Taming Uncertainty in the Assurance Process of Self-Adaptive Systems: a Goal-Oriented Approach

Goals are first-class entities in a self-adaptive system (SAS) as they guide the self-adaptation. A SAS often operates in dynamic and partially unknown environments, which cause uncertainty that the SAS has to address to achieve its goals. Moreover, besides the environment, other classes of uncertainty have been identified. However, these various classes and their sources are not systematically addressed by current approaches throughout the life cycle of the SAS. In general, uncertainty typically makes the assurance provision of SAS goals exclusively at design time not viable. This calls for an assurance process that spans the whole life cycle of the SAS. In this work, we propose a goal-oriented assurance process that supports taming different sources (within different classes) of uncertainty from defining the goals at design time to performing self-adaptation at runtime. Based on a goal model augmented with uncertainty annotations, we automatically generate parametric symbolic formulae with parameterized uncertainties at design time using symbolic model checking. These formulae and the goal model guide the synthesis of adaptation policies by engineers. At runtime, the generated formulae are evaluated to resolve the uncertainty and to steer the self-adaptation using the policies. In this paper, we focus on reliability and cost properties, for which we evaluate our approach on the Body Sensor Network (BSN) implemented in OpenDaVINCI. The results of the validation are promising and show that our approach is able to systematically tame multiple classes of uncertainty, and that it is effective and efficient in providing assurances for the goals of self-adaptive systems

CMOS design of chaotic oscillators using state variables: a monolithic Chua's circuit

This paper presents design considerations for monolithic implementation of piecewise-linear (PWL) dynamic systems in CMOS technology. Starting from a review of available CMOS circuit primitives and their respective merits and drawbacks, the paper proposes a synthesis approach for PWL dynamic systems, based on state-variable methods, and identifies the associated analog operators. The GmC approach, combining quasi-linear VCCS's, PWL VCCS's, and capacitors is then explored regarding the implementation of these operators. CMOS basic building blocks for the realization of the quasi-linear VCCS's and PWL VCCS's are presented and applied to design a Chua's circuit IC. The influence of GmC parasitics on the performance of dynamic PWL systems is illustrated through this example. Measured chaotic attractors from a Chua's circuit prototype are given. The prototype has been fabricated in a 2.4- mu m double-poly n-well CMOS technology, and occupies 0.35 mm/sup 2/, with a power consumption of 1.6 mW for a +or-2.5-V symmetric supply. Measurements show bifurcation toward a double-scroll Chua's attractor by changing a bias current

Transcriptional control of the H-NS antagonists LeuO and RcsB-BglJ in Escherichia coli

The bacterial nucleoid-associated protein (NAP) H-NS is involved in the organization and compaction of the bacterial chromatin and acts as a global respressor, mainly of genes that have been acquired by horizontal gene transfer and that are related to stress responses and pathogenicity. Binding of H-NS to the DNA and formation of a nucleoprotein complex at promoter regions leads to repression. This repressor effect of H-NS can be antagonized by gene-specific transcription factors (H-NS antagonists) that activate transcription of H NS-repressed genes by competing with H-NS for binding or by disturbing formation of the nucleoprotein complex. Two examples of such H NS antagonists are the LysR-type transcription factor LeuO and the FixJ/NarL-type transcription factor heterodimer RcsB-BglJ. LeuO is a pleiotropic regulator of stress responses and virulence determinants. RcsB-BglJ activates transcription of the H NS-repressed bgl (aryl-β,D-glucoside) operon. In this work, novel targets of RcsB-BglJ were identified in Escherichia coli by microarray analyses. The results suggest that heterodimerization of RcsB and BglJ is essential for regulation. Further, in addition to genes related to unknown or predicted function in the membrane the leuO gene was identified as a target gene. Detailed analysis of transcriptional regulation of leuO demonstrated that RcsB-BglJ strongly activates transcription of leuO by binding proximal to a newly mapped leuO promoter. Thus RcsB-BglJ antagonizes repression of leuO by H-NS and the H-NS-like protein StpA. Additional data presented here show that LeuO negatively autoregulates its own expression and inhibits activation of leuO by RcsB-BglJ. Regulation of leuO by RcsB-BglJ and autoregulation by LeuO, as shown here, as well as activation of bglJ by LeuO, as published previously, indicates a feedback control mechanism of two global transcriptional regulators and H-NS antagonists.This feedback regulation may ensure turn on of their expression in response to specific environmental signals. Screens to search for novel regulators or upstream signals were performed by transposon mutagenesis and by using a genomic expression library. These screens indicate that additional factors may be involved in the regulation of this leuO-bglJ feedback loop

Adaptive-smith predictor for controlling an automotive electronic throttle over network

The paper presents a control strategy for an automotive electronic throttle, a device used to regulate the power produced by spark-ignition engines. Controlling the electronic throttle body is a difficult task because the throttle accounts strong nonlinearities. The difficulty increases when the control works through communication networks subject to random delay. In this paper, we revisit the Smith-predictor control, and show how to adapt it for controlling the electronic throttle body over a delay-driven network. Experiments were carried out in a laboratory, and the corresponding data indicate the benefits of our approach for applications.Peer ReviewedPostprint (published version

Approximations and their consequences for dynamic modelling of signal transduction pathways

Signal transduction is the process by which the cell converts one kind of signal or stimulus into another. This involves a sequence of biochemical reactions, carried out by proteins. The dynamic response of complex cell signalling networks can be modelled and simulated in the framework of chemical kinetics. The mathematical formulation of chemical kinetics results in a system of coupled differential equations. Simplifications can arise through assumptions and approximations. The paper provides a critical discussion of frequently employed approximations in dynamic modelling of signal transduction pathways. We discuss the requirements for conservation laws, steady state approximations, and the neglect of components. We show how these approximations simplify the mathematical treatment of biochemical networks but we also demonstrate differences between the complete system and its approximations with respect to the transient and steady state behavior

Integrated chaos generators

This paper surveys the different design issues, from mathematical model to silicon, involved on the design of integrated circuits for the generation of chaotic behavior.Comisión Interministerial de Ciencia y Tecnología 1FD97-1611(TIC)European Commission ESPRIT 3110

Phenotypic Variation and Bistable Switching in Bacteria

Microbial research generally focuses on clonal populations. However, bacterial cells with identical genotypes frequently display different phenotypes under identical conditions. This microbial cell individuality is receiving increasing attention in the literature because of its impact on cellular differentiation, survival under selective conditions, and the interaction of pathogens with their hosts. It is becoming clear that stochasticity in gene expression in conjunction with the architecture of the gene network that underlies the cellular processes can generate phenotypic variation. An important regulatory mechanism is the so-called positive feedback, in which a system reinforces its own response, for instance by stimulating the production of an activator. Bistability is an interesting and relevant phenomenon, in which two distinct subpopulations of cells showing discrete levels of gene expression coexist in a single culture. In this chapter, we address techniques and approaches used to establish phenotypic variation, and relate three well-characterized examples of bistability to the molecular mechanisms that govern these processes, with a focus on positive feedback.