Interactions among dynamic sets of objects

In this paper, we present an operator to model interactions among objects. Our proposal allows a variable number of participant objects in an interaction, and this number will be fixed during the execution of the model. This provides a very flexible interaction model based on synchronous interactions among several objects. Our interaction model is based on events and allows a multiple-way communication among objects. Concrete values of a communication are generated through constraints which are imposed locally on each participant object. The proposed interaction (and communication) model is very versatile and can be used as an abstract specification mechanism.     

Supervision of networked dynamical systems under coordination constraints

In this paper, we present a discrete-time predictive control strategy for the supervision of networked dynamic systems subject to coordination constraints. Such a network paradigm is characterized by a set of spatially distributed systems, possibly dynamically coupled and connected via communication links, which need to be controlled and coordinated in order to accomplish their overall objective. The network latency is modeled abstractly as a time-varying time-delay, which is allowed to become unbounded for taking into account data-loss. The method can be specialized to deal more efficiently either with random, possibly unbounded, time-delays, such as the case over the Internet, or constant/bounded time-delays, typically encountered in space and underwater applications. An example of coordination of two autonomous vehicles under input-saturation and formation accuracy constraints is presented.     

A characterization of illumination models and shading techniques

The interaction of light with material surfaces was studied in the fields of physics and optics long before the advent of computer graphics. The application of this knowledge to computer graphics is shaped by the dichotomy of attempting to solve the complex problem of generating realistic appearance within both the informational limits imposed by visible surface techniques and the computational constraints imposed by the computing hardware.Analyzing the evolution of illumination models in the context of this dichtomy presents a clearer understanding of the models that are currently in use and an insight into the directions of future development.     

A capacitated hub location problem under hose demand uncertainty

In this study, we consider a capacitated multiple allocation hub location problem with hose demand uncertainty. Since the routing cost is a function of demand and capacity constraints are imposed on hubs, demand uncertainty has an impact on both the total cost and the feasibility of the solutions. We present a mathematical formulation of the problem and devise two different Benders decomposition algorithms. We develop an algorithm to solve the dual subproblem using complementary slackness. In our computational experiments, we test the efficiency of our approaches and we analyze the effects of uncertainty. The results show that we obtain robust solutions with significant cost savings by incorporating uncertainty into our problem.     

Bayesian estimation via sequential Monte Carlo sampling—Constrained dynamic systems

Nonlinear and non-Gaussian processes with constraints are commonly encountered in dynamic estimation problems. Methods for solving such problems either ignore the constraints or rely on crude approximations of the model or probability distributions. Such approximations may reduce the accuracy of the estimates since they often fail to capture the variety of probability distributions encountered in constrained linear and nonlinear dynamic systems. This article describes a practical approach that overcomes these shortcomings via a novel extension of sequential Monte Carlo (SMC) sampling or particle filtering. Inequality constraints are imposed by accept/reject steps in the algorithm. The proposed approach provides samples representing the posterior distribution at each time point, and is shown to satisfy the same theoretical properties as unconstrained SMC. Illustrative examples show that results of the proposed approach are at least as accurate as moving horizon estimation, but computationally more efficient and in addition, the approach indicates the uncertainty associated with these estimates.     

Communication mechanisms in ecological network-based grid middleware for service emergence

Next generation grid systems are heading for globally collaborative, service-oriented and live information systems that exhibit a strong sense of automation. A collection of autonomous agents is searched, assembled, and coordinated in a grid middleware system to produce desirable grid services. An effective communication mechanism is vital to the effectiveness of the step to build a novel grid middleware system. In this study, we provide our grid middleware with a flexible communication solution to implement the complicated behaviors among different agents. We propose a transport mechanism of grid middleware, named as ecological network communication language (ENCL) and ecological network interaction protocol (ENIP) respectively from a low-level to a high-level implementation strategy of a communication mechanism. A series of experiments demonstrate that a service with some of the desired properties can emerge from interacting agents via the proposed solution.     

Event-Based Real-Time Monitoring

Real-time monitoring is required because of the uncertainty in the operating environment such as

(i) faulty hardware

(ii) the untrustworthiness of legacy and/or imported systems and

(iii) the violation of operational assumptions by the external environment, e.g., operator mistakes.

Different types of uncertainty may constrain the type of monitoring that can be performed. In this talk, we shall discuss the monitoring of non-functional properties such as timeliness and resource usage bounds, under the constraints imposed by the operating environment such as the uncertainty in the time of occurrence of events or the untrustworthiness of imported code.     

Robust quantization for digital finite communication bandwidth (DFCB) control

The problem of digital finite communication bandwidth (DFCB) control has come to the attention of the research community in connection with a growing interest in the development of distributed and/or networked control systems. In these systems, actuators, sensors, and other components are connected via data-rate constrained links such as wireless radio, etc. In this paper, we consider a scalar model of DFCB control that accommodates time-varying data-rate constraints, such as might occur with intermittent network congestion, and asynchronism of sampling and control actuation. Because of the possibly unpredictable fluctuation of the data-rate, we are interested in feedback control designs that will tolerate significantly constrained data-rates on feedback loops, while providing acceptable performance when such data-rate constraints are not in force. In light of a very basic notion of acceptable performance, we show that control designs with different number of quantization levels tolerate constrained data-rates differently. This leads to the conclusion that binary control represents the most robust control quantization under data-rate constraints imposed by time-varying congestion on the feedback communication channel. The advantage margin of binary control is further investigated numerically with and without the sampling-control asynchronism being considered. We show that the advantage margin is more substantial when the sampling-control asynchronism is significant. A design of quantized (binary) feedback with side channel information is proposed, and stability properties are discussed. We conclude the paper by examining performance limitations of our binary coding in the presence of noise.     

基于校园网络的元计算实验系统WADE的设计与实现

元计算系统是可以作为虚拟的整体而使用的地理上分散的异构计算资源，这些资源包括计算机、数据库和昂贵仪器等．元计算系统在硬件和软件方面均有异构性，适合具有不同内在并行性的复杂应用的执行．现存的绝大多数并行系统都是同构的，不具有这一优势，因此，研究异构环境下的元计算系统就很有现实意义．WADE是基于校园网络开发的元计算实验系统，使用MD支持异构数据格式转换，使用面向对象技术实现单一映像系统，使用优先约束的任务调度算法来实现应用程序的调度和运行，并提供与流行的并行编程软件如PVM等的接口。     

Task allocation for maximizing reliability of distributed systems: A simulated annealing approach

This paper addresses the problem of task allocation in heterogeneous distributed systems with the goal of maximizing the system reliability. It first develops an allocation model for reliability based on a cost function representing the unreliability caused by the execution of tasks on the system processors and the unreliability caused by the interprocessor communication time subject to constraints imposed by both the application and the system resources. It then presents a heuristic algorithm derived from the well-known simulated annealing (SA) technique to quickly solve the mentioned problem. The performance of the proposed algorithm is evaluated through experimental studies on a large number of randomly generated instances. Indeed, the quality of solutions are compared with those derived by using the branch-and-bound (BB) technique.     

Maximizing stochastic robustness of static resource allocations in a periodic sensor driven cluster

This research investigates the problem of robust static resource allocation for distributed computing systems operating under imposed Quality of Service (QoS) constraints. Often, such systems are expected to function in an environment where uncertainty in system parameters is common. In such an environment, the amount of processing required to complete a task may fluctuate substantially. Determining a resource allocation that accounts for this uncertainty—in a way that can provide a probability that a given level of QoS is achieved—is an important area of research. We have designed novel techniques for maximizing the probability that a given level of QoS is achieved. These techniques feature a unique application of both path relinking and local search within a Genetic Algorithm. In addition, we define a new methodology for finding resource allocations that are guaranteed to have a non-zero probability of addressing the timing constraints of the system. We demonstrate the use of this methodology within two unique steady-state genetic algorithms designed to maximize the robustness of resource allocations. The performance results for our techniques are presented for a simulated environment that models a heterogeneous cluster-based radar data processing center.     

Performance limitations for networked control systems with plant uncertainty

There has recently been significant interest in performance study for networked control systems with communication constraints. But the existing work mainly assumes that the plant has an exact model. The goal of this paper is to investigate the optimal tracking performance for networked control system in the presence of plant uncertainty. The plant under consideration is assumed to be non-minimum phase and unstable, while the two-parameter controller is employed and the integral square criterion is adopted to measure the tracking error. And we formulate the uncertainty by utilising stochastic embedding. The explicit expression of the tracking performance has been obtained. The results show that the network communication noise and the model uncertainty, as well as the unstable poles and non-minimum phase zeros, can worsen the tracking performance.     

Locating sensor nodes on construction projects

Localization of randomly distributed wireless sensor nodes is a significant and fundamental problem in a broad range of emerging civil engineering applications. Densely deployed in physical environments, they are envisioned to form ad hoc communication networks and provide sensed data without relying on a fixed communications infrastructure. To establish ad hoc communication networks among wireless sensor nodes, it is useful and sometimes necessary to determine sensors’ positions in static and dynamic sensor arrays. As well, the location of sensor nodes becomes of immediate use if construction resources, such as materials and components, are to be tracked. Tracking the location of construction resources enables effortless progress monitoring and supports real-time construction state sensing. This paper compares several models for localizing RFID nodes on construction job sites. They range from those based on triangulation with reference to transmission space maps, to roving RFID reader and tag systems using multiple proximity constraints, to approaches for processing uncertainty and imprecision in proximity measurements. They are compared qualitatively on the basis of cost, flexibility, scalability, computational complexity, ability to manage uncertainty and imprecision, and ability to handle dynamic sensor arrays. Results of field experiments and simulations are also presented where applicable.     

Stable,robust tracking by sliding mode control

Sliding mode control is examined from the perspective of obtaining stable and robust tracking of an arbitrary time-varying reference by a multi-input-output, linear, time-invariant system driven by a certain class of bounded errors, nonlinearities and disturbances. Most existing sliding mode schemes for such systems are subsumed by the one presented here. The results are developed via the use of inverse models, and make clear the constraints imposed by the finite and infinite zero structure of the system. In particular, stable and robust tracking is shown to be obtained by the scheme in this paper if and only if the system is minimum phase.     

Computing nearest neighbors in real time

The nearest-neighbor method can successfully be applied to correct possible errors induced into bit strings transmitted over noisy communication channels or to classify samples into a predefined set of categories. These two applications are investigated under real-time constraints, when the deadlines imposed can dramatically alter the quality of the solution unless a parallel model of computation (in these cases, a linear array of processors) is used. We also study a class of real-time computations, referred to as reactive real-time systems, that are particularly sensitive to the first time constraint imposed.     

Delta算子系统具有极点约束的鲁棒非脆弱方差控制

研究Delta算子描述的线性不确定系统具有圆形区域极点约束的鲁棒非脆弱方差控制问题. 针对系统参数范数有界不确定性和控制器的乘性增益不确定性, 运用线性矩阵不等式(LMI)方法, 提出具有圆形区域极点约束的状态反馈鲁棒非脆弱方差控制器存在的条件和设计方法. 数值算例表明设计方法的可行性.     

Probabilistic tubes in linear stochastic model predictive control

This paper considers constrained control of linear systems with additive and multiplicative stochastic uncertainty and linear input/state constraints. Both hard and soft constraints are considered, and bounds are imposed on the probability of soft constraint violation. Assuming the plant parameters to be finitely supported, a method of constraint handling is proposed in which a sequence of tubes, corresponding to a sequence of confidence levels on the predicted future plant state, is constructed online around nominal state trajectories. A set of linear constraints is derived by imposing bounds on the probability of constraint violation at each point on an infinite prediction horizon through constraints on one-step-ahead predictions. A guarantee of the recursive feasibility of the online optimization ensures that the closed loop system trajectories satisfy both the hard and probabilistic soft constraints. The approach is illustrated by a numerical example.     

Causal delivery protocols in real-time systems: A generic model

The objective of this paper is to introduce a model for causal delivery protocols in real-time systems. We start by showing that temporal order properties of real-time protocols are independent of whether they are timer-driven or clock-driven, being instead related to their degree of synchronism, that we call steadiness. Then, we derive a set of correctness conditions for such protocols to secure causal delivery order. To achieve this objective, we use an extension of Lamport's model of time-stamp based order. We show that both timer- and clock-driven protocols have order correctness limits dictated by the environment and the target applications, and define those limits, through a set of working formulas. We show that in extremely adverse cases, timer-driven protocols will perform as well as clock-driven ones, due to the restrictions imposed on the operation of the latter, which is perhaps surprising. These results open the door to exploring new forms of communication in time-critical systems, for example, supporting clock-and time-driven communication, and event-and time-triggered operation. We expect that the results of this paper will give insight to that problem, and will be useful in real-life systems, such as distributed computer control.     

Stochastic robustness metric and its use for static resource allocations

This research investigates the problem of robust static resource allocation for distributed computing systems operating under imposed Quality of Service (QoS) constraints. Often, such systems are expected to function in a physical environment replete with uncertainty, which causes the amount of processing required to fluctuate substantially over time. Determining a resource allocation that accounts for this uncertainty in a way that can provide a probabilistic guarantee that a given level of QoS is achieved is an important research problem. The stochastic robustness metric proposed in this research is based on a mathematical model where the relationship between uncertainty in system parameters and its impact on system performance are described stochastically.The utility of the established metric is then exploited in the design of optimization techniques based on greedy and iterative approaches that address the problem of resource allocation in a large class of distributed systems operating on periodically updated data sets. The performance results are presented for a simulated environment that replicates a heterogeneous cluster-based radar data processing center. A mathematical performance lower bound is presented for comparison analysis of the heuristic results. The lower bound is derived based on a relaxation of the Integer Linear Programming formulation for a given resource allocation problem.