Investigating Optical Transport Network Performance:A Recurrence Plot Approach

In future optical transport networks,lightpath performance analysis is of great practical significance for fully automated management.In general,the quality of transmission(QoT)of lightpaths,measured by optical quality factor or optical signal-to-noise ratio,has a complex time-varying process,along with the interactions of the other lightpath state parameters(LSPs),such as transmit power,chromatic dispersion,polarization mode dispersion.Current studies are mostly focused on lightpath QoT estimation,but ignoring lightpath-level data analytics.In this case,our article proposes a novel lightpath performance analysis method considering recurrence plot(RP)and cross recurrence plot(CRP).Firstly,we give a detailed interpretation on the recurrence patterns of LSPs via a qualitative 2-D RP representation and its quantitative measure.It can potentially enable the accurate and fast lightpath failure detection with a low computational burden.On the other hand,CRP is devoted to modeling the relationships between lightpath QoT and LSPs,and the correlation degree is determined by a geometric mean of multiple indexes of cross recurrence quantification analysis.From the view of application,such CRP analysis can provide the effective knowledge sharing to guarantee more credible QoT prediction.Extensive experiments on a real-world optical network dataset have clearly demonstrated the effectiveness of our proposal.

Design and Implementation of a Network Performance Analysis System for Space Network Emulation Platforms

Emulation platforms are critical for evaluation and verification in the research of networking technologies and protocols for space networks(SN).High fidelity emulating technologies have been extensively studied for SN in earlier work,while little emphasis has been placed on the performance evaluation part.In this paper,the design of a network performance analysis architecture is presented,with which high-speed network traffic can be captured and indexed,and the performance of the emulated SN can be well analyzed and evaluated.This architecture comprises three components,namely capture layer,storage layer and analysis layer.Analytic Hierarchy Process(AHP)and several analysis methods are adopted to evaluate the network performance comprehensively.In the implementation of the proposed architecture,configuration optimization and parallel processing are applied to handle large amount of high-speed network traffic.Finally,experiment results through the analysis system exhibits the effectiveness of the proposed architecture.

Providing Guaranteed Network Performance across Tenants:Advances,Challenges and Opportunities

The varied network performance in the cloud hurts application performance.This increases the tenant’s cost and becomes the key hindrance to cloud adoption.It is because virtual machines(VMs)belonging to one tenant can reside in multiple physical servers and communication interference across tenants occasionally occurs when encountering network congestion.In order to prevent such unpredictability,it is critical for cloud providers to offer the guaranteed network performance at tenant level.Such a critical issue has drawn increasing attention in both academia and industry.Many elaborate mechanisms are proposed to provide guaranteed network performance,such as guaranteed bandwidth or bounded message delay across tenants.However,due to the intrinsic complexities and limited capabilities of commodity hardware,the deployment of these mechanisms still faces great challenges in current cloud datacenters.Moreover,with the rapid development of new technologies,there are new opportunities to improve the performance of existing works,but these possibilities are not under full discussion yet.Therefore,in this paper,we survey the latest development of the network performance guarantee approaches and summarize them based on their features.Then,we explore and discuss the possibilities of using emerging technologies as knobs to upgrade the performance or overcome the inherent shortcomings of existing advances.We hope this article will help readers quickly Received:Apr.07,2020 Revised:Oct.23,2020 Editor:Haifeng Zheng understand the causes of the problems and serve as a guide to motivate researchers to develop innovative algorithms and frameworks.

Design of Intelligent Network Performance Analysis & Forecast Support System

A system designed for supporting the network performance analysis and forecast effort is presented, based on the combination of offline network analysis and online real-time performance forecast. The off-line analysis will perform analysis of specific network node performance, correlation analysis of relative network nodes performance and evolutionary mathematical modeling of long-term network performance measurements. The online real-time network performance forecast will be based on one so-called hybrid prediction modeling approach for short-term network, performance prediction and trend analysis. Based on the module design, the system proposed has good intelligence, scalability and self-adaptability, which will offer highly effective network performance analysis and forecast tools for network managers, and is one ideal support platform for network performance analysis and forecast effort.

Roles and Functions of Tourism Destinations in Tourism Region of South Anhui:A Tourist Flow Network Perspective

Theoretic and practical significance has been highlighted in the research of the roles and functions of destinations,as destinations are restricted by the spatial structure based on tourist flow network from the perspective of relationship.This article conducted an empirical analysis for Tourism Region of South Anhui(TRSA) and revealed the necessity and feasibility of studying the roles and functions of destinations from tourist flow network's perspective.The automorphic equivalence analysis and centrality analysis were used to classify 16 destinations in TRSA into six role types:tourist flow distribution center,hub of tourist flows,passageway destination,common touring destination,attached touring destination,and nearly isolated destination.Some suggestions were given on suitable infrastructure construction and destinations service designs according to their functions in network.This destination role positioning was based on tourist flow network structure in integral and macroscopic way.It provided an important reference for the balanced and harmonious development of all the destinations of TRSA.In addition,this article verified the applicability of social network analysis on tourist flow research in local scale,and expanded this method to destination role and function positioning.

A Spatial-Temporal Network Perspective for the Propagation Dynamics of Air Traffic Delays

Intractable delays occur in air traffic due to the imbalance between ever-increasing air traffic demand and limited airspace capacity.As air traffic is associated with complex air transport systems,delays can be magnified and propagated throughout these systems,resulting in the emergent behavior known as delay propagation.An understanding of delay propagation dynamics is pertinent to modern air traffic management.In this work,we present a complex network perspective of delay propagation dynamics.Specifically,we model air traffic scenarios using spatial–temporal networks with airports as the nodes.To establish the dynamic edges between the nodes,we develop a delay propagation method and apply it to a given set of air traffic schedules.Based on the constructed spatial-temporal networks,we suggest three metrics-magnitude,severity,and speed-to gauge delay propagation dynamics.To validate the effectiveness of the proposed method,we carry out case studies on domestic flights in the Southeastern Asia region(SAR)and the United States.Experiments demonstrate that the propagation magnitude in terms of the number of flights affected by delay propagation and the amount of propagated delays for the US traffic are respectively five and ten times those of the SAR.Experiments further reveal that the propagation speed for US traffic is eight times faster than that of the SAR.The delay propagation dynamics reveal that about six hub airports in the SAR have significant propagated delays,while the situation in the United States is considerably worse,with a corresponding number of around 16.This work provides a potent tool for tracing the evolution of air traffic delays.

A Study on Priority Based ZigBee Network Performance Analysis with Tree Routing Method

The Wireless Sensor Network (WSN) is spatially distributed autonomous sensor to sense special task. WSN like ZigBee network forms simple interconnecting, low power, and low processing capability wireless devices. The ZigBee devices facilitate numerous applications such as pervasive computing, security monitoring and control. ZigBee end devices collect sensing data and send them to ZigBee Coordinator. The Coordinator processes end device requests. The effect of a large number of random unsynchronized requests may degrade the overall network performance. An effective technique is particularly needed for synchronizing available node’s request processing to design a reliable ZigBee network. In this paper, region based priority mechanism is implemented to synchronize request with Tree Routing Method. Riverbed is used to simulate and analyze overall ZigBee network performance. The results show that the performance of the overall priority based ZigBee network model is better than without a priority based model. This research paves the way for further designing and modeling a large scale ZigBee network.

Complex Networks: Traffic Dynamics, Network Performance, and Network Structure

This paper explores traffic dynamics and performance of complex networks. Complex networks of various structures are studied. We use node betweenness centrality, network polarization, and average path length to capture the structural characteristics of a network. Network throughput, delay, and packet loss are used as network performance measures. We investigate how internal traffic, through put, delay, and packet loss change as a function of packet generation rate, network structure, queue type, and queuing discipline through simulation. Three network states are classified. Further, our work reveals that the parameters chosen to reflect network structure, including node betweenness centrality, network polarization, and average path length, play important roles in different states of the underlying networks.

Packing induced bistable phenomenon in granular flow:analysis from complex network perspective

The effects of packing configurations on the phase transition of straight granular chute flow with two bottlenecks axe studied. The granular flow shows a dilute- to-dense flow transition when the channel width is varied, accompanied with a peculiar bistable phenomenon. The bistable phenomenon is induced by the initial packing config- uration of particles. When the packing is dense, the initial flux is small and will induce a dense flow. When the packing is loose, the initial flux is large and will induce a di- lute flow. The fabric network of granulax packing is analyzed from a complex network perspective. The degree distribution shows quantitatively different characteristics for the configurations. A two-dimensional （2D） packing clustering coefficient is defined to better quantify the fabric network.

Complex network perspective on modelling chaotic systems via machine learning

Recent advances have demonstrated that a machine learning technique known as "reservoir computing" is a significantly effective method for modelling chaotic systems. Going beyond short-term prediction, we show that long-term behaviors of an observed chaotic system are also preserved in the trained reservoir system by virtue of network measurements. Specifically, we find that a broad range of network statistics induced from the trained reservoir system is nearly identical with that of a learned chaotic system of interest. Moreover, we show that network measurements of the trained reservoir system are sensitive to distinct dynamics and can in turn detect the dynamical transitions in complex systems. Our findings further support that rather than dynamical equations, reservoir computing approach in fact provides an alternative way for modelling chaotic systems.

Artificial Neural Network Performing the Forward Operation of Color Appearance Model

A method of the forward operation of color appearance (from colorimetric attributes to color appearance attributes) using an artificial neural network (ANN) is presented The neural network model developed is a multilayer feedforward neural network model for predicting color appearance model (CAM). This method greatly decreased the mathematical computation in color appearance prediction. The error backed-propagation (BP) algorithm was applied in the training of the neural networks, and it was trained and tested by the LUTCHI color appearance datasets which are the most comprehensive one in testing color appearance model. CRT was selected as a typical example in experiment because it is usually used as self-luminous object in fact, and several ways for choosing training samples were included and compared each other. The testing results show that the color appearance prediction using artificial neural network is well consistent with visual evaluation.

Getting the Balance Right in Intercultural Groups: A Dynamic Social Network Perspective

Problem: A common assumption is that students prefer to select their friends for group-work. The prime goal of this study was to understand the impact of two group selection methods on how students from diverse cultural backgrounds build learning and work relations. Method: Social Network Analysis in a pre-post test manner in a quasi-experimental design of 81 vs. 70 third-year students. Solution: In this study, we “disrupted” this group selection process after Day 1 by balancing students from different parts of the social network together. In one condition the students were “balanced” into groups by staff to encourage structural hole formation, and in the other condition students were allowed to self-select their group members to encourage network closure. Results: Students in the self-selected condition primarily selected their friends from a similar cultural background. In both conditions the learning networks after 11 weeks were primarily predicted by the group allocation and initial friendships. However, students in the balanced condition developed more cross-cultural learning links. These results indicate that teachers can actively intervene in the cross-cultural dynamics in- and outside the classroom.

Neural Network Performance for Complex Minimization Problem

We have analyzed the important problem of contemporary high-energy physics concerning the estimation of some parameters of the observed complex phenomenon. The standard statistical method of the data analysis and minimization was confronted with the Neural Network approaches. For the Natural Neural Networks we have used brains of high school students involved in our Roland Maze Project. The excitement of active participation in real scientific work produced their astonishing performance what is described in the present work. Some preliminary results are given and discussed.

Evaluation of Broadband Network Performance in Nigeria

Broadband provides high speed data transmission to Internet and 4G networks were developed to transform broadband technology with higher data rate and enhanced quality of service. The performance of broadband network in Nigeria in terms of type, purpose and speed was evaluated in this work. Some quarters at Ilesa and Oba-Ile in Akure were chosen as rural areas, while Abuja and Lagos represented the urban areas of the study. Questionnaires were administered among users in these areas randomly. Thereafter, data were analyzed and research questions answered from the analyzed results. The results showed that the majority of the respondents operated on wireless broadband technologies. The download speed is generally above 100 mbps in urban areas and below in rural areas, with MTN having the highest number of subscribers. In addition, most of the Internet surfers download files. With these characteristics, it was discovered that the network operators were deploying 3G systems as broadband instead of 4G systems.

Practical Routing Protocol Models to Improve Network Performance and Adequacy

The telecommunications network has become an essential facility of our daily life, which is the reason why a good number of the recent researches are directed to it. In this paper, the performance of routing protocols for selected network and the optimum way of utilizing the network resources is proposed, through improving the routing method protocols to obtain the most accurate communication models, which give the best network performance, taking into consideration that the protocol time interval to recalculate the future routing step is agreed to be our performance criteria, which is then used to determine the total amount of incoming traffic normalized at the best network performance with respect to the network capacity as well. Moreover, adaptive routing evaluation methods have been mathematically investigated in this work for telecommunication networks (TN), more precisely, developing the infrared radiation (IR) routing methods for hybrid TN applications, in terms of implementation conditions at a certain guaranteed quality of service, where we give a particular interest in analyzing routing methods based on the fact that the distribution information is contained in the routing variables, rather than in the state variables. The protocol that deals with the unbalanced traffic distribution over TN nodes has been investigated in this paper as well, and simulation results show good progress in the proposed protocol over the traditional protocols.

《Storage Network Performance Analysis》

《Storage Network Performance Analysis》一书作者Huseyin Simitci博士，是XIOtech公司的工程研究人员，致力于高性能输入、输出系统和并行文件系统自适应技术的研究．并在这些领域发表有研究论文。本书是一本深入指导分析和改进网络存储性能的书籍。

Observing Network Performance and Congestion on Managing Assets with RFID and Cloud Computing

Today, we observe that more and more, radio frequency identification (RFID) technology has been used to identify and track objects in enterprises and institutions. In addition, we also perceive the growing adoption of cloud computing, either public or private, to process and store data from the objects. In this context, the literature does not present an initiative that looks into the network on enterprise-cloud interactions, so neglecting network performance and congestion information when transmitting data to the cloud. Thus, we are presenting a model named ACMA—Automatic Control and Management of Assets. ACMA employs context awareness to control and monitor corporate assets in companies with multiple units. ACMA provides a centralized point of access in the cloud in which interested actors can get online data about each corporate asset. In particular, our scientific contribution consists in considering network congestion to control dynamically the data updating interval from sensors to the cloud. The idea is to search for reliability and integrity of operations, without losing or corrupting data when updating the information to cloud. Thus, this article describes the ACMA model, its architecture, algorithms and features. In addition, we describe the evaluation methodology and the results obtained through experiments and simulations based on the developed prototype.

A Study on the Evolution of Labor Self-Organizations and the Design of Governmental Mechanism from A Complex Network Perspective

Self-organization theory informs an analysis on the evolution of labor self-organizations (LSOs), but lacks technical analysis on the evolution of their organizational structures. Fortunately, complex network technology offers a new approach to analyzing these structures. Built on an extension of the Barabási-Albert (BA) model, we can simulate the evolution of LSOs by analyzing indicators including the clustering coefficient, degree distribution (DD) and average path length (APL) of workers, thereby demonstrating the evolving patterns of LSOs. Accordingly, governmental mechanism designs based on such patterns may not only stimulate energy growth and functional realization of LSOs, but also reduce the social percussions of abrupt evolutions. A comparative analysis of the evolutionary trajectories of LSOs in China and the U.S. finds that the U.S. government’s mechanism designs for protecting capitalism not only prevented the effective gathering of workers, but also prolonged the history of industrial conflicts. Such mechanism designs also led to the early dispersion and decline of LSOs and hindered the evolution of the working class. In contrast, the Chinese government established a socialist system that allowed workers to become the underlying force of socialist productivity. This design reduced labor strife while accelerating the evolution of workers towards higher stages.

A Cross-System Invocation Platform Based on Distributed Network Performance Measurement System

The Distributed Network Performance Measurement Sys-tem provides functions to derive performance indices of networks and services, which are significant for Network Management System. To make these two systems cooperate, we realize this cross-system invocation platform, using Web Service, a mechanism which allows two systems to exchange data over the internet through publishing interfaces [1]. There are several mature Web Service frameworks, Apache Axis2, Apache CXF etc. In this paper we choose Apache Axis2 to achieve the objective that the Network Management System can invocate the net-work performance measurement functions via the Web Services.