Nash-based robust distributed model predictive control for large-scale systems

In this paper, a new robust distributed model predictive control (RDMPC) is proposed for large-scale systems with polytopic uncertainties. The time-varying system is first decomposed into several interconnected subsystems. Interactions between subsystems are obtained by a distributed Kalman filter, in which unknown parameters of the system are estimated using local measurements and measurements of neighboring subsystems that are available via a network. Quadratic boundedness is used to guarantee the stability of the closed-loop system. In the MPC algorithm, an output feedback-interaction feedforward control input is computed by an LMI-based optimization problem that minimizes an upper bound on the worst case value of an infinite-horizon objective function. Then, an iterative Nash-based algorithm is presented to achieve the overall optimal solution of the whole system in partially distributed fashion. Finally, the proposed distributed MPC approach is applied to a load frequency control (LFC) problem of a multi-area power network to study the efficiency and applicability of the algorithm in comparison with the centralized, distributed and decentralized MPC schemes.     

A macroeconomic model for resource allocation in large-scale distributed systems

In this paper we discuss an economic model for resource sharing in large-scale distributed systems. The model captures traditional concepts such as consumer satisfaction and provider revenues and enables us to analyze the effect of different pricing strategies upon measures of performance important for the consumers and the providers. We show that given a particular set of model parameters the satisfaction reaches an optimum; this value represents the perfect balance between the utility and the price paid for resources. Our results confirm that brokers play a very important role and can influence positively the market. We also show that consumer satisfaction does not track the consumer utility; these two important performance measures for consumers behave differently under different pricing strategies. Pricing strategies also affect the revenues obtained by providers, as well as, the ability to satisfy a larger population of users.     

Towards to dynamic optimal control for large-scale distributed systems

There is a class of complex, large-scale systems that are composed of many interacted and spatially distributed subsystems such as the power grids, transportation systems, and large scale chemical processes. With the progress of industrial technology, field bus, integrated circuit technologies and network communication technology, this automation system has taken a totally new configuration in which each subsystem owns only one hardware controller for controlling the subsystem itself, and all hardware controllers are connected by networks for exchanging information with each other or with upper layer controllers. In this distributed (or decentralized) framework, the distributed control algorithms are usually adopted because the classical centralized control solutions are often impractical due to their heavy computational demands and the lack of fault tolerance....     

An integrated admission control scheme for the delivery of streaming media

Quality of service (QoS) assurance is a major concern in media-on-demand (MoD) systems. Admission control is one of the most important issues that need to be addressed for QoS assurance. Also, smoothing is a basic technique for the media server to improve its bandwidth and buffer utilization. However, existing approaches cannot achieve the best resource utilization because (1) they cannot fully utilize the time-varying buffer spaces available at both server and client sides due to the separation of admission control and smoothing processes, and (2) the computing time is unacceptable for media of long duration. In this paper, we formulate the admission control as an integer programming problem and propose several heuristic methods for solving the problem. Specially, we introduce an efficient scheme, called batched admission (BA) scheme, which integrates admission control, transmission rate smoothing, and batching, to achieve best resource utilization with guaranteed QoS. Experimental studies show that the BA scheme outperforms existing approaches.     

Data-driven model reduction-based nonlinear MPC for large-scale distributed parameter systems

Model predictive control (MPC) has been effectively applied in process industries since the 1990s. Models in the form of closed equation sets are normally needed for MPC, but it is often difficult to obtain such formulations for large nonlinear systems. To extend nonlinear MPC (NMPC) application to nonlinear distributed parameter systems (DPS) with unknown dynamics, a data-driven model reduction-based approach is followed. The proper orthogonal decomposition (POD) method is first applied off-line to compute a set of basis functions. Then a series of artificial neural networks (ANNs) are trained to effectively compute POD time coefficients. NMPC, using sequential quadratic programming is then applied. The novelty of our methodology lies in the application of POD's highly efficient linear decomposition for the consequent conversion of any distributed multi-dimensional space-state model to a reduced 1-dimensional model, dependent only on time, which can be handled effectively as a black-box through ANNs. Hence we construct a paradigm, which allows the application of NMPC to complex nonlinear high-dimensional systems, even input/output systems, handled by black-box solvers, with significant computational efficiency. This paradigm combines elements of gain scheduling, NMPC, model reduction and ANN for effective control of nonlinear DPS. The stabilization/destabilization of a tubular reactor with recycle is used as an illustrative example to demonstrate the efficiency of our methodology. Case studies with inequality constraints are also presented.     

Enhancing topological information of the Lyapunov-based distributed model predictive control design for large-scale nonlinear systems

In this paper, a distributed model predictive control architecture based on graph theory for integrated large-scale nonlinear process systems is proposed. This architecture is first agglomerated using popular community detection techniques and then organized on account of the relative master–slave relationship according to the ample information of interactions among separate subsystems. Both sequential and iterative distributed nonlinear model predictive coordination forms are considered for the reduction of the communication and computational burden within an acceptable loss of performance. Furthermore, the control performance of the large-scale integrated system could be improved to some extent under the architecture and the communication strategy we propose, whereby a brave exploration is made on the relationship between the control structure and the control performance, ulteriorly obtaining some notable results towards the untapped territory. The effectiveness of the proposed coordination method is evaluated by a standard reactor-separator process system.     

Cost-based admission control for Internet Commerce QoS enhancement

In many e-commerce systems, preserving Quality of Service (QoS) is crucial to keep a competitive edge. Poor QoS translates into poor system resource utilisation, customer dissatisfaction and profit loss. In this paper, a cost-based admission control (CBAC) approach is described which is a novel approach to preserve QoS in Internet Commerce systems. CBAC is a dynamic mechanism which uses a congestion control technique to maintain QoS while the system is online. Rather than rejecting customer requests in a high-load situation, a discount-charge model which is sensitive to system current load and navigational structure is used to encourage customers to postpone their requests. A scheduling mechanism with load forecasting is used to schedule user requests in more lightly loaded time periods. Experimental results showed that the use of CBAC at high load achieves higher profit, better utilisation of system resources and service times competitive with those which are achievable during lightly loaded periods. Throughput is sustained at reasonable levels and request failure at high load is dramatically reduced.     

QoS customization in distributed object systems

Applications built on networked collections of computers are increasingly using distributed object platforms such as CORBA,Java Remote Method Invocation (RMI), and DCOM to standardize object interactions. With this increased use comes the increased need for enhanced quality of service (QoS) attributes related to fault tolerance, security, and timeliness. This paper describes an architecture called CQoS (configurable QoS) for implementing such enhancements in a transparent, highly customizable, and portable manner. CQoS consists of two parts: application‐ and platform‐dependent interceptors and generic QoS components. The generic QoS components are implemented using Cactus, a system for building highly configurable protocols and services in distributed systems. The CQoS architecture and the interfaces between the different components are described, together with implementations of QoS attributes using Cactus and interceptors for CORBA and Java RMI. Experimental results are given for a test application executing on a Linux cluster using Cactus/J, the Java implementation of Cactus. Compared with other approaches, CQoS emphasizes portability across different distributed object platforms, while the use of Cactus allows custom combinations of fault‐tolerance, security, and timeliness attributes to be realized on a per‐object basis in a straightforward way. Copyright © 2003 John Wiley & Sons, Ltd.     

可靠的分布式系统生存性保障模型

基于检查点的协同式回滚恢复机制是一种针对分布式系统生存性保障的有效机制,现有分布式系统中基于检查点的回滚恢复机制以分布式信道可靠作为假设前提,而实际应用场景中,该假设并不总是成立。针对分布式系统实际的应用环境,提出了适用于信道不可靠的分布式计算环境的协同式系统生存性保障模型。该模型在保留检查点回滚恢复机制优点的基础上,通过建立冗余通信链路和进程迁移来保障不可靠通信信道环境下分布式系统的生存性。     

Independent recovery in large-scale distributed systems

In large systems, replication can become important means to improve data access times and availability. Existing recovery protocols, on the other hand, were proposed for small-scale distributed systems. Such protocols typically update stale, newly-recovered sites with replicated data and resolve the commit uncertainty of recovering sites. Thus, given that in large systems failures are more frequent and that data access times are costlier, such protocols can potentially introduce large overheads in large systems and must be avoided, if possible. We call these protocols dependent recovery protocols since they require a recovering site to consult with other sites. Independent recovery has been studied in the context of one-copy systems and has been proven unattainable. This paper offers independent recovery protocols for large-scale systems with replicated data. It shows how the protocols can be incorporated into several well-known replication protocols and proves that these protocols continue to ensure data consistency. The paper then addresses the issue of nonblocking atomic commitment. It presents mechanisms which can reduce the overhead of termination protocols and the probability of blocking. Finally, the performance impact of the proposed recovery protocols is studied through the use of simulation and analytical studies. The results of these studies show that the significant benefits of independent recovery can be enjoyed with a very small loss in data availability and a very small increase in the number of transaction abortions     

A synthesizing control model of networked control systems to guarantee QoP and QoS

The whole performance of the networked control system （NCSs） depends on two interaction factors, namely the quality of control performance （QoP） and quality of network service （QoS）. So, to optimize the whole perfor-mance of NCSs, the problem of guaranteeing QoP and QoS plays an important role in the design of NCSs. However, up to now, little work has been done in this field. In this paper, a synthesizing control model of NCSs to guarantee QoP and QoS is proposed, and a feasible condition of optimizing whole performance of NCSs is also suggested. Finally, the simulation results show that the proposed model is effective.     

Dynamic end-to-end QoS management middleware for distributed multimedia systems

In this paper, we present a separable, reusable middleware solution that provides coordinated, end-to-end QoS management over any type of service component, and can use existing (legacy) QoS management solutions (by using wrappers) in a distributed multimedia system. Our middleware solution incorporates strategic and tactical QoS managers, and supports protocols and messages between tactical managers and managed application components, and between QoS managers in the management hierarchy. Strategic QoS managers take a global view of QoS provided by a set of application components within the manager's policy domain. Tactical QoS managers provide local control over application components. We introduce the concept of QoS policy domains to scope the authority of a strategic QoS manager. We describe how the management hierarchy is dynamically configured and reconfigured based on runtime needs of the application.     

Risk modeling in distributed, large-scale systems

Risk is inherent in distributed, large-scale systems. The paper explores the challenges of risk modeling in such systems, and suggests a risk modeling approach that is responsive to the requirements of complex, distributed, large-scale systems. An example of the use of the approach in the marine transportation system is given. The paper concludes with a discussion of limitations of the approach and of future work     

A distributed channel assignment control for QoS support in mobile ad hoc networks

Recently, one of the most critical issues in mobile ad hoc networks (MANETs) is providing quality of service (QoS) through routing, access/admission control, resource reservation, and mobility management. However, most existing solutions do not provide QoS effectively due to the interference arising from mobility. In this paper, we refer to interference as a quasi-exposed node problem. To solve this problem, a new algorithm, named a distributed channel assignment control, is proposed that focuses on performance enhancements related to QoS and mathematical analysis techniques for the channel bandwidth. This novel algorithm uses channel assignment control with a power control to reduce the negative effects induced by the quasi-exposed node problem, and then the channels are adaptively negotiated to allow communication in the interference region. The proposed algorithm has been evaluated via extensive simulations, and the results show that it can successfully guarantee QoS by maintaining good throughput, reducing control message overhead, and enhancing delay.     

A heuristic algorithm for distributed control in manufacturing systems

Distributed Problem Solving Networks (DPSN) provide a means for interconnecting intelligent problem solver nodes that can solve only a part of a problem depending on their ability in the problem domain. The decomposition of a problem into subproblems, and the selection of nodes to solve them can be regarded as the generation of an AND/OR tree, and the solution of the problem as a search for a solution tree. Introducing measurements for the cost of a solution tree, we present an algorithm to find one having minimal cost under certain conditions. A Flexible Manufacturing System consisting of a network of flexible workcells is used as an example.     

Ad Hoc网络中基于QoS的分布式接纳控制算法

随着人们对Ad Hoc网络研究的深入,服务质量（QoS）已经成为了当前的研究热点之一。为了在Ad Hoc这种特殊的网络中提供对QoS的支持,必须设计一种针对流的高效的接纳控制算法。通过分析无线信道的特点,解决了实现接纳控制必须解决的关键问题,并在此基础上提出了一种基于QoS的分布式接纳控制算法。仿真实验证明,将此接纳控制算法应用到传统的路由协议（比如AODV）中,性能将会大大提高,并且更适合于实时业务的传输。     

A software architecture for distributed computer control systems

Distributed computer control systems have a number of potential advantages over centralized systems, especially where the application is itself physically distributed. A computer station can be placed close to the plant being controlled, and a communications network used to enable the stations to communicate to coordinate their actions. However, the software must be carefully designed to exploit the potential advantages of distribution. This paper describes the software architecture of CONIC, a system to support distributed computer control applications. This architecture emphasizes the distinction between the writing of individual software components and the construction and configuration of a system from a set of components. A modular structure is used to separate programming from configuration. Typed entry and exit ports are used to clearly define module interfaces. Ports, analagous to the plugs and sockets of hardware components, permit modules to be interconnected in different ways. On-line modification and extension of the system is supported by permitting the dynamic creation and interconnection of modules. Message passing primitives are provided to permit modules to coordinate and synchronize control actions.     

An admission control scheme for end-to-end statistical QoS provision in IP networks

This paper presents a distributed and scalable admission control scheme to provide end-to-end statistical QoS guarantees in IP network.The basic idea of the scheme is that the ingress routers make admission control decisions according to the network status information obtained by sending probing packets along the selected routing path.Each router passively monitors the arriving traffic and marks the probing packets with its network status.The performance of the presented scheme is evaluated with a variety of traffic models,QoS metrics and network topologies,The simulation results show that the proposed scheme can accurately control the admissible region and effectively improve the utilization of network resource.