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In this paper three models of parallel speedup are studied. They are fized-size speedup, fized-time speedup and memoq-bounded speedup. Two sets of speedup formulations are derived for these three models. One set requires more information and gives more accurate estimation. Another set considers a simplified case and provides a clear picture of possible performance gain of parallel processing. The simplified fixed-size speedup is Amdahl's law. The simplified fixed-time speedup is Gustafson's scaled speedup. The simplified memorybounded speedup contains both Amdahl's law and Gustafson's scaled speedup as its special cases. This study proposea a new metric for performance evaluation and leads to a better understanding of parallel processing.

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In this paper, a new nonlinear decentralized disturbance attenuation excitation control for multi-machine power systems is proposed based on recursive design without linearization treatment. The proposed controller improves system robustness to dynamic uncertainties and also attenuates bounded exogenous disturbances on the system in the sense of L 2-gain [1]. Computer test results on a 6-machine system show clearly that the proposed excitation control strategy can enhance transient stability of power systems more effectively than other excitation controllers.

Abstract-This paper describes software implementation for online risk-based security assessment which computes indices based on probabilistic risk for use by operators in the control room to assess system security levels as a function of existing and near-future network conditions. The paper focuses on speed enhancement techniques that are essential for online application and result visualization methods that offer clear and meaningful ways to enhance human assimilation and comprehension of security levels. Results of testing on a series of 1600 bus power flow models retrieved from the energy management system of a large U.S. utility are presented and serve to illustrate the benefits of the software.

Blind flooding is a popular search mechanism used in current commercial P2P systems because of its simplicity. However, blind flooding among peers or superpeers causes large volume of unnecessary traffic although the response time is short. Some improved statistics-based search mechanisms can reduce the traffic volume but also significantly shrink the query coverage range. In some search mechanisms, not all peers may be reachable creating the so-called partial coverage problem. Aiming at alleviating the partial coverage problem and reducing the unnecessary traffic, we propose an efficient and adaptive search mechanism, Hybrid Periodical Flooding (HPF). HPF retains the advantages of statistics-based search mechanisms, alleviates the partial coverage problem, and provides the flexibility to adaptively adjust different parameters to meet different performance requirements. The effectiveness of HPF is demonstrated through simulation studies.

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