Performance evaluation of shortest multipath source routing scheme

Multipath routing in mobile ad-hoc networks allows the establishment of multiple paths for routing between a source-destination pair. It exploits the resource redundancy and diversity in the underlying network to provide benefits such as fault tolerance, load balancing, bandwidth aggregation and the improvement in quality-of-service metrics such as delay. Previous work shows that on-demand multipath routing schemes achieve better performance under certain scenarios with respect to a number of key performance metrics when compared with traditional single-path routing mechanisms. A multipath routing scheme, referred to as shortest multipath source (SMS) routing based on dynamic source routing (DSR) is proposed here. The mechanism has two novel aspects compared with other on-demand multipath routing schemes: it achieves shorter multiple partial-disjoint paths and allows more rapid recovery from route breaks. The performance differentials are investigated using NS-2 under conditions of varying mobility, offered load and network size. Results reveal that SMS provides a better solution than existing source-based approaches in a truly mobile ad-hoc environment.     

Design and performance analysis of code families for multi-dimensional optical CDMA

A code design algorithm for application in multi-dimensional optical code division multiple access (MD-OCDMA) for asynchronous optical fibre communication is proposed. Two-dimensional (2D) wavelength-time or space-time OCDMA and three-dimensional (3D) space-wavelength-time OCDMA are subsets of MD-OCDMA. Some applications and the performance analysis of the algorithm in 2D multipulse per row codes and 3D multipulse per plane codes are shown. In the applications discussed, this design ensures a maximum cross-correlation of '1' between any two codes. The performance metrics studied are the probability of error due to multiple-access interference for different numbers of active users and optimum temporal length for different values of cardinality. The performance analysis shows that the proposed 2D design offers very low probability of error due to multiple-access interference at lower cardinality when compared with other 2D designs using equivalent code dimension. A comparison of the proposed 3D design with an existing 3D design shows better performance at lower cardinality. The 3D designs show better performance when compared with the 2D designs.     

Optimisation of facility layout design problem with safety and environmental factors by stochastic DEA and simulation approach

This article presents an integrated computer simulation–stochastic data envelopment analysis (SDEA) approach to deal with the job shop facility layout design problem (JSFLD) with stochastic outputs and safety and environmental factors. Stochastic outputs are defined as non-crisp operational and deterministic inputs. At first, feasible layout alternatives are generated under expert decision. Then, computer simulation network is used for performance modelling of each layout design. The outputs of simulation are average time-in-system, average queue length and average machine utilisation. Finally, SDEA is used with Lingo software for finding the optimum layout alternative amongst all feasible generated alternatives with respect to stochastic, safety and environmental indicators. The integrated approach of this study was more precise and efficient than previous studies with the stated outputs. The results have been verified and validated by principal component analysis. The unique features of this study are the ability of dealing with multiple inputs (including safety) and stochastic (including environmental) outputs. It also uses mathematical programming for optimum layout alternatives. Moreover, it is a practical tool and may be applied in real cases by considering safety and environmental aspects of the manufacturing process within JSFLD problems.     

Model-based process monitoring using robust generalized linear models

Model-based process-monitoring procedures are extremely useful in situations where an output variable of interest is impacted by one or more inputs to the process, and where there are multistage processes with multiple inputs and outputs. To build the model relating input and output variables, the procedure uses historical data, which often contain outliers. To accommodate the presence of these outliers, a robust fitting scheme is introduced for the Generalized Linear Model in process monitoring. Robust deviance residuals are defined and used as the basis of the monitoring procedure. An example and a simulation study for a gamma-distributed response are included. The average run length performance reveals that the procedure is effective for detecting small process shifts when outliers are present.     

CUSUM Statistical Monitoring of M/M/1 Queues and Extensions

Many production and service systems can be modeled as queueing systems. Their operational efficiency and performance are often measured using queueing performance metrics (QPMs), such as average cycle time, average waiting length, and throughput rate. These metrics need to be quantitatively evaluated and monitored in real time to continuously improve the system performance. However, QPMs are often highly stochastic, and hence are difficult to monitor using existing methods. In this article, we propose the cumulative sum (CUSUM) schemes to efficiently monitor the performance of typical queueing systems based on different sampling schemes. We use M/M/1 queues to illustrate how to design the CUSUM chart and compare their performance with several alternative methods. We demonstrate that the performance of CUSUM is superior, responding faster to many shift patterns through extensive numerical studies. We also briefly discuss the extensions of CUSUM charts to more general queues, such as M/G/1, G/G/1, or M/M/c queues. We use case studies to demonstrate the applications of our approach. Supplementary materials for this article are available online.     

Optimization of Degree of Conformance in Multiresponse–Multistage Systems with a Simulation‐based Metaheuristic

In today's manufacturing and service systems, entities are progressed across the several stages of operations wherein one or more quality characteristic may be formed. The quality of final system outputs depends on the quality of intermediate characteristics as well as design parameters in each stage. This paper presents a new mathematical program to simultaneously optimize multiple quality characteristics in multiple stage systems. Multivariate form response surface methodology is applied with iterative seemingly unrelated regression as the estimation method to extract the relationships between the outputs and inputs in each stage. Because the intermediate response variables may act as covariates in the next stages, the probabilistic patterns of the response surfaces are considered by association with the quality of the previous stages. The objective function in the proposed model is the acceptance probability of the outputs based on predefined specification limits. A combination of Monte Carlo simulation and the genetic algorithm is also proposed to solve the final stochastic optimization model. At the end, the applicability of the proposed approach is illustrated by a numerical example. Copyright © 2014 John Wiley & Sons, Ltd.     

Statistical characteristics of the envelope in diversity combining of two correlated Rayleigh fading channels

Performance of diversity systems is often evaluated under the assumption of perfect interleaving and characterised in terms of long-term parameters such as the average bit-error rate, which does not capture the dynamics of fading channels. Statistical characteristics (static and dynamic) of the envelope of two correlated Rayleigh fading channels are explored using a physical model. For two popular diversity-combining schemes, maximal ratio combining and selection combining, both static and dynamic (level-crossing rate) properties of correlated fading channels are derived. These results are very useful for performance evaluation of diversity systems without bit-level simulations. The results can also provide very useful characteristics such as average duration of fades, fading rate and outage probability for two-channel diversity systems and can be extended to multiple fading channels     

Evaluating the efficiency of local municipalities in providing traffic safety using the Data Envelopment Analysis

The purpose of this study was to estimate the relative efficiency of 197 local municipalities in traffic safety in Israel during 2004–2009, using Data Envelopment Analysis (DEA). DEA efficiency is based on multiple inputs and multiple outputs, when their weights are unknown. We used here inputs reflecting the resources allocated to the local municipalities (such as funding), outputs include measures that reflect reductions in accidents (such as accidents per population), and intermediate variables known as safety performance indicators (SPI): measures that are theoretically linked to crash and injury reductions (such as use of safety belts). Some of the outputs are undesirable. Using DEA, the local municipalities were rank-scaled from the most efficient to the least efficient and required improvements for inefficient municipalities were calculated. We found that most of the improvements were required in two intermediate variables related to citations for traffic violations. Several DEA versions were used including a two-stage model where in the first stage the intermediate variables are the outputs, and in the second stage they are the inputs. Further analyses utilizing multiple regressions were performed to verify the effect of various demographic parameters on the efficiency of the municipalities. The demographic parameters tested for each local municipality were related to the size, age, and socio-economic level of the population. The most significant environmental variable affecting the efficiency of local municipalities in preventing road accidents is the population size of the local authority; the size has a negative effect on the efficiency. As far as we could determine, this is the first time that the DEA is used to measure the efficiency of local municipalities in improving traffic safety.     

Analytical performance evaluation of ultra-wideband multiple access schemes for different wireless sensor network application environments

One of the most promising uses for ultra-wideband (UWB) is wireless sensor networks (WSNs). Since WSNs offer a wide variety of services for different application areas, the UWB propagation channel characteristics of each application environment show fundamental differences from each other in many aspects. A reliable and energy-efficient multiple access scheme is thus required to coordinate the transmissions of sensor nodes in these various application channel environments. We develop an analytical framework for evaluating the performance of UWB time-hopping (TH), direct sequence (DS) and orthogonal frequency division multiplexing (OFDM) multiple access schemes with multi-node interference in the following UWB propagation channel environments that have a high importance for WSN applications: residential, office, suburban outdoor, industrial and agricultural. The objective is to determine the most appropriate multiple access scheme to be applied for a particular WSN application channel environment. Performance is evaluated in terms of the average information throughput efficiency, a relevant progress-related measure for multihop WSNs. The mathematical expression of this metric is derived in detail, and is used in numerical evaluations for assessing the performance of the three schemes operating under UWB propagation channel models of the various environments that are characterised by distinct channel parameters and specific valid distance ranges. TH-UWB is shown to be the most suitable multiple access scheme to be adopted for UWB WSNs. It outperforms both the DS-UWB and OFDM-UWB schemes for all application environments and is the most robust and energy efficient. OFDM-UWB is the poorest performing whereas DS-UWB provides similar performance to TH-UWB below a specific threshold number of interfering nodes.     

Sparse polynomial surrogates for non-intrusive,high-dimensional uncertainty quantification of aeroelastic computations

This paper is concerned with aircraft aeroelastic interactions and the propagation of parametric uncertainties in numerical simulations using high-fidelity fluid flow solvers. More specifically, the influence of variable operational and structural parameters (random inputs) on the drag performance and deformation (outputs) of a flexible wing in transonic regime, is assessed. Because of the complexity of fluid flow solvers, non-intrusive uncertainty quantification techniques are favored. Polynomial surrogate models based on homogeneous chaos expansions in the random inputs are commonly considered in this respect. The polynomial expansion coefficients are constructed using either structured sampling sets of the input parameters, as Gauss quadrature nodes, or unstructured sampling sets, as in Monte-Carlo methods. In complex systems such as the advanced aeroelastic test case studied here, the output quantities of interest generally depend only weakly on the multiple cross-interactions between the random inputs. Consequently, only low-order polynomials significantly contribute to their surrogates, which thus have a sparse structure in the underlying polynomial bases. This feature prompts to use compressed sensing, or compressive sampling theory for the construction of the polynomial surrogates. The proposed methodology is non-adapted and considers unstructured sampling sets orders of magnitude smaller than the ones required by the usual techniques with structured sampling sets. It is illustrated in the present work for a moderately to high dimensional parametric space.     

A Novel Universal Steganalysis Algorithm Based on the IQM and the SRM

The state-of-the-art universal steganalysis method, spatial rich model (SRM), and the steganalysis method using image quality metrics (IQM) are both based on image residuals, while they use 34671 and 10 features respectively. This paper proposes a novel steganalysis scheme that combines their advantages in two ways. First, filters used in the IQM are designed according to the models of the SRM owning to their strong abilities for detecting the content adaptive steganographic methods. In addition, a total variant (TV) filter is also used due to its good performance of preserving image edge properties during filtering. Second, due to each type of these filters having own advantages, the multiple filters are used simultaneously and the features extracted from their outputs are combined together. The whole steganalysis procedure is removing steganographic noise using those filters, then measuring the distances between images and their filtered version with the image quality metrics, and last feeding these metrics as features to build a steganalyzer using either an ensemble classifier or a support vector machine. The scheme can work in two modes, the single filter mode using 9 features, and the multi-filter mode using 639 features. We compared the performance of the proposed method, the SRM and the maxSRMd2. The maxSRMd2 is the improved version of the SRM. The simulated results show that the proposed method that worked in the multi-filter mode was about 10% more accurate than the SRM and maxSRMd2 when the data were globally normalized, and had similar performance with the SRM and maxSRMd2 when the data were locally normalized.     

基于自主运算的自管理的IP-SAN存储系统的体系结构与性能策略

性能问题和系统管理问题是IP-SAN存储系统最需要解决的问题。针对IP-SAN存储系统和工作负载的特点设计和实现了一个基于自主运算的自管理的IP-SAN存储系统，使系统能够自我适应外部环境的变化进行自我配置和自我优化，从而有效地改进系统性能。重点阐述了自管理的IP-SAN存储系统的体系结构和性能策略，详细地介绍了多个不同性能策略的具体算法。测试结果显示基于自主运算的自管理的IP-SAN存储系统有效地提高了响应时间和吞吐量等性能。     

Reliability and performance analysis of time – space – time switching networks with multiple separated space switches

Since electronic switching systems usually require very strict reliability requirements as well as good performance objectives, we need to jointly analyse the performance and reliability of switching systems. In this paper, we compare conventional time–space–time switches with single space switches with those with multiple separated space switches, from the viewpoints of reliability and performance. We consider time–space–time switching networks which consist of N incoming time switches, i.e. one NxN space switch, two (N/2)x(N/2) space switches, and four (N/4)x(N/4) space switches. We introduce a Markov reliability model to study the effect of failures and analyse the reliability and performance of three different types of switching networks in terms of average blocking probability and the mean time to unreliable operation, as we vary the offered traffic. As a result, T–S–T switching networks with multiple separated space switches exhibit better performance and reliability than those with single space switches.     

Information-theoretic sensitivity analysis: a general method for credit assignment in complex networks.

Most systems can be represented as networks that couple a series of nodes to each other via one or more edges, with typically unknown equations governing their quantitative behaviour. A major question then pertains to the importance of each of the elements that act as system inputs in determining the output(s). We show that any such system can be treated as a 'communication channel' for which the associations between inputs and outputs can be quantified via a decomposition of their mutual information into different components characterizing the main effect of individual inputs and their interactions. Unlike variance-based approaches, our novel methodology can easily accommodate correlated inputs.     

A study on group decision-making based fault multi-symptom-domain consensus diagnosis

In the field of fault diagnosis for rotating machines, the conventional methods or the neural network based methods are mainly single symptom domain based methods, and the diagnosis accuracy of which is not always satisfactory. In this paper, in order to utilize multiple symptom domains to improve the diagnosis accuracy, an idea of fault multi-symptom-domain consensus diagnosis is developed. From the point of view of the group decision-making, two particular multi-symptom-domain diagnosis strategies are proposed. The proposed strategies use BP (Back-Propagation) neural networks as diagnosis models in various symptom domains, and then combine the outputs of these networks by two combination schemes, which are based on Dempster–Shafer evidence theory and fuzzy integral theory, respectively. Finally, a case study pertaining to the fault diagnosis for rotor-bearing systems is given in detail, and the results show that the proposed diagnosis strategies are feasible and more efficient than conventional stacked-vector methods.     

Fuzzy simulation approach to multi-task scheduling in uncertain distributed server systems

The efficient scheduling of tasks in distributed server systems is of great importance to minimise the response time and thus improve the performance of such systems. This paper presents an integrated fuzzy simulation approach to improve the performance of distributed server systems. Performance is defined in terms of time-varying distributions of job arrival, job parallelism and task service demand with fuzzy parameters. In order to achieve the most efficient policies for job scheduling in this fuzzy system, an integrated fuzzy simulation approach is used. This is the first study that uses fuzzy simulation for performance improvement of uncertain distributed server systems.     

地震动多元强度参数主成分与结构损伤的相关性分析

采用主成分分析方法,考虑多个地震动强度参数,综合分析多元地震动强度参数主成分与结构损伤之间的相关性。以单自由度体系为研究对象,使用三种恢复力模型,选择80条真实地震动记录作为输入,分析得到体系在地震作用下的最大位移和滞回能量。采用挑选的10个地震动强度参数,基于主成分分析方法,构造地震动强度的主成分线性组合,并对地震动强度参数主成分与结构损伤之间的相关性进行分析。结果表明:由于考虑了多个地震动强度参数,相比于单个地震动强度参数与结构损伤之间的相关性,地震动多元强度参数主成分与结构损伤之间的相关性更为稳定。     

Improved Hybrid Beamforming for mmWave Multi-User Massive MIMO

Massive multiple input multiple output (MIMO) has become essential for the increase of capacity as the millimeter-wave (mmWave) communication is considered. Also, hybrid beamforming systems have been studied since full-digital beamforming is impractical due to high cost and power consumption of the radio frequency (RF) chains. This paper proposes a hybrid beamforming scheme to improve the spectral efficiency for multi-user MIMO (MU-MIMO) systems. In a frequency selective fading environment, hybrid beamforming schemes suffer from performance degradation since the analog precoder performs the same precoding for all subcarriers. To mitigate performance degradation, this paper uses the average channel covariance matrix for all subcarriers and considers an iterative algorithm to design analog precoder using approximation techniques. The analog precoder is iteratively updated for each column until it converges. The proposed scheme can reduce errors in the approximating process of the overall spectral efficiency. This scheme can be applied to fully-connected and partially-connected structures. The simulation results show that spectral efficiency performance for the proposed scheme is better than the conventional schemes. The proposed scheme can achieve similar performance with full-digital beamforming by using a sufficiently large number of RF chains. Also, this paper shows that the proposed scheme outperforms other schemes in the frequency selective fading environment. This performance improvement can be achieved in both structures.     

Information processing by biochemical networks: a dynamic approach

Understanding how information is encoded and transferred by biochemical networks is of fundamental importance in cellular and systems biology. This requires analysis of the relationships between the stochastic trajectories of the constituent molecular (or submolecular) species that comprise the network. We describe how to identify conditional independences between the trajectories or time courses of groups of species. These are robust network properties that provide important insight into how information is processed. An entire network can then be decomposed exactly into modules on informational grounds. In the context of signalling networks with multiple inputs, the approach identifies the routes and species involved in sequential information processing between input and output modules. An algorithm is developed which allows automated identification of decompositions for large networks and visualization using a tree that encodes the conditional independences. Only stoichiometric information is used and neither simulations nor knowledge of rate parameters are required. A bespoke version of the algorithm for signalling networks identifies the routes of sequential encoding between inputs and outputs, visualized as paths in the tree. Application to the toll-like receptor signalling network reveals that inputs can be informative in ways unanticipated by steady-state analyses, that the information processing structure is not well described as a bow tie, and that encoding for the interferon response is unusually sparse compared with other outputs of this innate immune system.     

Analysis of some channel selection methods for networks with multiple channels

Abstract

Communications networks with multiple parallel channels become more feasible more than before because of the decreasing cost of equipments. Advantages of using multiple parallel channels to connect terminals include better reliability and fault‐tolerance capability, higher throughput and lower delay, easier implementing priority schemes, and more adaptable to provide various kinds of network services. We analyze in this paper the performances of four different channel selection methods in a network with multiple parallel channels. The basic idea is that the performance can be significantly improved by transmitting multiple copies of the same packet simultaneously. We also evaluate the performance deterioration caused by channel failures. The deterioration is observed to be significant if users do not know which channels are out of order. However, an efficient fault‐diagnosis technique is very helpful to alleviate the deterioration. Some easily implementable priority schemes, which are called priority by diversity, priority by privilege, and priority by diversity and privilege, are discussed and evaluated. By appropriately adjustig the values of the control parameters, one can get a suitable priority scheme to achieve the desired performance.