时延加权融合技术的无线传感器网络控制

本文研究了无线传感器网络控制系统的建模、稳定性与控制器设计问题.首先建立一个新的无线传感器网络控制系统模型,然后提出一种用于多个传感器数据融合的时延相关加权均值方法,并通过系统建模及分析,把无线传感器网络控制系统稳定性问题转换成为具有多个传输时延和丢包现象的多传感器单控制器网络控制系统稳定性问题.并利用线性跳变系统理论...     

Consensus and disturbance attenuation in multi‐agent chains with nonlinear control and time delays

In this paper, we investigate consensus and disturbance attenuation in a chain of mobile agents, which include non‐autonomous agents, semi‐autonomous agents and autonomous agents. In particular, the nonlinear dynamics of non‐autonomous agents is given and cannot be designed, while the dynamics of semi‐autonomous and autonomous agents can be partially and fully designed, respectively. To improve the robustness of multi‐agent chains against disturbances, we propose a nonlinear control framework for semi‐autonomous and autonomous agents such that they mimic the behavior of non‐autonomous agents for compatibility while also exploiting long‐range connections with distant agents. This framework ensures the existence of a unique consensus equilibrium, which is independent of the network size, connectivity topologies, control gains and information delays. Robustness of multi‐agent chains against disturbances is investigated by evaluating the frequency response at the nonlinear level. For infinitely long multi‐agent chains with recurrent patterns, we also derive a condition that ensures the disturbance attenuation but only requires the analysis of the linearized model. A case study is conducted for a connected vehicle system where numerical simulations are used to validate the analytical results. Copyright © 2016 John Wiley & Sons, Ltd.     

传感器网络高效密钥建立方案

随着时间的推移,传感器网络中正常工作的节点越来越少。为了确保网络正常工作,必须适时地添加新节点。针对传感器网络,提出了一个高效的密钥建立方案。该方案构造了n个相互独立的子密钥池,两相邻子密钥池之间存在联系密钥。第j次部署的传感器节点只从第j个子密钥池中选取密钥。理论分析及模拟结果表明与使用固定密钥池的方案相比,该方案的抗毁性显著提高。     

Application of fuzzy sets to manufacturing/distribution planning decisions in supply chains

In the real-world manufacturing/distribution planning decision (MDPD) integration problems in supply chains, the environmental coefficients and parameters are normally imprecise due to incomplete and/or unavailable information. This work presents a fuzzy linear programming approach based on the possibility theory. It applies this approach to solve multi-product and multi-time period MDPD problems with imprecise goals and forecast demand by considering the time value of money of related operating cost categories. The proposed approach attempts to minimize the total manufacturing and distribution costs by considering the levels of inventory, subcontracting and backordering, the available machine capacity and labor levels at each source, forecast demand and available warehouse space at each destination. This study utilizes an industrial case study to demonstrate the feasibility of applying the proposed approach to practical MDPD problems. The primary contribution of this paper is a fuzzy mathematical programming methodology for solving the MDPD integration problems in uncertain environments.     

Approximate steady-state analysis of large Markov models based on the structure of their decision diagram encoding

We propose a new approximate numerical algorithm for the steady-state solution of general structured ergodic Markov models. The approximation uses a state-space encoding based on multiway decision diagrams and a transition rate encoding based on a new class of edge-valued decision diagrams. The new method retains the favorable properties of a previously proposed Kronecker-based approximation, while eliminating the need for a Kronecker-consistent model decomposition. Removing this restriction allows for a greater utilization of event locality, which facilitates the generation of both the state-space and the transition rate matrix, thus extends the applicability of this algorithm to larger and more complex models.     

Efficient Tate pairing computation using double-base chains

Pairing-based cryptosystems have developed very fast in the last few years. The efficiencies of these cryptosystems depend on the computation of the bilinear pairings, In this paper, a new efficient algorithm based on double-base chains for computing the Tate pairing is proposed for odd characteristic p 〉 3. The inherent sparseness of double-base number system reduces the computational cost for computing the Tate pairing evidently. The new algorithm is 9% faster than the previous fastest method for the embedding degree k = 6.     

On the Convergence of Temporal-Difference Learning with Linear Function Approximation

The asymptotic properties of temporal-difference learning algorithms with linear function approximation are analyzed in this paper. The analysis is carried out in the context of the approximation of a discounted cost-to-go function associated with an uncontrolled Markov chain with an uncountable finite-dimensional state-space. Under mild conditions, the almost sure convergence of temporal-difference learning algorithms with linear function approximation is established and an upper bound for their asymptotic approximation error is determined. The obtained results are a generalization and extension of the existing results related to the asymptotic behavior of temporal-difference learning. Moreover, they cover cases to which the existing results cannot be applied, while the adopted assumptions seem to be the weakest possible under which the almost sure convergence of temporal-difference learning algorithms is still possible to be demonstrated.     

Towards More Complete Models of TCP Latency and Throughput

Recently, several researchers have developed equations for modeling TCP behaviors, such as the expected throughput or latency, based on Markov chains derived from TCP with additional simplifying assumptions. In this paper, we suggest new directions for Markov chain analyses of TCP. Our first contribution is to closely examine not just the expectation but the entire cumulative distribution function of transfer times under various models. Particularly for short or medium transfers, the distribution is likely to be more useful than the expectation in terms of measuring end-user satisfaction. We find that the shapes of TCP cumulative distribution functions are remarkably robust to small changes in the model. Our results suggest that simplifying Markov analyses can be extended to yield approximations for the entire distribution as well as for the expectation.Our second contribution is to consider correction procedures to enhance these models. A correction procedure is a rule of thumb that allows equations from one model to be used in other situations. As an example, several analyses use a Drop-Tail loss model. We determine correction procedures for the deviation between this model and other natural loss models based on simulations. The existence of a simple correction procedure in this instance suggests that the high-level behavior of TCP is robust against changes in the loss model.     

Efficient simulated annealing on fractal energy landscapes

We present a new theoretical framework for analyzing simulated annealing. The behavior of simulated annealing depends crucially on the ldergy landscape associated with the optimization problem: the landscape must have special properties if annealing is to be efficient.We prove that certain fractal properties are sufficient for simulated annealing to be efficient in the following sense: If a problem is scaled to have best solutions of energy 0 and worst solutions of energy 1, a solution of expected energy no more than can be found in time polynomial in 1/, where the exponent of the polynomial depends on certain parameters of the fractal. Higher-dimensional versions of the problem can be solved with almost identical efficiency.The cooling schedule used to achieve this result is the familiar geometric schedule of annealing practice, rather than the logarithmic schedule of previous theory. Our analysis is more realistic than those of previous studies of annealing in the constraints we place on the problem space and the conclusions we draw about annealing's performance.The mode of analysis is also new: Annealing is modeled as a random walk on a graph, and recent theorems relating the conductance of a graph to the mixing rate of its associated Markov chain generate both a new conceptual approach to annealing and new analytical, quantitative methods.The efficiency of annealing is compared with that of random sampling and descent algorithms. While these algorithms are more efficient for some fractals, their run times increase exponentially with the number of dimensions, making annealing better for problems of high dimensionality.We find that a number of circuit placement problems have energy landscapes with fractal properties, thus giving for the first time a reasonable explanation of the successful application of simulated annealing to problems in the VLSI domain.This work was done while the author was on leave from IBM Research, and was also sponsored by DARPA and monitored by SNWSC under contract numbers N00039-87-C-0182 and N00039-88-C-0292. The author is completing his doctoral studies with Prof. Alberto Sangiovanni-Vincentelli. He is on leave from the I.B.M. Thomas J. Watson Research Center.     

供应链模式下企业间利益分配演化博弈模型的建立

供应链各个节点企业作为独立的实体,其进入供应链的根本目的就是获得供应链产生的超额利益．本文基于演化博弈理论对供应链中企业的利益分配问题进行了研究,建屯了演化博弈模型,并对模型进行了分析,最终确定了分配系数的取值．