Robust chaotic key stream generator for real-time images encryption

In this paper, we propose a robust and compact design architecture of hardware chaotic key generator for real-time images encryption. The new proposed approach combines the perturbation technique with a non-linear switching between multiple three-dimensional continuous chaotic systems. The originality of this new scheme is that it allows a low-cost image encryption for embedded systems while still providing a good trade-off between performance and hardware resources. This pipelined architecture is particularly attractive since it provides a high security. Numerical simulations and real-time experimental results using Xilinx FPGA Virtex technology have demonstrated the feasibility and the efficiency of our secure solution and can be applied to many secure real-time embedded applications in System on Chip (SoC). Thorough experimental tests are carried out with detailed analysis, demonstrating the high security and fast encryption speed of the new scheme while still able to resist statistical and key analysis attacks.     

A cloud middleware for assuring performance and high availability of soft real-time applications

Applications are increasingly being deployed in the cloud due to benefits stemming from economy of scale, scalability, flexibility and utility-based pricing model. Although most cloud-based applications have hitherto been enterprise-style, there is an emerging need for hosting real-time streaming applications in the cloud that demand both high availability and low latency. Contemporary cloud computing research has seldom focused on solutions that provide both high availability and real-time assurance to these applications in a way that also optimizes resource consumption in data centers, which is a key consideration for cloud providers. This paper makes three contributions to address this dual challenge. First, it describes an architecture for a fault-tolerant framework that can be used to automatically deploy replicas of virtual machines in data centers in a way that optimizes resources while assuring availability and responsiveness. Second, it describes the design of a pluggable framework within the fault-tolerant architecture that enables plugging in different placement algorithms for VM replica deployment. Third, it illustrates the design of a framework for real-time dissemination of resource utilization information using a real-time publish/subscribe framework, which is required by the replica selection and placement framework. Experimental results using a case study that involves a specific replica placement algorithm are presented to evaluate the effectiveness of our architecture.     

Complexity-aware algorithm architecture for real-time enhancement of local anomalies in hyperspectral images

Anomaly detection (AD) from remotely sensed multi-hyperspectral images is a powerful tool in many applications, such as strategic surveillance and search and rescue operations. In a typical operational scenario, an airborne hyperspectral sensor searches a wide area to identify regions that may contain potential targets. These regions typically cue higher spatial-resolution sensors to provide target recognition and identification. While this procedure is mostly automated, an on-board operator is generally assigned to examine in real time the AD output and select the regions of interest to be sent for cueing. Real-time enhancement of local anomalies in images of the over flown scene can be presented to the operator to facilitate the decision-making process. Within this framework, one of the ultimate research interests is undoubtedly the design of complexity-aware AD algorithm architectures capable of assuring real-time or nearly real-time in-flight processing and prompt decision making. Among the different AD algorithms developed, this work focuses on those AD algorithms aimed at detecting small rare objects that are anomalous with respect to their local background. One of such algorithms, called RX algorithm, is based on a local Gaussian assumption for background and locally estimates its parameters from each pixel local neighborhood. RX has been recognized to be the benchmark AD algorithm for detecting local anomalies in multi-hyperspectral images. RX decision rule has been employed to develop computationally efficient algorithms tested in real-time operating systems. These algorithms rely upon a recursive block-based parameter estimation procedure that makes their processing and, in turn, their detection performance differ from those of original RX. In this paper, a complexity-aware algorithm architecture fully adaptable to real-time processing is presented that allows the computational load to be reduced with respect to original RX, while strictly following its original formulation and thus assuring the same detection performance. An experimental study is presented that analyzes in detail the complexity reduction, in terms of number of elementary operations, offered by the proposed architecture with respect to original RX. A real hyperspectral image of a scene with deployed targets has been employed to perform a case-study analysis of the complexity reduction to be experienced in different operational scenarios. The real data are also adopted to illustrate a possible strategy for on-board line-by-line enhanced visualization of anomalies for decision support.     

An Architecture for Planning in Embedded Systems

This work is focused on an architecture for systems which act inside an unpredictable world (embedded systems). Several systems dealing with the above issue have been proposed so far. We classify them by means of their architectures and algorithms, obtaining, for example, classical, deferred and reactive planning. From the systems developed up to now, we can point out some of the features that embedded systems must have. Namely, each system must have a flexible architecture, so it can deal with different problems. Each system must allow different basic activities, i.e., actuators and sensors controlling, plan formation and execution, and so on. Each system must have a flexible failure handling mechanism , since no action is guaranteed to succeed. In this paper, we propose a system called MRG which addresses the above features. Its architecture has several modules which can be combined in different ways depending on the problem. A module performs a basic activity. The system is able to detect and to react to failures. The architecture allows MRG a parallel activation of modules and a quick reaction to external events. The control of the architecture is reached by means of a planning language which has a small set of powerful control structures. MRG has been experimented in a complex large-scale application.     

具有高效缓冲策略的运动估计阵列处理器结构

基于改进的线性处理器阵列,提出了一种用于全搜索运动估计的阵列处理器结构,它可以并行执行运算而只要求串行的数据输入.分析表明这种结构不仅执行效率高,而且内部缓冲区很小.由于其简单的结构和规则的数据流,它可以方便地在FPGA器件中实现,用作实时编码器的协处理器.     

一种内嵌软件传感器的双软总线体系结构研究

航空软件的逻辑结构和系统规模日趋庞大,软件可靠性保障已成为新一代航空电子综合化领域的研究热点;针对实时软件的状态监控与故障诊断问题,提出了一种基于构件技术的双软总线风格体系结构,采用面向对象方法予以建模,构建该体系结构的静态框架和动态行为,并探讨了软件传感器采集监控对象实时状态的详细设计;以某惯导系统软件为例,对双总线体系结构进行扩展和应用,实例说明了该体系结构有助于使可靠性保障软件的框架定义更加清晰,易于实现。     

A two-layer architecture for economically optimal process control and operation

A two-layer architecture for dynamic real-time optimization (or nonlinear modelpredictive control (NMPC) with an economic objective) is presented, where the solution of the dynamic optimization problem is computed on two time-scales. On the upper layer, a rigorous optimization problem is solved with an economic objective function at a slow time-scale, which captures slow trends in process uncertainties. On the lower layer, a fast neighboring-extremal controller is tracking the trajectory in order to deal with fast disturbances acting on the process. Compared to a single-layer architecture, the two-layer architecture is able to address control systems with complex models leading to high computational load, since the rigorous optimization problem can be solved at a slower rate than the process sampling time. Furthermore, solving a new rigorous optimization problem is not necessary at each sampling time if the process has rather slow dynamics compared to the disturbance dynamics. The two-layer control strategy is illustrated with a simulated case study of an industrial polymerization process.     

Autonomous and adaptive procedure for cumulative failure prediction

An autonomous adaptive reliability prediction model using evolutionary connectionist approach based on Recurrent Radial Basis Function architecture is proposed. Based on the currently available failure time data, Fuzzy Min–Max algorithm is used to globally optimize the number of the k Gaussian nodes. This technique allows determining and initializing the k-centers of the neural network architecture in an iterative way. The user does not have to define arbitrary some parameters. The optimized neural network architecture is then iteratively and dynamically reconfigured as new failure occurs. The performance of the proposed approach has been tested using sixteen real-time software failure data.     

GUARDS: a generic upgradable architecture for real-time dependablesystems

The development and validation of fault-tolerant computers for critical real-time applications are currently both costly and time consuming. Often, the underlying technology is out-of-date by the time the computers are ready for deployment. Obsolescence can become a chronic problem when the systems in which they are embedded have lifetimes of several decades. This paper gives an overview of the work carried out in a project that is tackling the issues of cost and rapid obsolescence by defining a generic fault-tolerant computer architecture based essentially on commercial off-the-shelf (COTS) components (both processor hardware boards and real-time operating systems). The architecture uses a limited number of specific, but generic, hardware and software components to implement an architecture that can be configured along three dimensions: redundant channels, redundant lanes, and integrity levels. The two dimensions of physical redundancy allow the definition of a wide variety of instances with different fault tolerance strategies. The integrity level dimension allows application components of different levels of criticality to coexist in the same instance. The paper describes the main concepts of the architecture, the supporting environments for development and validation, and the prototypes currently being implemented     

Depth-limited search for real-time problem solving

We propose depth-limited heuristic search as a general paradigm for real-time problem solving in a dynamic environment. When combined with iterative-deepening, it provides the ability to commit to an action almost instantaneously, but allows the quality of that decision to improve as long as time is available. Once a deadline is reached, the best decision arrived at is executed. We illustrate the paradigm in three different settings, corresponding to single-agent search, two-player games, and multi-agent problem solving. First we review two-player minimax search with alpha-beta pruning. Minimax can be extended to themaxn algorithm for more than two players, which admits a much weaker form of alpha-beta pruning. Finally, we explore real-time search algorithms for single-agent problems. Minimax is specialized tominimin, which allows a very powerfulalpha pruning algorithm. In addition,real-time-A ^* allows backtracking while still guaranteeing a solution and making locally optimal decisions.This research was supported by an NSF Presidential Young Investigator Award, NSF Grant IRI-8801939, and and equipment grant from Hewlett-Packard. Thanks to Valerie Aylett for drawing the figures.     

A survey of timed automata for the development of real-time systems

Timed automata are a popular formalism to model real-time systems. They were introduced two decades ago to support formal verification. Since then they have also been used for other purposes and a large number of variants has been introduced to be able to deal with the many different kinds of requirements of real-time system development. This survey attempts to introduce a massive and complicated theoretical research area to a reader in an easy and compact manner. One objective of this paper is to inform a reader about the theoretical properties (or capabilities) of timed automata which are (or might be) useful for real-time model driven development. To achieve this goal, this paper presents a survey on semantics, decision problems, and variants of timed automata. The other objective of this paper is to inform a reader about the current state of the art of timed automata in practice. To achieve the second aim, this article presents a survey on timed automata’s implementability and tools.     

Automatic synthesis and verification of real-time embedded software for mobile and ubiquitous systems

Currently available application frameworks that target the automatic design of real-time embedded software are poor in integrating functional and non-functional requirements for mobile and ubiquitous systems. In this work, we present the internal architecture and design flow of a newly proposed framework called Verifiable Embedded Real-Time Application Framework (VERTAF), which integrates three techniques namely software component-based reuse, formal synthesis, and formal verification. Component reuse is based on a formal unified modeling language (UML) real-time embedded object model. Formal synthesis employs quasi-static and quasi-dynamic scheduling with multi-layer portable efficient code generation, which can output either real-time operating systems (RTOS)-specific application code or automatically generated real-time executive with application code. Formal verification integrates a model checker kernel from state graph manipulators (SGM), by adapting it for embedded software. The proposed architecture for VERTAF is component-based which allows plug-and-play for the scheduler and the verifier. The architecture is also easily extensible because reusable hardware and software design components can be added. Application examples developed using VERTAF demonstrate significantly reduced relative design effort as compared to design without VERTAF, which also shows how high-level reuse of software components combined with automatic synthesis and verification increases design productivity.     

Dai-depur architecture: Distributed agents for real-time wwtp supervision and control

One of the key problems in real-time control Artificial Intelligent systems design is the development of an architecture able to manage efficiently the different elements of the process. In the management of Waste Water Treatment Plants (WWTP), with a great interrelation between the different units, there is a problem in order to identify and solve the different specific situations. A Supervisory System recognizes predefined problems and uses a determined strategy in order to keep the process controlled. The main goal of the paper is to present a knowledge-based distributed architecture for real time supervision and control of WWTP that overcomes some of these troubles. It is discussed the development of the application and the methodology employed in it. The prototype's architecture being developed DAI-DEPUR is detailed together with some obtained results.     

An architecture for real-time distributed artificial intelligent systems

This paper introduces a new architecture for a real-time distributed artificial intelligence system: DENIS—a Dynamic Embedded Noticeboard Information System. The fundamental idea underlying the architecture draws heavily upon a distributed human system analogy, as seen, for example, in the workplace. The aim of DENIS is to provide a simple, meaningful means by which autonomous intelligent agents can cooperate and coordinate their actions in order to enhance the reliability and effectiveness of a real-time distributed control system. Based on a human paradigm, the architecture inherently allows for the control of an intelligent agent to be taken over by a human operator, yet still to maintain consistency in the distributed system. The key to the thinking in this new approach is to try to model how humans work together, and to implement this in a distributed architecture. One of the main issues raised is that humans owe much of their flexibility to their ability to reason, not only logically, but also in terms of time.     

Distributed control and speed sensorless for the synchronisation of multi-robot systems

This paper investigates a synchronization approach to trajectory tracking of networked robotic systems while maintaining time-varying formations. The objective is to control networked robots to track a desired trajectory while synchronizing their behaviors. Combining trajectory tracking and synchronization algorithms, the developed approach uses a cross-coupling technical to create interconnections for mutual synchronization of robots. The main objective of distributed approach is to generate an emerging behavior using only local information interactions. First, a distributed scheme is developed to achieve the networked robots synchronization on undirected graph. Then, the leaderless synchronized tracking problem in the case when only position measurements are available, will be presented. For both cases: In the presence of the velocity feedback or in its absence, the controller, designed by incorporating the cross-coupling technical into a sliding mode control architecture, successfully guarantees asymptotic convergence to zero of both position tracking and synchronization errors simultaneously. The Lyapunov-based approach has been used to establish the multi-robot systems asymptotic stability. A real-time software simulator is developed to visualize the synchronized behaviors. Based on LabVIEW integrated development environment (IDE), a developed human-machine-interface (HMI) allows its user to control, in real time, the networked robots. Simulation and experimental results are provided to demonstrate performances of the proposed control schemes.     

A JAVA application framework for scientific software development

This paper presents AIBench (SING group, Ourense, Spain), a JAVA desktop application framework mainly focused on scientific software development, with the goal of improving the productivity of research groups. Following the MVC design pattern, the programmer is able to develop applications using only three types of concepts: operations, data‐typesand views. The framework provides the rest of the functionality present in typical scientific applications, including user parameter requests, logging facilities, multithreading execution, experiment repeatability and graphic user interface generation, among others. The proposed framework is implemented following a plugin‐based architecture, which also allows assembling new applications by the reuse of modules from past development projects. Copyright © 2011 John Wiley & Sons, Ltd.     

A real-time profile for UML

This paper describes an approach for real-time modelling in UML, focusing on analysis and verification of time and scheduling-related properties. To this aim, a concrete UML profile, called the ωprofile, is defined, dedicated to real-time modelling by identifying a set of relevant concepts for real-time modelling which can be considered as a refinement of the standard SPT profile. The profile is based on a rich concept of event representing an instant of state change, and allows the expression of duration constraints between occurrences of events. These constraints can be provided in the form of OCL-like expressions annotating the specification or by means of state machines, stereotyped as ‘observers’. A framework for modelling scheduling issues is obtained by adding a notion of resource and a notion of execution time. For proving the relevance of these choices, the profile has been implemented in a validation tool and applied to case studies. It has a formal semantics and is sufficiently general and expressive to define a semantic underpinning for other real-time profiles of UML which in general define more restricted frameworks. In particular, most existing profiles handling real-time issues define a number of predefined attributes representing particular durations or constraints on them and their semantic interpretation can be expressed in the OMEGA-RT profile. This work has been partially supported by the IST-2002-33522 OMEGA project. VERIMAG is an academic research laboratory associated with CNRS, Université Joseph Fourier and Institut Nationale Polytechnique de Grenoble.     

基于滚动优化的密码云实时任务阈值调度方法

针对当前云任务调度算法在密码云环境中无法实现任务实时处理的问题,提出一种基于滚动优化窗口的实时阈值调度方法。首先,将密钥调用环节融入密码任务流程中,提出一种密码云服务架构;其次,为实现任务的实时调度,构建基于滚动窗口的密码任务调度器模型和吞吐量分析模型,用于获得实时的吞吐量数据;最后,为满足云租户对高速密码服务的客观需求,提出吞吐量阈值调度算法,从而根据实时吞吐量相对于吞吐量阈值的变化情况实时迁移虚拟密码机。仿真结果表明,该方法与未采用滚动优化窗口或虚拟机迁移技术的方法相比,具有任务完成时间短、CPU占用率低的特点,且实时吞吐量能够持续保持在网络带宽的70%~85%,从而验证了其在密码云环境中的有效性和实时性。     

Parallel 1D-FFT computation on constant-valence multicomputers

This paper addresses the problem of monodimensional (1D) FFT parallel computation on constant-valence multicomputers, i.e. on parallel systems made up of processing elements (PEs) which do not share memory and are connected to a bounded number of neighbours. After a qualitative analysis of several possible partitionings of the DIT FFT algorithm, a decomposition is introduced that has good scalability properties and makes it possible to use sections of sequential code based on the most common 1D-FFT algorithms. If a computing architecture with indirect binary n-cube interconnection network is used, the proposed decomposition guarantees strictly local communications and therefore requires no through-routing support. These characteristics have a positive impact on software development and also on overall performance. Furthermore, thanks to a pipelined organization of the PEs, the resulting architecture has high potentialities for real-time signal processing. As these useful features are obtained at the ‘expense’ of an uneven workload distribution, computing efficiency is relatively low but does not significantly change in a wide range of the number of processors. An implementation on a Transputer-based system is presented along with the performance results obtained. Finally a simple analytical model of the architecture is shown, that allows the values of the main performance parameters to be obtained as a function of the number of processors used and of the elementary response times of the first stage of PEs.     

Synthesis of nonlinear controller for wind turbines stability when providing grid support

This paper presents a new nonlinear polynomial controller for wind turbines that assures stability and maximizes the energy produced while imposing a bound in the generated power derivative in normal operation (guarantees a smooth operation against wind turbulence). The proposed controller structure also allows eventually producing a transient power increase to provide grid support, in response to a demand from a frequency controller. The controller design uses new optimization over polynomials techniques, leading to a tractable semidefinite programming problem. The ability of the wind turbine to increase its power under partial load operation has been analysed. The aforementioned optimization techniques have allowed quantifying the maximum transient overproduction that can be demanded to the wind turbine without violating minimum speed constraints (that could lead to unstable behaviour), as well as the total generated energy loss. The ability to evaluate this shortfall has permitted the development of an optimization procedure in which wind farm overproduction requirements are divided into individual turbines, assuring that the total energy loss in the wind farm is minimum, while complying with the maximum demanded power constraints. Copyright © 2013 John Wiley & Sons, Ltd.