67 resultados para distributed parameter systems


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This paper initiates the study of two specific security threats on smart-card-based password authentication in distributed systems. Smart-card-based password authentication is one of the most commonly used security mechanisms to determine the identity of a remote client, who must hold a valid smart card and the corresponding password to carry out a successful authentication with the server. The authentication is usually integrated with a key establishment protocol and yields smart-card-based password-authenticated key agreement. Using two recently proposed protocols as case studies, we demonstrate two new types of adversaries with smart card: 1) adversaries with pre-computed data stored in the smart card, and 2) adversaries with different data (with respect to different time slots) stored in the smart card. These threats, though realistic in distributed systems, have never been studied in the literature. In addition to point out the vulnerabilities, we propose the countermeasures to thwart the security threats and secure the protocols. © 2013 IEEE.

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In this paper, a novel robust finite-horizon Kalman filter is developed for discrete linear time-varying systems with missing measurements and normbounded parameter uncertainties. The missing measurements are modelled by a Bernoulli distributed sequence and the system parameter uncertainties are in the state and output matrices. A two stage recursive structure is considered for the Kalman filter and its parameters are determined guaranteeing that the covariances of the state estimation errorsare not more than the known upper bound. Finally, simulation results are presented to illustrate the outperformance of the proposed robust estimator compared with the previous results in the literature.

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In this paper, an agent-based distributed control scheme is presented to control single-phase parallel inverters in solar photovoltaic (PV) systems connected to microgrids. A communication assisted multi-agent framework is developed within microgrids where agents perform their tasks in a distributed manner with an aim of stabilizing load voltage and current under normal and faulted conditions through the asymptotic tracking of the reference current signal. The distributed agent-based control scheme requires information from the neighboring agents through communication network to decide control actions. The proposed control scheme utilizes Ziegler-Nichols (Z-N) tuning approach to design proportional integral (PI) controllers for controlling inverters within the multi-agent system (MAS). A microgrid with parallel inverter-connected solar PV systems is considered for simulations under normal and faulted conditions where results show the excellency of the proposed agent-based scheme in comparison to the conventional scheme without MAS.

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This paper presents a load frequency control scheme using electric vehicles (EVs) to help thermal turbine units to provide the stability fluctuated by load demands. First, a general framework for deriving a state-space model for general power system topologies is given. Then, a detailed model of a four-area power system incorporating a smart and renewable discharged EVs system is presented. The areas within the system are interconnected via a combination of alternating current/high voltage direct current links and thyristor controlled phase shifters. Based on some recent development on functional observers, novel distributed functional observers are designed, one at each local area, to implement any given global state feedback controller. The designed observers are of reduced order and dynamically decoupled from others in contrast to conventional centralized observer (CO)-based controllers. The proposed scheme can cope better against accidental failures than those CO-based controllers. Extensive simulations and comparisons are given to show the effectiveness of the proposed control scheme.

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Growing evidence shows that in obtaining high performance, a well-managed time-constrained workflow scheduling is needed. Efficient workflow scheduling is critical for achieving high performance especially in heterogeneous computing system. However, it is a great challenge to improve performance and to optimize several objectives simultaneously. We propose a workflow scheduling algorithm that minimizes the makespan of the workflow application modeled by a Directed Acyclic Graph (DAG). The new proposed scheduling algorithm is named Multi Dependency Joint (MDJ) Algorithm. The performance of MDJ is compared with existing algorithms such as, Highest Level First with Estimated Time (HLFET), Modified Critical Path (MCP) and Earliest Time First (ETF). As a result, the experiments show that our proposed MDJ algorithm outperforms HLEFT, MCP, and EFT with a 7% lower overall completion time.

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The rapid development and increasing complexity of computer systems and communication networks coupled with the proliferation of services and applications in both Internet-based and ad-hoc based environments have brought network and system security issues to the fore. We have been witnessing ever-increasing cyber attacks on the network and system leading to tarnished confidence and trusts in the use of networked distributed systems. As a result, there is an increasing demand for development of new trust, security and privacy approaches to guarantee the privacy, integrity, and availability of resources in networked distributed systems.