What is the complexity of a distributed computing system?

Distributed computing systems are becoming bigger and more complex. Although the complexity of large‐scale distributed systems has been acknowledged to be an important challenge, there has not been much work in defining or measuring system complexity. Thus, today, it is difficult to compare the complexities of different systems, or to state that one system is easier to program, to manage, or to use than another. In this article, we try to understand the factors that cause computing systems to appear very complex to people. We define different aspects of system complexity and propose metrics for measuring these aspects. We also show how these aspects affect different kinds of people—viz. developers, administrators, and end‐users. On the basis of the aspects and metrics of complexity that we identify, we propose general guidelines that can help reduce the complexity of systems. © 2007 Wiley Periodicals, Inc. Complexity 12: 37–45, 2007     

Parallel Newton Two-Stage Multisplitting Iterative Methods for Nonlinear Systems

Parallel Newton two-stage iterative methods to solve nonlinear systems are studied. These algorithms are based on both the multisplitting technique and the two-stage iterative methods. Convergence properties of these methods are studied when the Jacobian matrix is either monotone or an H-matrix. Furthermore, in order to illustrate the performance of the algorithms studied, computational results about these methods on a distributed memory multiprocessor are discussed.This revised version was published online in October 2005 with corrections to the Cover Date.     

Optimality conditions for age-structured control systems

We consider a fairly general model (extension of the Gurtin-MacCamy model of population dynamics) of an age structured control system with nonlocal dynamics and nonlocal boundary conditions. A necessary optimality condition is obtained in the form of Pontryagin's maximum principle, which is applicable to a number of practically meaningful models where the previously known results fail. We discuss such models (an epidemic control, and a capital accumulation model) as illustrations.     

A Domain Embedding Method Using the Optimal Distributed Control and a Fast Algorithm

We propose a domain embedding method to solve second order elliptic problems in arbitrary two-dimensional domains. The method is based on formulating the problem as an optimal distributed control problem inside a disc in which the arbitrary domain is embedded. The optimal distributed control problem inside the disc is solved rapidly using a fast algorithm developed by Daripa et al. [3,7,10–12]. The arbitrary domains can be simply or multiply connected and the proposed method can be applied, in principle, to a large number of elliptic problems. Numerical results obtained for Dirichlet problems associated with the Poisson equation in simply and multiply connected domains are presented. The computed solutions are found to be in good agreement with the exact solutions with moderate number of grid points in the domain.     

"大互联网梅森素数寻求(GIMPS)"研究计划进展

梅森素数是一种特殊的素数,它的研究与寻求一直是数论研究的代表性问题之一.寻求梅森素数之路艰辛曲折,其计算复杂性对现代计算能力极具挑战.计算机网络技术的发展,特别是能使虚拟组织共享计算资源的全球分布计算技术,使得寻求速度大大加快.本文综述寻求梅森素数的最新进展及历史进程,并介绍寻求梅森数所用的分布计算技术.     

EXISTENCE AND ATTRACTIVITY OF ALMOST PERIODIC SOLUTION FOR SHUNTING INHIBITORY CELLULAR NEURAL NETWORKS WITH CONTINUOUSLY DISTRIBUTED DELAYS AND VARIABLE COEFFICIENTS

In this paper, a class of two-dimensional shunting inhibitory cellular neural networks with distributed delays and variable coefficients system is studied. By using the Schauder's fixed point theorem and Lyapunov function, we obtain some sufficient conditions about the existence and attractivity of almost periodic solutions to the above system, and all its solutions converge to such almost periodic solution. An example is given to illustrate that the conditions of our results are feasible.     

Allocating modelling resources in distributed model management systems

Due to the growing popularity of distributed computing systems and the increased level of modelling activity in most organizations, significant benefits can be realized through the implementation of distributed model management systems (DMMS). These systems can be defined as a collection of logically related modelling resources distributed over a computer network. In several ways, functions of DMMS are isomorphic to those of distributed database systems. In general, this paper examines issues viewed as central to the development of distributed model bases (DMB). Several criteria relevant to the overall DMB design problem are discussed. Specifically, this paper focuses on the problem of distributing decision models and tools (solvers), henceforth referred to as theModel Allocation Problem (MAP), to individual computing sites in a geographically dispersed organization. In this research, a 0/1 integer programming model is formulated for the MAP, and an efficient dual ascent heuristic is proposed. Our extensive computational study shows in most instances heuristic-generated solutions which are guaranteed to be within 1.5–7% of optimality. Further, even problems with 420 integer and 160,000 continuous variables took no more than 60 seconds on an IBM 3090-600E computer.     

Asymptotics of Estimating Equations under Natural Conditions

In a variety of statistical problems one needs to solve an equation in order to get an estimator. We consider the large sample properties of such estimators generated from samples that are not necessarily identically distributed. Very general assumptions that lead to the existence, strong consistency, and asymptotic normality of the estimators are given. A number of results that are useful in verifying the general assumptions are given and an example illustrates their use. General applications to maximum likelihood, iteratively reweighted least squares, and robust estimation are discussed briefly.     

Numerical Method to Fit the Refractive Index Profile of Planar Microlenses Made by Ion Exchange Techniques

We present a fitting method for obtaining a functional form of the refractive index profile of planar microlenses made by ion exchange techniques from total shearing interferometric measurements. Compared to the usual power series expansion fit, this method allows a reduction in the number of coefficients needed to characterize a lens.     

具有分布时滞的一阶微分方程解的渐近稳定性

本文给出具有分布时滞的一阶微分方程零解的渐近稳定性准则。