢdieĢ et dāoutils statistiques associeĢs. Le systeĢme facilite ainsi lāeĢcriture des modeĢles, leur analyse de sensibiliteĢ, leur identification parameĢtrique et leur eĢvaluation aĢ partir de donneĢes expeĢrimentales, leur optimisation. Notre domaine dāeĢtude est au coeur de ālāagronomie quantitativeā, qui combine aĢ la fois agronomie, modeĢlisation, statistiques et informatique. Nous deĢcrirons les types de modeĢles matheĢmatiques pris en compte et comment nous les traduisons sur machine afin de permettre des simulations. Puis nous passerons en revue le flux de travail geĢneĢral ainsi que les algorithmes utiliseĢs afin de montrer la conduite geĢneĢrale des eĢtudes qui sont deĢsormais plus facilement et rapidement faisables. Ce flux sera testeĢ sur plusieurs cas dāeĢtude, en particulier pour les modeĢles LNAS et STICS. Finalement, nous ouvrirons sur la possibiliteĢ dāinjecter ces eĢtudes dans une base de connaissance geĢneĢrale, ou ontologie, avec un langage deĢdieĢ avant de conclure sur les perspectives du travail deĢveloppeĢ pour la communauteĢ et notamment celles en termes de plateformes aĢ destination des modeĢlisateurs en geĢneĢral et des utilisateurs des modeĢles agronomiques en particulier
An intelligent intrusion detection system for external communications in autonomous vehicles
Advancements in computing, electronics and mechanical systems have resulted in the creation of a new class of vehicles called autonomous vehicles. These vehicles function using sensory input with an on-board computation system. Self-driving vehicles use an ad hoc vehicular network called VANET. The network has ad hoc infrastructure with mobile vehicles that communicate through open wireless channels.
This thesis studies the design and implementation of a novel intelligent intrusion detection system which secures the external communication of self-driving vehicles. This thesis makes the following four contributions:
It proposes a hybrid intrusion detection system to protect the external
communication in self-driving vehicles from potential attacks. This has been achieved using fuzzification and artificial intelligence. The second contribution is the incorporation of the Integrated Circuit Metrics (ICMetrics) for improved security and privacy. By using the ICMetrics, specific device features have been used to create a unique identity for vehicles. Our work is based on using the bias in on board sensory
systems to create ICMetrics for self-driving vehicles.
The incorporation of fuzzy petri net in autonomous vehicles is the third
contribution of the thesis. Simulation results show that the scheme can successfully detect denial-of-service attacks. The design of a clustering based hierarchical detection system has also been presented to detect worm hole and Sybil attacks. The final contribution of this research is an integrated intrusion detection system which detects various attacks by using a central database in BusNet. The proposed schemes have
been simulated using the data extracted from trace files. Simulation results have been compared and studied for high levels of detection capability and performance. Analysis shows that the proposed schemes provide high detection rate with a low rate of false alarm. The system can detect various attacks in an optimised way owing to a reduction in the number of features, fuzzification
XXIII Congreso Argentino de Ciencias de la ComputaciĆ³n - CACIC 2017 : Libro de actas
Trabajos presentados en el XXIII Congreso Argentino de Ciencias de la ComputaciĆ³n (CACIC), celebrado en la ciudad de La Plata los dĆas 9 al 13 de octubre de 2017, organizado por la Red de Universidades con Carreras en InformĆ”tica (RedUNCI) y la Facultad de InformĆ”tica de la Universidad Nacional de La Plata (UNLP).Red de Universidades con Carreras en InformĆ”tica (RedUNCI