Hierarchical control of multiple resources in distributed real-time and embedded systems

Real-time and embedded systems have traditionally been designed for closed environments where operating conditions, input workloads, and resource availability are known a priori, and are subject to little or no change at runtime. There is increasing demand, however, for adaptive capabilities in distributed real-time and embedded (DRE) systems that execute in open environments where system operational conditions, input workload, and resource availability cannot be characterized accurately a priori. A challenging problem faced by researchers and developers of such systems is devising effective adaptive resource management strategies that can meet end-to-end quality of service (QoS) requirements of applications. To address key resource management challenges of open DRE systems, this paper presents the Hierarchical Distributed Resource-management Architecture (HiDRA), which provides adaptive resource management using control techniques that adapt to workload fluctuations and resource availability for both bandwidth and processor utilization simultaneously. This paper presents three contributions to research in adaptive resource management for DRE systems. First, we describe the structure and functionality of HiDRA. Second, we present an analytical model of HiDRA that formalizes its control-theoretic behavior and presents analytical assurance of system performance. Third, we evaluate the performance of HiDRA via experiments on a representative DRE system that performs real-time distributed target tracking. Our analytical and empirical results indicate that HiDRA yields predictable, stable, and efficient system performance, even in the face of changing workload and resource availability.     

Correction: Real-time detection of deception attacks in cyber-physical systems

Detection of deception attacks is pivotal to ensure the safe and reliable operation of cyber-physical systems (CPS). Detection of such attacks needs to consider time-series sequences and is very challenging especially for autonomous vehicles that rely on high-dimensional observations from camera sensors. The paper presents an approach to detect deception attacks in real-time utilizing sensor observations, with a special focus on high-dimensional observations. The approach is based on inductive conformal anomaly detection (ICAD) and utilizes a novel generative model which consists of a variational autoencoder (VAE) and a recurrent neural network (RNN) that is used to learn both spatial and temporal features of the normal dynamic behavior of the system. The model can be used to predict the observations for multiple time steps, and the predictions are then compared with actual observations to efficiently quantify the nonconformity of a sequence under attack relative to the expected normal behavior, thereby enabling real-time detection of attacks using high-dimensional sequential data. We evaluate the approach empirically using two simulation case studies of an advanced emergency braking system and an autonomous car racing example, as well as a real-world secure water treatment dataset. The experiments show that the proposed method outperforms other detection methods, and in most experiments, both false positive and false negative rates are less than 10%. Furthermore, execution times measured on both powerful cloud machines and embedded devices are relatively short, thereby enabling real-time detection.

     

Safety and Reachability of Piecewise Linear Hybrid Dynamical Systems Based on Discrete Abstractions

In this paper, a novel methodology for analysis of piecewise linear hybrid systems based on discrete abstractions of the continuous dynamics is presented. An important characteristic of the approach is that the available control inputs are taken into consideration in order to simplify the continuous dynamics. Control specifications such as safety and reachability specifications are formulated in terms of partitions of the state space of the system. The approach provides a convenient general framework not only for analysis, but also for controller synthesis of hybrid systems. The research contributions of this paper impact the areas of analysis, verification, and synthesis of piecewise linear hybrid systems.     

A simulation as a service cloud middleware

Many seemingly simple questions that individual users face in their daily lives may actually require substantial number of computing resources to identify the right answers. For example, a user may want to determine the right thermostat settings for different rooms of a house based on a tolerance range such that the energy consumption and costs can be maximally reduced while still offering comfortable temperatures in the house. Such answers can be determined through simulations. However, some simulation models as in this example are stochastic, which require the execution of a large number of simulation tasks and aggregation of results to ascertain if the outcomes lie within specified confidence intervals. Some other simulation models, such as the study of traffic conditions using simulations may need multiple instances to be executed for a number of different parameters. Cloud computing has opened up new avenues for individuals and organizations with limited resources to obtain answers to problems that hitherto required expensive and computationally-intensive resources. This paper presents SIMaaS, which is a cloud-based Simulation-as-a-Service to address these challenges. We demonstrate how lightweight solutions using Linux containers (e.g., Docker) are better suited to support such services instead of heavyweight hypervisor-based solutions, which are shown to incur substantial overhead in provisioning virtual machines on-demand. Empirical results validating our claims are presented in the context of two case studies.     

DEUCON: Decentralized End-to-End Utilization Control for Distributed Real-Time Systems

Many real-time systems must control their CPU utilizations in order to meet end-to-end deadlines and prevent overload. Utilization control is particularly challenging in distributed real-time systems with highly unpredictable workloads and a large number of end-to-end tasks and processors. This paper presents the decentralized end-to-end utilization control (DEUCON) algorithm, which can dynamically enforce the desired utilizations on multiple processors in such systems. In contrast to centralized control schemes adopted in earlier works, DEUCON features a novel decentralized control structure that requires only localized coordination among neighbor processors. DEUCON is systematically designed based on advances in distributed model predictive control theory. Both control-theoretic analysis and simulations show that DEUCON can provide robust utilization guarantees and maintain global system stability despite severe variations in task execution times. Furthermore, DEUCON can effectively distribute the computation and communication cost to different processors and tolerate considerable communication delay between local controllers. Our results indicate that DEUCON can provide a scalable and robust utilization control for large-scale distributed real-time systems executing in unpredictable environments.     

Pressure support ventilation in adult respiratory distress syndrome: short-term effects of a servocontrolled mode

PURPOSE: To assess the short-term effects of pressure support ventilation in adult respiratory distress syndrome (ARDS), we studied 17 patients with moderate to severe ARDS using mandatory rate ventilation (MRV), a servocontrolled mode of PSV having respiratory rate as the targeted parameter. MATERIALS AND METHODS: Based on the duration of ARDS, the patients were divided into two groups: Group 1, early ARDS (duration up to 1 week), 10 patients; Group 2, intermediate ARDS (duration between 1 and 2 weeks). The patients were initially ventilated with assisted mechanical ventilation then with MRV, and finally with controlled mechanical ventilation. After a 20-minute period allowed for stabilization in each mode, ventilatory variables, gas exchange, hemodynamics, and patient's inspiratory effort were evaluated. RESULTS: During MRV blood gases, airway pressures and hemodynamic variables remained within acceptable limits in all patients. Compared with assisted mechanical ventilation, during MRV, patients of group 1 decreased their VT and V (from 0.64 +/- 0.04 to 0.42 +/- 0.03 L/sec) and increased their TI/TT (from 0.39 +/- 0.03 to 0.52 +/- 0.03). f did not change. PAO2 - PaO2 and QS/QT decreased (from 306 +/- 16 to 269 +/- 15 mm Hg, and from 20.2 +/- 1.4 to 17.5 +/- 1.1, respectively), while PaCO2 increased (from 44 +/- 3 to 50 +/- 3 mm Hg). On the contrary, patients of group 2 increased their VT (from 0.69 +/- 0.02 to 0.92 +/- 0.09 L), decreased their f (from 22.3 +/- 0.5 to 19.3 +/- 0.3 b/min), although they did not change their V and TI/TT. PAO2 - PaO2 and QS/QT remained stable. PaCO2 diminished (from 39 +/- 3 to 34 +/- 3 mm Hg). Pressure support level was higher in group 2 than in group 1 (29.4 +/- 3.0 v 19.8 +/- 2.9 cm H2O). CONCLUSIONS: We conclude that (1) PSV delivered by MRV may adequately ventilate patients with moderate to severe ARDS, preserving gas exchange and hemodynamics, at least for the short period tested; (2) early and intermediate ARDS respond in a different manner to MRV in terms of breathing pattern, gas exchange, and level of pressure assistance; and (3) patients with early ARDS are those who have an improvement in intrapulmonary oxygenation probably due, at least in part, to alveolar recruitment augmented by active diaphragmatic contraction.     

Data space randomization for securing cyber-physical systems

International Journal of Information Security - Non-control data attacks have become widely popular for circumventing authentication mechanisms in websites, servers, and personal computers. These...     

Modelling and analysis of the sugar cataract development process using stochastic hybrid systems

Modelling and analysis of biochemical systems such as sugar cataract development (SCD) are critical because they can provide new insights into systems, which cannot be easily tested with experiments; however, they are challenging problems due to the highly coupled chemical reactions that are involved. The authors present a stochastic hybrid system (SHS) framework for modelling biochemical systems and demonstrate the approach for the SCD process. A novel feature of the framework is that it allows modelling the effect of drug treatment on the system dynamics. The authors validate the three sugar cataract models by comparing trajectories computed by two simulation algorithms. Further, the authors present a probabilistic verification method for computing the probability of sugar cataract formation for different chemical concentrations using safety and reachability analysis methods for SHSs. The verification method employs dynamic programming based on a discretisation of the state space and therefore suffers from the curse of dimensionality. To analyse the SCD process, a parallel dynamic programming implementation that can handle large, realistic systems was developed. Although scalability is a limiting factor, this work demonstrates that the proposed method is feasible for realistic biochemical systems.     

Evaluation of an improved CFD model against nine vented deflagration experiments

In the present work, a newly developed CFD deflagration model incorporated into the ADREA-HF code is evaluated against hydrogen vented deflagrations experiments carried out by KIT and FM-Global in a medium (1 m³) and a real (63.7 m³) scale enclosure respectively. A square vent of 0.5 m² and 5.4 m² respectively is located in the center of one of side walls. In the case of the medium scale enclosure the 18% v/v homogeneous hydrogen-air mixture and back-wall ignition case is examined. In the case of the real scale enclosure the examined cases cover different homogeneous mixture concentrations (15% and 18% v/v), different ignition locations (back-wall and center) and different levels of initial turbulence. The CFD model accounts for flame instabilities that develop as the flame propagates inside the chamber and turbulence that mainly develops outside the vent. Pressure predictions are compared against experimental measurements revealing a very good performance of the CFD model for the back-wall ignition cases. For the center ignition cases, the model overestimates the maximum overpressure. The opening of the vent cover is identified as a possible reason for the overprediction. The analysis indicates that turbulence is the main factor which enhances external explosion strength causing the sudden pressure increase, confirming previous findings.     

The Corrosion Effects on the Structural Integrity of Reinforcing Steel

An experimental study conducted on 12 mm diameter, artificially corroded BSt500_s steel rebars, showed that the mass loss, the fatigue limit, and the life expectancy were reduced according to the level of corrosion. Rebar corrosion has a great impact on the mass loss, mechanical properties, low cycle fatigue (LCF) and there is strong indication that embrittlement takes place. The extended salt-spray exposure enhanced the damage and promoted extended creation of pits and perforations suggesting progressive embrittlement and reduction of the available energy, justified by the SEM micrograph results. The low cycle strain-controlled fatigue testing under ±1, ±2.5, and ±4% constant amplitude strain indicated that the corroded steel bars exhibit gradual reduction in available energy, number of cycles to failure, and load bearing ability. For the ±1% strain level the fatigue limit was reduced considerably as the level of corrosion increased due to mass loss and reduction of the exterior martensitic layer. In addition, a drastic drop in the energy density of the specimens was observed with creation of stress concentration points. At ±2.5% and ±4% strain levels, the fatigue limit was reduced dramatically mainly due to accumulated damage from plastic deformation and minimally due to corrosion. Anti-seismic design that ignores the influence of corrosion and cumulative damage due to plastic deformation, and the mechanical behavior of reinforcing steel during severe ground motion, could lead to unpredictable performance.