Context-driven methodologies for context-aware and adaptive systems

Applications which are both context-aware and adapting, enhance users’ experience by anticipating their need in relation with their environment and adapt their behavior according to environmental changes. Being by definition both context-aware and adaptive these applications suffer both from faults related to their context-awareness and to their adaptive nature plus from a novel variety of faults originated by the combination of the two. This research work analyzes, classifies, detects, and reports faults belonging to this novel class aiming to improve the robustness of these Context-Aware Adaptive Applications (CAAAs). To better understand the peculiar dynamics driving the CAAAs adaptation mechanism a general high-level architectural model has been designed. This architectural model clearly depicts the stream of information coming from sensors and being computed all the way to the adaptation mechanism. The model identifies a stack of common components representing increasing abstractions of the context and their general interconnections. Known faults involving context data can be re-examined according to this architecture and can be classified in terms of the component in which they are happening and in terms of their abstraction from the environment. Resulting from this classification is a CAAA-oriented fault taxonomy. Our architectural model also underlines that there is a common evolutionary path for CAAAs and shows the importance of the adaptation logic. Indeed most of the adaptation failures are caused by invalid interpretations of the context by the adaptation logic. To prevent such faults we defined a model, the Adaptation Finite-State Machine (A-FSM), describing how the application adapts in response to changes in the context. The A-FSM model is a powerful instrument which allows developers to focus in those context-aware and adaptive aspects in which faults reside. In this model we have identified a set of patterns of faults representing the most common faults in this application domain. Such faults are represented as violation of given properties in the A-FSM. We have created four techniques to detect such faults. Our proposed algorithms are based on three different technologies: enumerative, symbolic and goal planning. Such techniques compensate each other. We have evaluated them by comparing them to each other using both crafted models and models extracted from existing commercial and free applications. In the evaluation we observe the validity, the readability of the reported faults, the scalability and their behavior in limited memory environments. We conclude this Thesis by suggesting possible extensions

Analysis And Control Of Networked Systems Using Structural And Measure-Theoretic Approaches

Network control theory provides a plethora of tools to analyze the behavior of dynamical processes taking place in complex networked systems. The pattern of interconnections among components affects the global behavior of the overall system. However, the analysis of the global behavior of large scale complex networked systems offers several major challenges. First of all, analyzing or characterizing the features of large-scale networked systems generally requires full knowledge of the parameters describing the system\u27s dynamics. However, in many applications, an exact quantitative description of the parameters of the system may not be available due to measurement errors and/or modeling uncertainties. Secondly, retrieving the whole structure of many real networks is very challenging due to both computation and security constraints. Therefore, an exact analysis of the global behavior of many real-world networks is practically unfeasible. Finally, the dynamics describing the interactions between components are often stochastic, which leads to difficulty in analyzing individual behaviors in the network. In this thesis, we provide solutions to tackle all the aforementioned challenges. In the first part of the thesis, we adopt graph-theoretic approaches to address the problem caused by inexact modeling and imprecise measurements. More specifically, we leverage the connection between algebra and graph theory to analyze various properties in linear structural systems. Using these results, we then design efficient graph-theoretic algorithms to tackle topology design problems in structural systems. In the second part of the thesis, we utilize measure-theoretic techniques to characterize global properties of a network using local structural information in the form of closed walks or subgraph counts. These methods are based on recent results in real algebraic geometry that relates semidefinite programming to the multidimensional moment problem. We leverage this connection to analyze stochastic networked spreading processes and characterize safety in nonlinear dynamical systems

Statistiline lähenemine mälulekete tuvastamiseks Java rakendustes

Kaasaegsed hallatud käitusaja keskkonnad (ingl. managed runtime environment) ja programmeerimiskeeled lihtsustavad rakenduste loomist ning haldamist. Kõige levinumaks näiteks säärase keele ja keskkonna kohta on Java. Üheks tähtsaks hallatud käitusaja keskkonna ülesandeks on automaatne mäluhaldus. Vaatamata sisseehitatud prügikoristajale, mälulekke probleem Javas on endiselt relevantne ning tähendab tarbetut mälu hoidmist. Probleem on eriti kriitiline rakendustes mis peaksid ööpäevaringselt tõrgeteta toimima, kuna mäluleke on üks väheseid programmeerimisvigu mis võib hävitada kogu Java rakenduse. Parimaks indikaatoriks otsustamaks kas objekt on kasutuses või mitte on objekti viimane kasutusaeg. Selle meetrika põhiliseks puudujäägiks on selle hind jõudluse mõttes. Käesolev väitekiri uurib mälulekete problemaatikat Javas ning pakub välja uudse mälulekkeid tuvastava ning diagnoosiva algoritmi. Väitekirjas kirjeldatakse alternatiivset lähenemisviisi objektide kasutuse hindamiseks. Põhihüpoteesiks on idee et lekkivaid objekte saab statistiliste meetoditega eristada mittelekkivatest kui vaadelda objektide populatsiooni eluiga erinevate gruppide lõikes. Pakutud lähenemine on oluliselt odavama hinnaga jõudluse mõttes, kuna objekti kohta on vaja salvestada infot ainult selle loomise hetkel. Väitekirja uurimistöö tulemusi on rakendatud mälulekete tuvastamise tööriista Plumbr arendamisel, mida hetkel edukalt kasutatakse ka erinevates toodangkeskkondades. Pärast sissejuhatavaid peatükke, väitekirjas vaadeldakse siiani pakutud lahendusi ning on pakutud välja ka nende meetodite klassifikatsioon. Järgnevalt on kirjeldatud statistiline baasmeetod mälulekete tuvastamiseks. Lisaks on analüüsitud ka kirjeldatud baasmeetodi puudujääke. Järgnevalt on kirjeldatud kuidas said defineeritud lisamõõdikud mis aitasid masinõppe abil baasmeetodit täpsemaks teha. Testandmeid masinõppe tarbeks on kogutud Plumbri abil päris rakendustest ning toodangkeskkondadest. Lisaks, kirjeldatakse väitekirjas juhtumianalüüse ning võrdlust ühe olemasoleva mälulekete tuvastamise lahendusega.Modern managed runtime environments and programming languages greatly simplify creation and maintenance of applications. One of the best examples of such managed runtime environments and a language is the Java Virtual Machine and the Java programming language. Despite the built in garbage collector, the memory leak problem is still relevant in Java and means wasting memory by preventing unused objects from being removed. The problem of memory leaks is especially critical for applications, which are expected to work uninterrupted around the clock, as running out of memory is one of a few reasons which may cause the termination of the whole Java application. The best indicator of whether an object is used or not is the time of the last access. However, the main disadvantage of this metric is the incurred performance overhead. Current thesis researches the memory leak problem and proposes a novel approach for memory leak detection and diagnosis. The thesis proposes an alternative approach for estimation of the 'unusedness' of objects. The main hypothesis is that leaked objects may be identified by applying statistical methods to analyze lifetimes of objects, by observing the ages of the population of objects grouped by their allocation points. Proposed solution is much more efficient performance-wise as for each object it is sufficient to record any information at the time of creation of the object. The research conducted for the thesis is utilized in a memory leak detection tool Plumbr. After the introduction and overview of the state of the art, current thesis reviews existing solutions and proposes the classification for memory leak detection approaches. Next, the statistical approach for memory leak detection is described along with the description of the main metric used to distinguish leaking objects from non-leaking ones. Follows the analysis of this single metric. Based on this analysis additional metrics are designed and machine learning algorithms are applied on the statistical data acquired from real production environments from the Plumbr tool. Case studies of real applications and one previous solution for the memory leak detection are performed in order to evaluate performance overhead of the tool

Resilience Against Sensor Deception Attacks at the Supervisory Control Layer of Cyber-Physical Systems: A Discrete Event Systems Approach

Cyber-Physical Systems (CPS) are already ubiquitous in our society and include medical devices, (semi-)autonomous vehicles, and smart grids. However, their security aspects were only recently incorporated into their design process, mainly in response to catastrophic incidents caused by cyber-attacks on CPS. The Stuxnet attack that successfully damaged a nuclear facility, the Maroochy water breach that released millions of gallons of untreated water, the assault on power plants in Brazil that disrupted the distribution of energy in many cities, and the intrusion demonstration that stopped the engine of a 2014 Jeep Cherokee in the middle of a highway are examples of well-publicized cyber-attacks on CPS. There is now a critical need to provide techniques for analyzing the behavior of CPS while under attack and to synthesize attack-resilient CPS. In this dissertation, we address CPS under the influence of an important class of attacks called sensor deception attacks, in which an attacker hijacks sensor readings to inflict damage to CPS. The formalism of regular languages and their finite-state automata representations is used to capture the dynamics of CPS and their attackers, thereby allowing us to leverage the theory of supervisory control of discrete event systems to pose our investigations. First, we focus on developing a supervisory control framework under sensor deception attacks. We focus on two questions: (1) Can we automatically find sensor deception attacks that damage a given CPS? and (2) Can we design a secure-by-construction CPS against sensor deception attacks? Answering these two questions is the main contribution of this dissertation. In the first part of the dissertation, using techniques from the fields of graph games and Markov decision processes, we develop algorithms for synthesizing sensor deception attacks in both qualitative and quantitative settings. Graph games provide the means of synthesizing sensor deception attacks that might damage the given CPS. In a second step, equipped with stochastic information about the CPS, we can leverage Markov decision processes to synthesize attacks with the highest likelihood of damage. In the second part of the dissertation, we tackle the problem of designing secure-by-construction CPS. We provide two different methodologies to design such CPS, in which there exists a trade-off between flexibility on selecting different designs and computational complexity of the methods. The first method is developed based on supervisory control theory, and it provides a computationally efficient way of designing secure CPS. Alternatively, a graph-game method is presented as a second solution for this investigated problem. The graph-game method grants flexible selection of the CPS at the cost of computational complexity. The first method finds one robust supervisor, whereas the second method provides a structure in which all robust supervisors are included. Overall, this dissertation provides a comprehensive set of algorithmic techniques to analyze and mitigate sensor deception attacks at the supervisory layer of cyber-physical control systems.PHDElectrical and Computer EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/166117/1/romulo_1.pd

Peripersonal Space in the Humanoid Robot iCub

Developing behaviours for interaction with objects close to the body is a primary goal for any organism to survive in the world. Being able to develop such behaviours will be an essential feature in autonomous humanoid robots in order to improve their integration into human environments. Adaptable spatial abilities will make robots safer and improve their social skills, human-robot and robot-robot collaboration abilities. This work investigated how a humanoid robot can explore and create action-based representations of its peripersonal space, the region immediately surrounding the body where reaching is possible without location displacement. It presents three empirical studies based on peripersonal space findings from psychology, neuroscience and robotics. The experiments used a visual perception system based on active-vision and biologically inspired neural networks. The first study investigated the contribution of binocular vision in a reaching task. Results indicated the signal from vergence is a useful embodied depth estimation cue in the peripersonal space in humanoid robots. The second study explored the influence of morphology and postural experience on confidence levels in reaching assessment. Results showed that a decrease of confidence when assessing targets located farther from the body, possibly in accordance to errors in depth estimation from vergence for longer distances. Additionally, it was found that a proprioceptive arm-length signal extends the robot’s peripersonal space. The last experiment modelled development of the reaching skill by implementing motor synergies that progressively unlock degrees of freedom in the arm. The model was advantageous when compared to one that included no developmental stages. The contribution to knowledge of this work is extending the research on biologically-inspired methods for building robots, presenting new ways to further investigate the robotic properties involved in the dynamical adaptation to body and sensing characteristics, vision-based action, morphology and confidence levels in reaching assessment.CONACyT, Mexico (National Council of Science and Technology

Robust Observation and Control of Complex Networks

The problem of understanding when individual actions of interacting agents display to a coordinated collective behavior has receiving a considerable attention in many research fields. Especially in control engineering, distributed applications in cooperative environments are achieving resounding success, due to the large number of relevant applications, such as formation control, attitude synchronization tasks and cooperative applications in large-scale systems. Although those problems have been extensively studied in Literature, themost of classic approaches use to consider the unrealistic scenario in which networks always consist of identical, linear, time-invariant entities. It’s clear that this assumption strongly approximates the effective behavior of a network. In fact agents can be subjected to parameter uncertainties, unmodeled dynamics or simply characterized by proper nonlinear dynamics. Therefore, motivated by those practical problems, the present Thesis proposes various approaches for dealing with the problem of observation and control in both the framework of multi-agents and complex interconnected systems. The main contributions of this Thesis consist on the development of several algorithms based on concepts of discontinuous slidingmode control. This techniques can be employed for solving in finite-time problems of robust state estimation and consensus-based synchronization in network of heterogenous nonlinear systems subjected to unknown but bounded disturbances and sudden topological changes. Both directed and undirected topologies have been taken into account. It is worth to mention also the extension of the consensus problem to networks of agents governed by a class parabolic partial differential equation, for which, for the first time, a boundary-based robust local interaction protocol has been presented

Robust Observation and Control of Complex Networks

The problem of understanding when individual actions of interacting agents display to a coordinated collective behavior has receiving a considerable attention in many research fields. Especially in control engineering, distributed applications in cooperative environments are achieving resounding success, due to the large number of relevant applications, such as formation control, attitude synchronization tasks and cooperative applications in large-scale systems. Although those problems have been extensively studied in Literature, themost of classic approaches use to consider the unrealistic scenario in which networks always consist of identical, linear, time-invariant entities. It’s clear that this assumption strongly approximates the effective behavior of a network. In fact agents can be subjected to parameter uncertainties, unmodeled dynamics or simply characterized by proper nonlinear dynamics. Therefore, motivated by those practical problems, the present Thesis proposes various approaches for dealing with the problem of observation and control in both the framework of multi-agents and complex interconnected systems. The main contributions of this Thesis consist on the development of several algorithms based on concepts of discontinuous slidingmode control. This techniques can be employed for solving in finite-time problems of robust state estimation and consensus-based synchronization in network of heterogenous nonlinear systems subjected to unknown but bounded disturbances and sudden topological changes. Both directed and undirected topologies have been taken into account. It is worth to mention also the extension of the consensus problem to networks of agents governed by a class parabolic partial differential equation, for which, for the first time, a boundary-based robust local interaction protocol has been presented

A new approach to the development and maintenance of industrial sequence logic

This thesis is concerned with sequence logic as found in industrial control systems, with the focus being on process and manufacturing control systems. At its core is the assertion that there is a need for a better approach to the development of industrial sequence logic to satisfy the life-cycle requirements, and that many of the ingredients required to deliver such an approach are now available. The needs are discussed by considering the business case for automation and deficiencies with traditional approaches. A set of requirements is then derived for an integrated development environment to address the business needs throughout the control system life-cycle. The strengths and weaknesses of relevant control system technology and standards are reviewed and their bias towards implementation described. Mathematical models, graphical methods and software tools are then assessed with respect to the requirements for an integrated development environment. A solution to the requirements, called Synect is then introduced. Synect combines a methodology using familiar graphical notations with Petri net modelling supported by a set of software tools. Its key features are justified with reference to the requirements. A set of case studies forms the basis of an evaluation against business needs by comparing the Synect methodology with current approaches. The industrial relevance and exploitation are then briefly described. The thesis ends with a review of the key conclusions along with contributions to knowledge and suggestions for further research

CTL Model Update for System Modifications

Model checking is a promising technology, which has been applied for verification of many hardware and software systems. In this paper, we introduce the concept of model update towards the development of an automatic system modification tool that extends model checking functions. We define primitive update operations on the models of Computation Tree Logic (CTL) and formalize the principle of minimal change for CTL model update. These primitive update operations, together with the underlying minimal change principle, serve as the foundation for CTL model update. Essential semantic and computational characterizations are provided for our CTL model update approach. We then describe a formal algorithm that implements this approach. We also illustrate two case studies of CTL model updates for the well-known microwave oven example and the Andrew File System 1, from which we further propose a method to optimize the update results in complex system modifications

Proceedings of the 21st Conference on Formal Methods in Computer-Aided Design – FMCAD 2021

The Conference on Formal Methods in Computer-Aided Design (FMCAD) is an annual conference on the theory and applications of formal methods in hardware and system verification. FMCAD provides a leading forum to researchers in academia and industry for presenting and discussing groundbreaking methods, technologies, theoretical results, and tools for reasoning formally about computing systems. FMCAD covers formal aspects of computer-aided system design including verification, specification, synthesis, and testing