Minimum time control of large‐scale boolean control networks with constraints

The minimum time control that steers a large‐scale Boolean control network with constraints from an initial state to a given state is investigated. This problem is studied under the partition of the large‐scale Boolean control networks. Based on that, the problem is converted to finding the minimum time control for each subnetwork. Hence, the minimum time control for small size Boolean control networks with constraints is considered firstly. Then, a method to solve the problem for large‐scale Boolean control networks with constraints is presented. Finally, a numerical example on T‐cell receptor kinetics is given to show the effectiveness of the main results.     

ExPregel: a new computational model for large‐scale graph processing

These days, large‐scale graph processing becomes more and more important. Pregel, inspired by Bulk Synchronous Parallel, is one of the highly used systems to process large‐scale graph problems. In Pregel, each vertex executes a function and waits for a superstep to communicate its data to other vertices. Superstep is a very time‐consuming operation, used by Pregel, to synchronize distributed computations in a cluster of computers. However, it may become a bottleneck when the number of communications increases in a graph with million vertices. Superstep works like a barrier in Pregel that increases the side effect of skew problem in distributed computing environment. ExPregel is a Pregel‐like model that is designed to reduce the number of communication messages between two vertices resided on two different computational nodes. We have proven that ExPregel reduces the number of exchanged messages as well as the number of supersteps for all graph topologies. Enhancing parallelism in our new computational model is another important feature that manifolds the speed of graph analysis programs. More interestingly, ExPregel uses the same model of programming as Pregel. Our experiments on large‐scale real‐world graphs show that ExPregel can reduce network traffic as well as number of supersteps from 45% to 96%. Runtime speed up in the proposed model varies from 1.2× to 30×. Copyright © 2015 John Wiley & Sons, Ltd.     

Reduction of the small gain condition for large‐scale interconnections

The small gain condition is sufficient for input‐to‐state stability (ISS) of interconnected systems. However, verification of the small gain condition requires large amount of computations in the case of a large size of the system. To facilitate this procedure, we aggregate the subsystems and the gains between the subsystems that belong to certain interconnection patterns (motifs) by using three heuristic rules. These rules are based on three motifs: sequentially connected nodes, nodes connected in parallel, and almost disconnected subgraphs. Aggregation of these motifs keeps the structure of the mutual influences between the subsystems in the network. Furthermore, fulfillment of the reduced small gain condition implies ISS of the large network. Thus, such reduction allows to decrease the number of computations needed to verify the small gain condition. Finally, an ISS‐Lyapunov function for the large network can be constructed using the reduced small gain condition. Applications of these rules is illustrated on an example. Copyright © 2013 John Wiley & Sons, Ltd.     

A heuristic approach for the allocation of resources in large‐scale computing infrastructures

An increasing number of enterprise applications are intensive in their consumption of IT but are infrequently used. Consequently, either organizations host an oversized IT infrastructure or they are incapable of realizing the benefits of new applications. A solution to the challenge is provided by the large‐scale computing infrastructures of clouds and grids, which allow resources to be shared. A major challenge is the development of mechanisms that allow efficient sharing of IT resources. Market mechanisms are promising, but there is a lack of research in scalable market mechanisms. We extend the multi‐attribute combinatorial exchange mechanism with greedy heuristics to address the scalability challenge. The evaluation shows a trade‐off between efficiency and scalability. There is no statistical evidence for an influence on the incentive properties of the market mechanism. This is an encouraging result as theory predicts heuristics to ruin the mechanism's incentive properties. Copyright © 2015 John Wiley & Sons, Ltd.     

Decentralized event‐triggered control of large‐scale nonlinear systems

This paper studies the decentralized event‐triggered control of large‐scale nonlinear systems. We consider a class of decentralized control systems that are transformable into an interconnection of input‐to‐state stable subsystems with the sampling errors as the inputs. The sampling events for each subsystem are triggered by a threshold signal, and the threshold signals for the subsystems are independent with each other for the decentralized implementation. By appropriately designing the event‐triggering mechanisms, it is shown that infinitely fast sampling can be avoided for each subsystem and asymptotic regulation is achievable for the large‐scale system. The proposed design is based on the ISS small‐gain arguments, and is validated by a benchmark example of controlling two coupled inverted pendulums.     

Finite‐time boundedness of large‐scale systems with actuator faults and gain fluctuations

This paper addresses the issue of finite‐time boundedness of large‐scale interconnected systems with the use of a distributed nonfragile fault‐tolerant controller. The objective of this paper is to design a state‐feedback controller consisting of a time‐varying delay such that the resulting closed‐loop system is finite‐time bounded under a prescribed extended passivity performance level even in the presence of all admissible uncertainties and possible actuator faults. More precisely, based on the Lyapunov‐Krasovskii stability theory, a new set of sufficient conditions is obtained in the framework of linear matrix inequality constraints that ensures finite‐time boundedness and satisfies the prescribed extended passivity performance index of the considered system. Finally, two numerical examples, including the interconnected inverted pendulum, are given to show the effectiveness of the proposed controller design technique.     

A viable system structure for large‐scale software systems

A homogeneous system structure is proposed that enhances modularity and flexibility, and facilitates (further) development of large‐scale software systems in a major‐industry environment. In our opinion, it is an effective means of countering the inherent increase in software entropy when (further) developing existing large‐scale software systems, thereby substantially cutting down production costs. It can be applied generally both to new and existing systems, whether application programs or operating systems, promotes the parallel use of different programming paradigms and various implementation languages, and offers the option of either redesigning parts or introducing additional parts in stages based on a more modern technology. The proposed system structure is compared and contrasted with other architectures such as CORBA, and it is shown that it may be regarded as an embellishment of the CORBA architecture for the internal structuring or restructuring of possibly distributed software systems. So far it has been used in four releases of the BS2000/OSD operating system with very positive results. Dependencies between various entities – which we call ‘subsystems’ – in the course of the (further) development process, as well as during dynamic execution are minimized and well‐regulated. The subsystems may be loaded on demand during the session by a system authority. Every interface in the system is classified according to its permitted scope of use. For interfaces between subsystems, a uniform and standardized technique is introduced which uses the same format for all implementation languages at both the source‐ and binary‐code level. This technique exceeds the regulations in other architectures but actually achieves considerable rationalization. Copyright © 1999 John Wiley & Sons, Ltd.     

Decentralized weighted control for a class of large‐scale systems with multi‐modes

In this paper, the control synthesis problem for a class of large‐scale systems with multi‐modes that are called large‐scale switched systems is addressed. By introducing the concept of decentralized switching signal and the relevant decentralized average dwell time, the asymptotic stability and weighted ?₂ gain performance are investigated. It should be noted that the decentralized switching covers general switching cases for large‐scale switched systems, namely, it admits both time‐dependent switching signal and arbitrary switching signal blended in the decentralized switching. Then, on the basis of the analysis results, the decentralized weighted control scheme including state feedback controller gains and switching signals is studied. Several design algorithms are proposed to meet different controller design problems. Finally, numerical examples are provided to illustrate theoretical findings within this paper. Copyright © 2013 John Wiley & Sons, Ltd.     

Adaptive fuzzy output feedback decentralized control of pure‐feedback nonlinear large‐scale systems

In this paper, an adaptive fuzzy decentralized output feedback control approach is presented for a class of uncertain nonlinear pure‐feedback large‐scale systems with immeasurable states. Fuzzy logic systems are utilized to approximate the unknown nonlinear functions, and a fuzzy state observer is designed to estimate the immeasurable states. On the basis of the adaptive backstepping recursive design technique, an adaptive fuzzy decentralized output feedback is developed. It is proved that the proposed control approach can guarantee that all the signals of the resulting closed‐loop system are semiglobally uniformly ultimately bounded (SUUB), and that the observer and tracking errors converge to a small neighborhood of the origin by appropriate choice of the design parameters. Simulation studies are included to illustrate the effectiveness of the proposed approach. Copyright © 2012 John Wiley & Sons, Ltd.     

Jcluster: an efficient Java parallel environment on a large‐scale heterogeneous cluster

In this paper, we present Jcluster, an efficient Java parallel environment that provides some critical services, in particular automatic load balancing and high‐performance communication, for developing parallel applications in Java on a large‐scale heterogeneous cluster. In the Jcluster environment, we implement a task scheduler based on a transitive random stealing (TRS) algorithm. Performance evaluations show that the scheduler based on TRS can make any idle node obtain a task from another node with much fewer stealing times than random stealing (RS), which is a well‐known dynamic load‐balancing algorithm, on a large‐scale cluster. In the performance aspects of communication, with the method of asynchronously multithreaded transmission, we implement a high‐performance PVM‐like and MPI‐like message‐passing interface in pure Java. The evaluation of the communication performance is conducted among the Jcluster environment, LAM‐MPI and mpiJava on LAM‐MPI based on the Java Grande Forum's pingpong benchmark. Copyright © 2005 John Wiley & Sons, Ltd.     

Performance analysis and optimization of AMGA for the large‐scale virtual screening

This paper addresses performance issues on ARDA Metadata Grid Application (AMGA) and presents new techniques to improve the throughput of AMGA for the WISDOM environment. The first issue is a performance degradation problem when AMGA is used as a metadata service for task retrieval in the WISDOM environment. To deal with the issue, a new AMGA operation designed to reduce the communication overhead required to retrieve a task from AMGA is proposed. According to a performance study conducted with the new operation, the throughput of task retrieval using the proposed operation can be as much as 70 times higher than the throughput when using the existing AMGA operations. The second issue is an AMGA throughput issue in large‐scale grid‐enabled applications such as WISDOM, where it is not uncommon that thousands of jobs running on grid nodes access the AGMA service simultaneously. To address this issue, integration of a load‐balancing technique and a DB connection pool technique into the AMGA are proposed. Test results demonstrate that the performance can be improved linearly in proportion to the number of AMGA servers set up for load balancing; the performance improvement continues until the performance limit of the backend database system is reached. Copyright © 2009 John Wiley & Sons, Ltd.     

Robust estimation‐free decentralized prescribed performance control of nonaffine nonlinear large‐scale systems

In this paper, a low‐complexity robust estimation‐free decentralized prescribed performance control scheme is proposed and analyzed for nonaffine nonlinear large‐scale systems in the presence of unknown nonlinearity and external disturbance. To tackle the high‐order dynamics of each tracking error subsystem, a time‐varying stable manifold involving the output tracking error and its high‐order derivatives is constructed, which is strictly evolved within the envelope of user‐specialized prescribed performance. Sequentially, a robust decentralized controller is devised for each manifold, under which the output tracking error and its high‐order derivatives are proven to converge asymptotically to a small residual domain with prescribed fast convergence rate. Additionally, no specialized approximation technique, adaptive scheme, and disturbance observer are needed, which alleviates the complexity and difficulty of robust decentralized controller design dramatically. Finally, 3 groups of illustrative examples are used to validate the effectiveness of the proposed low‐complexity robust decentralized control scheme for uncertain nonaffine nonlinear large‐scale systems.     

Adaptive fuzzy semi‐decentralized control for a class of large‐scale nonlinear systems with unknown interconnections

In this paper, a general method is developed to generate a stable adaptive fuzzy semi‐decentralized control for a class of large‐scale interconnected nonlinear systems with unknown nonlinear subsystems and unknown nonlinear interconnections. In the developed control algorithms, fuzzy logic systems, using fuzzy basis functions (FBF), are employed to approximate the unknown subsystems and interconnection functions without imposing any constraints or assumptions about the interconnections. The proposed controller consists of primary and auxiliary parts, where both direct and indirect adaptive approaches for the primary control part are aiming to maintain the closed‐loop stability, whereas the auxiliary control part is designed to attenuate the fuzzy approximation errors. By using Lyapunov stability method, the proposed semi‐decentralized adaptive fuzzy control system is proved to be globally stable, with converging tracking errors to a desired performance. Simulation examples are presented to illustrate the effectiveness of the proposed controller. Copyright © 2006 John Wiley & Sons, Ltd.     

Comparison of metaheuristics for the k‐labeled spanning forest problem

In this paper, we study the k‐labeled spanning forest (kLSF) problem in which an undirected graph whose edges are labeled and an integer‐positive value are given; the aim is to find a spanning forest of the input graph with the minimum number of connected components and the upper bound on the number of labels. The problem is related to the minimum labeling spanning tree problem and has several applications in the real world. In this paper, we compare several metaheuristics to solve this NP‐hard problem. In particular, the proposed intelligent variable neighborhood search (VNS) shows excellent performance, obtaining high‐quality solutions in short computational running time. This approach integrates VNS with other complementary approaches from machine learning, statistics, and experimental algorithmics, in order to produce high‐quality performance and completely automate the resulting optimization strategy.     

Adaptive decentralized fault‐tolerant tracking control for large‐scale nonlinear systems with input quantization

In this paper, an adaptive decentralized tracking control scheme is designed for large‐scale nonlinear systems with input quantization, actuator faults, and external disturbance. The nonlinearities, time‐varying actuator faults, and disturbance are assumed to exist unknown upper and lower bounds. Then, an adaptive decentralized fault‐tolerant tracking control method is designed without using backstepping technique and neural networks. In the proposed control scheme, adaptive mechanisms are used to compensate the effects of unknown nonlinearities, input quantization, actuator faults, and disturbance. The designed adaptive control strategy can guarantee that all the signals of each subsystem are bounded and the tracking errors of all subsystems converge asymptotically to zero. Finally, simulation results are provided to illustrate the effectiveness of the designed approach.     

Observer‐based decentralized adaptive control for large‐scale pure‐feedback systems with unknown time‐delayed nonlinear interactions

This paper presents an approximation design for a decentralized adaptive output‐feedback control of large‐scale pure‐feedback nonlinear systems with unknown time‐varying delayed interconnections. The interaction terms are bounded by unknown nonlinear bounding functions including unmeasurable state variables of subsystems. These bounding functions together with the algebraic loop problem of virtual and actual control inputs in the pure‐feedback form make the output‐feedback controller design difficult and challenging. To overcome the design difficulties, the observer‐based dynamic surface memoryless local controller for each subsystem is designed using appropriate Lyapunov‐Krasovskii functionals, the function approximation technique based on neural networks, and the additional first‐order low‐pass filter for the actual control input. It is shown that all signals in the total controlled closed‐loop system are semiglobally uniformly bounded and control errors converge to an adjustable neighborhood of the origin. Finally, simulation examples are provided to illustrate the effectiveness of the proposed decentralized control scheme. Copyright © 2013 John Wiley & Sons, Ltd.     

Adaptive NN output‐feedback decentralized stabilization for a class of large‐scale stochastic nonlinear strict‐feedback systems

In this paper, the decentralized adaptive neural network (NN) output‐feedback stabilization problem is investigated for a class of large‐scale stochastic nonlinear strict‐feedback systems, which interact through their outputs. The nonlinear interconnections are assumed to be bounded by some unknown nonlinear functions of the system outputs. In each subsystem, only a NN is employed to compensate for all unknown upper bounding functions, which depend on its own output. Therefore, the controller design for each subsystem only need its own information and is more simplified than the existing results. It is shown that, based on the backstepping method and the technique of nonlinear observer design, the whole closed‐loop system can be proved to be stable in probability by constructing an overall state‐quartic and parameter‐quadratic Lyapunov function. The simulation results demonstrate the effectiveness of the proposed control scheme. Copyright © 2010 John Wiley & Sons, Ltd.     

Robust decentralized adaptive fuzzy control for a class of large‐scale MIMO nonlinear systems

In this paper, a novel decentralized robust adaptive fuzzy control scheme is proposed for a class of large‐scale multiple‐input multiple‐output uncertain nonlinear systems. By virtue of fuzzy logic systems and the regularized inverse matrix, the decentralized robust indirect adaptive fuzzy controller is developed such that the controller singularity problem is addressed under a united design framework; no a priori knowledge of the bounds on lumped uncertainties are being required. The closed‐loop large‐scale system is proved to be asymptotically stable. Simulation results confirmed the validity of the approach presented. Copyright © 2011 John Wiley & Sons, Ltd.     

Decentralized output feedback stabilization for a class of large‐scale feedforward nonlinear time‐delay systems

This paper is concerned with the decentralized stabilization problem for a class of large‐scale feedforward nonlinear time‐delay systems. The uncertain nonlinearities involved in the systems are assumed to be bounded by continuous functions of the inputs and delayed inputs multiplied by unmeasured states and delayed states. An observer‐based decentralized output feedback control scheme is proposed by using the dynamic gain control design approach. On the basis of the Lyapunov–Krasovskii stability theory, the global asymptotic stability of the closed‐loop control system is proved. Contrary to many existing control designs for feedforward nonlinear systems, the celebrated forwarding design and saturation design are not utilized here. An example is finally given to demonstrate the effectiveness of the proposed design procedure. Copyright © 2013 John Wiley & Sons, Ltd.     

Global decentralized sampled‐data output feedback stabilization for a class of large‐scale nonlinear systems with sensor and actuator failures

In this paper, we investigate global decentralized sampled‐data output feedback stabilization problem for a class of large‐scale nonlinear systems with time‐varying sensor and actuator failures. The considered systems include unknown time‐varying control coefficients and inherently nonlinear terms. Firstly, coordinate transformations are introduced with suitable scaling gains. Next, a reduced‐order observer is designed to estimate unmeasured states. Then, a decentralized sampled‐data fault‐tolerant control scheme is developed with an allowable sampling period. By constructing an appropriate Lyapunov function, it can be shown that all states of the resulting closed‐loop system are globally uniformly ultimately bounded. Finally, the validity of the proposed control approach is verified by using two examples.