How realistic is the mixed-criticality real-time system model?

23rd International Conference on Real-Time Networks and Systems (RTNS 2015). 4 to 6, Nov, 2015, Main Track. Lille, France. Best Paper Award NomineeWith the rapid evolution of commercial hardware platforms, in most application domains, the industry has shown a growing interest in integrating and running independently-developed applications of different “criticalities” in the same multicore platform. Such integrated systems are commonly referred to as mixed-criticality systems (MCS). Most of the MCS-related research published in the state-of-the-art cite the safety-related standards associated to each application domain (e.g. aeronautics, space, railway, automotive) to justify their methods and results. However, those standards are not, in most cases, freely available, and do not always clearly and explicitly specify the requirements for mixed-criticality systems. This paper addresses the important challenge of unveiling the relevant information available in some of the safety-related standards, such that the mixed-criticality concept is understood from an industrialist’s perspective. Moreover, the paper evaluates the state-of-the-art mixed-criticality real-time scheduling models and algorithms against the safety-related standards and clarifies some misconceptions that are commonly encountered

Utilization-Based Scheduling of Flexible Mixed-Criticality Real-Time Tasks

Mixed-criticality models are an emerging paradigm for the design of real-time systems because of their significantly improved resource efficiency. However, formal mixed-criticality models have traditionally been characterized by two impractical assumptions: once \textit{any} high-criticality task overruns, \textit{all} low-criticality tasks are suspended and \textit{all other} high-criticality tasks are assumed to exhibit high-criticality behaviors at the same time. In this paper, we propose a more realistic mixed-criticality model, called the flexible mixed-criticality (FMC) model, in which these two issues are addressed in a combined manner. In this new model, only the overrun task itself is assumed to exhibit high-criticality behavior, while other high-criticality tasks remain in the same mode as before. The guaranteed service levels of low-criticality tasks are gracefully degraded with the overruns of high-criticality tasks. We derive a utilization-based technique to analyze the schedulability of this new mixed-criticality model under EDF-VD scheduling. During runtime, the proposed test condition serves an important criterion for dynamic service level tuning, by means of which the maximum available execution budget for low-criticality tasks can be directly determined with minimal overhead while guaranteeing mixed-criticality schedulability. Experiments demonstrate the effectiveness of the FMC scheme compared with state-of-the-art techniques.Comment: This paper has been submitted to IEEE Transaction on Computers (TC) on Sept-09th-201

Critical behavior in an evolutionary Ultimatum Game

Experimental studies have shown the ubiquity of altruistic behavior in human societies. The social structure is a fundamental ingredient to understand the degree of altruism displayed by the members of a society, in contrast to individual-based features, like for example age or gender, which have been shown not to be relevant to determine the level of altruistic behavior. We explore an evolutionary model aiming to delve how altruistic behavior is affected by social structure. We investigate the dynamics of interacting individuals playing the Ultimatum Game with their neighbors given by a social network of interaction. We show that a population self-organizes in a critical state where the degree of altruism depends on the topology characterizing the social structure. In general, individuals offering large shares but in turn accepting large shares, are removed from the population. In heterogeneous social networks, individuals offering intermediate shares are strongly selected in contrast to random homogeneous networks where a broad range of offers, below a critical one, is similarly present in the population.Comment: 13 pages, 7 figure

Can biological quantum networks solve NP-hard problems?

There is a widespread view that the human brain is so complex that it cannot be efficiently simulated by universal Turing machines. During the last decades the question has therefore been raised whether we need to consider quantum effects to explain the imagined cognitive power of a conscious mind. This paper presents a personal view of several fields of philosophy and computational neurobiology in an attempt to suggest a realistic picture of how the brain might work as a basis for perception, consciousness and cognition. The purpose is to be able to identify and evaluate instances where quantum effects might play a significant role in cognitive processes. Not surprisingly, the conclusion is that quantum-enhanced cognition and intelligence are very unlikely to be found in biological brains. Quantum effects may certainly influence the functionality of various components and signalling pathways at the molecular level in the brain network, like ion ports, synapses, sensors, and enzymes. This might evidently influence the functionality of some nodes and perhaps even the overall intelligence of the brain network, but hardly give it any dramatically enhanced functionality. So, the conclusion is that biological quantum networks can only approximately solve small instances of NP-hard problems. On the other hand, artificial intelligence and machine learning implemented in complex dynamical systems based on genuine quantum networks can certainly be expected to show enhanced performance and quantum advantage compared with classical networks. Nevertheless, even quantum networks can only be expected to efficiently solve NP-hard problems approximately. In the end it is a question of precision - Nature is approximate.Comment: 38 page

Topology by dissipation

Topological states of fermionic matter can be induced by means of a suitably engineered dissipative dynamics. Dissipation then does not occur as a perturbation, but rather as the main resource for many-body dynamics, providing a targeted cooling into a topological phase starting from an arbitrary initial state. We explore the concept of topological order in this setting, developing and applying a general theoretical framework based on the system density matrix which replaces the wave function appropriate for the discussion of Hamiltonian ground-state physics. We identify key analogies and differences to the more conventional Hamiltonian scenario. Differences mainly arise from the fact that the properties of the spectrum and of the state of the system are not as tightly related as in a Hamiltonian context. We provide a symmetry-based topological classification of bulk steady states and identify the classes that are achievable by means of quasi-local dissipative processes driving into superfluid paired states. We also explore the fate of the bulk-edge correspondence in the dissipative setting, and demonstrate the emergence of Majorana edge modes. We illustrate our findings in one- and two-dimensional models that are experimentally realistic in the context of cold atoms.Comment: 61 pages, 8 figure

Cities: Continuity, transformation and emergence

Book synopsis: This book applies ideas and methods from the complexity perspective to key concerns in the social sciences, exploring co-evolutionary processes that have not yet been addressed in the technical or popular literature on complexity. \ud \ud Authorities in a variety of fields – including evolutionary economics, innovation and regeneration studies, urban modelling and history – re-evaluate their disciplines within this framework. The book explores the complex dynamic processes that give rise to socio-economic change over space and time, with reference to empirical cases including the emergence of knowledge-intensive industries and decline of mature regions, the operation of innovative networks and the evolution of localities and cities. Sustainability is a persistent theme and the practicability of intervention is examined in the light of these perspectives. \ud \ud Specialists in disciplines that include economics, evolutionary theory, innovation, industrial manufacturing, technology change, and archaeology will find much to interest them in this book. In addition, the strong interdisciplinary emphasis of the book will attract a non-specialist audience interested in keeping abreast of current theoretical and methodological approaches through evidence-based and practical examples

Effects of network topology, transmission delays, and refractoriness on the response of coupled excitable systems to a stochastic stimulus

We study the effects of network topology on the response of networks of coupled discrete excitable systems to an external stochastic stimulus. We extend recent results that characterize the response in terms of spectral properties of the adjacency matrix by allowing distributions in the transmission delays and in the number of refractory states, and by developing a nonperturbative approximation to the steady state network response. We confirm our theoretical results with numerical simulations. We find that the steady state response amplitude is inversely proportional to the duration of refractoriness, which reduces the maximum attainable dynamic range. We also find that transmission delays alter the time required to reach steady state. Importantly, neither delays nor refractoriness impact the general prediction that criticality and maximum dynamic range occur when the largest eigenvalue of the adjacency matrix is unity