This paper studies a number of quantized feedback design problems for linear systems. We consider the case where quantizers are static (memoryless). The common aim of these design problems is to stabilize the given system or to achieve certain performance with the coarsest quantization density. Our main discovery is that the classical sector bound approach is nonconservative for studying these design problems. Consequently, we are able to convert many quantized feedback design problems to well-known robust control problems with sector bound uncertainties. In particular, we derive the coarsest quantization densities for stabilization for multiple-input-multiple-output systems in both state feedback and output feedback cases; and we also derive conditions for quantized feedback control for quadratic cost and H/sub /spl infin// performances.

The sector bound approach to quantized feedback control | NOVA. The University of Newcastle's Digital Repository

http://user.it.uu.se/~jarst116/slides/week4.pdf

Graph-Based Algorithms for Boolean Function Manipulation

Although awareness is constantly rising, that industrial computer networks (in a very broad sense) can be exposed to serious cyber threats, many people still think that the same countermeasures, developed to protect general-purpose computer networks, can be effectively adopted also in those situations where a physical system is managed/controlled through some distributed Information and Communication Technology (ICT) infrastructure. Unfortunately, this is not the case, as several examples of successful attacks carried out in the last decade, and more frequently in the very recent past, have dramatically shown. Experts in this area know very well that often the peculiarities of industrial networks prevent the adoption of classical approaches to their security and, in particular, of those popular solutions that are mainly based on a detect and patch philosophy. This paper is a contribution, from the security point of view, to the assessment of the current situation of a wide class of industrial distributed computing systems. In particular, the analysis presented in this paper takes into account the process of ensuring a satisfactory degree of security for a distributed industrial system, with respect to some key elements such as the system characteristics, the current state of the art of standardization and the adoption of suitable controls (countermeasures) that can help in lowering the security risks below a predefined, acceptable threshold.

Review of Security Issues in Industrial Networks

Web search engines use highly optimized compression schemes to decrease inverted index size and improve query throughput, and many index compression techniques have been studied in the literature. One approach taken by several recent studies first performs a renumbering of the document IDs in the collection that groups similar documents together, and then applies standard compression techniques. It is known that this can significantly improve index compression compared to a random document ordering. We study index compression and query processing techniques for such reordered indexes. Previous work has focused on determining the best possible ordering of documents. In contrast, we assume that such an ordering is already given, and focus on how to optimize compression methods and query processing for this case. We perform an extensive study of compression techniques for document IDs and present new optimizations of existing techniques which can achieve significant improvement in both compression and decompression performances. We also propose and evaluate techniques for compressing frequency values for this case. Finally, we study the effect of this approach on query processing performance. Our experiments show very significant improvements in index size and query processing speed on the TREC GOV2 collection of 25.2 million web pages.

/pdf/inverted-index-compression-and-query-processing-with-1xtqa8028s.pdf

Inverted index compression and query processing with optimized document ordering

Modeling and simulation techniques are today extensively used both in industry and science. Parts of larger systems are, however, typically modeled and simulated by different techniques, tools, and algorithms. In addition, experts from different disciplines use various modeling and simulation techniques. Both these facts make it difficult to study coupled heterogeneous systems.Co-simulation is an emerging enabling technique, where global simulation of a coupled system can be achieved by composing the simulations of its parts. Due to its potential and interdisciplinary nature, co-simulation is being studied in different disciplines but with limited sharing of findings.In this survey, we study and survey the state-of-the-art techniques for co-simulation, with the goal of enhancing future research and highlighting the main challenges.To study this broad topic, we start by focusing on discrete-event-based co-simulation, followed by continuous-time-based co-simulation. Finally, we explore the interactions between these two paradigms, in hybrid co-simulation.To survey the current techniques, tools, and research challenges, we systematically classify recently published research literature on co-simulation, and summarize it into a taxonomy. As a result, we identify the need for finding generic approaches for modular, stable, and accurate coupling of simulation units, as well as expressing the adaptations required to ensure that the coupling is correct.

/pdf/co-simulation-a-survey-158xsoh6d5.pdf

Co-Simulation: A Survey

We show how by combining Explicit Model Checking techniques and simulation it is possible to effectively carry out (bounded) System Level Formal Verification of large Hybrid Systems such as those defined using model-based tools like Simulink.

We use an explicit model checker (namely, CMurphi) to generate all possible (finite horizon) simulation scenarios and then optimise the simulation of such scenarios by exploiting the ability of simulators to save and restore visited states. We show feasibility of our approach by presenting experimental results on the verification of the fuel control system example in the Simulink distribution. To the best of our knowledge this is the first time that (exhaustive) verification has been carried out for hybrid systems of such a size.

/pdf/system-level-formal-verification-via-model-checking-driven-26lgbvnqyt.pdf

System Level Formal Verification via Model Checking Driven Simulation

The goal of System Level Formal Verification (SLFV) is to show system correctness notwithstanding uncontrollable events (such as: faults, variation in system parameters, external inputs, etc). Hardware In the Loop Simulation (HILS) based SLFV attains such a goal by considering exhaustively all relevant simulation scenarios. We present a distributed multi-core algorithm for HILS-based SLFV. Our experimental results on the Fuel Control System example in the Simulink distribution show that by using 64 machines with an 8 core processor each we can complete the SLFV activity in about 27 hours whereas a sequential approach would require more than 200 days. To the best of our knowledge this is the first time that a distributed multi-core algorithm for HILS-based SLFV is presented.

/pdf/system-level-formal-verification-via-distributed-multi-core-45cn49t64n.pdf

System Level Formal Verification via Distributed Multi-core Hardware in the Loop Simulation

The goal of System Level Formal Verification is to show system correctness notwithstanding uncontrollable events (disturbances), as for example faults, variation in system parameters, external inputs, etc. This may be achieved with an exhaustive Hardware In the Loop Simulation based approach, by considering all relevant scenarios in the System Under Verification (SUV) operational environment. In this paper, we present SyLVaaS, a Web-based tool enabling Verification as a Service (VaaS). SyLVaaS implements an assume-guarantee approach to the verification problem outlined above. SyLVaaS takes as input a high-level model defining the SUV operational environment and computes, using parallel algorithms deployed in a cluster infrastructure, a set of highly optimised simulation campaigns, which can be executed in an embarrassingly parallel fashion on a set of Simulink instances, using a platform independent Simulink driver downloadable from the SyLVaaS Web site. As the actual simulation is carried out at the user premises (e.g., in a private cluster), SyLVaaS allows full Intellectual Property protection on the SUV model and the user verification flow. The simulation campaigns computed by SyLVaaS randomise the verification order of operational scenarios and this enables, at anytime during the parallel simulation activity, the estimation of the completion time and the computation of an upper bound to the Omission Probability, i.e., the probability that there is a yet-to-be-simulated operational scenario which violates the property under verification. This information supports graceful degradation in the verification activity. We show effectiveness of the SyLVaaS algorithms and infrastructure by evaluating the system on industry-scale input related to the verification of the Fuel Control System (FCS) model in the Simulink distribution.

/pdf/sylvaas-system-level-formal-verification-as-a-service-4sg5yduirf.pdf

SyLVaaS: System Level Formal Verification as a Service*

Biological models typically depend on many parameters. Assigning suitable values to such parameters enables model individualisation. In our clinical setting, this means finding a model for a given patient. Parameter values cannot be assigned arbitrarily, since inter-dependency constraints among them are not modelled and ignoring such constraints leads to biologically meaningless model behaviours. Classical parameter identification or estimation techniques are typically not applicable due to scarcity of clinical measurements and the huge size of parameter space. Recently, we have proposed a statistical algorithm that finds (almost) all biologically meaningful parameter values. Unfortunately, such algorithm is computationally extremely intensive, taking up to months of sequential computation. In this paper we propose a parallel algorithm designed as to be effectively executed on an arbitrary large cluster of multi-core heterogenous machines.

Computing biological model parameters by parallel statistical model checking

We present a parallel random exhaustive Hardware In the Loop Simulation based model checker for hybrid systems that, by simulating all operational scenarios exactly once in a uniform random order, is able to provide, at any time during the verification process, an upper bound to the probability that the System Under Verification exhibits an error in a yet-to-be-simulated scenario (Omission Probability). We show effectiveness of the proposed approach by presenting experimental results on System Level Formal Verification of the Fuel Control System example in the Simulink distribution. To the best of our knowledge, no previously published model checker can exhaustively verify hybrid systems of such a size and provide at any time an upper bound to the Omission Probability.

/pdf/anytime-system-level-verification-via-random-exhaustive-wy3fy0sd1z.pdf

Federico Mari

Papers

System Level Formal Verification via Model Checking Driven Simulation

System Level Formal Verification via Distributed Multi-core Hardware in the Loop Simulation

SyLVaaS: System Level Formal Verification as a Service*

Computing biological model parameters by parallel statistical model checking

Anytime System Level Verification via Random Exhaustive Hardware in the Loop Simulation