A game theoretic approach to balancing energy consumption in heterogeneous wireless sensor networks

Energy balancing is an effective technique in enhancing the lifetime of a wireless sensor network (WSN). Specifically, balancing the energy consumption among sensors can prevent losing some critical sensors prematurely due to energy exhaustion so that the WSN's coverage can be maintained. However, the heterogeneous hostile operating conditions—different transmission distances, varying fading environments, and distinct residual energy levels—have made energy balancing a highly challenging task. A key issue in energy balancing is to maintain a certain level of energy fairness in the whole WSN. To achieve energy fairness, the transmission load should be allocated among sensors such that, regardless of a sensor's working conditions, no sensor node should be unfairly overburdened. In this paper, we model the transmission load assignment in WSN as a game. With our novel utility function that can capture realistic sensors’ behaviors, we have derived the Nash equilibrium (NE) of the energy balancing game. Most importantly, under the NE, while each sensor can maximize its own payoff, the global objective of energy balancing can also be achieved. Moreover, by incorporating a penalty mechanism, the delivery rate and delay constraints imposed by the WSN application can be satisfied. Through extensive simulations, our game theoretic approach is shown to be effective in that adequate energy balancing is achieved and, consequently, network lifetime is significantly enhanced. Copyright © 2012 John Wiley & Sons, Ltd.     

一种快速全局优化的神经网络及其在数据融合中的应用

本文将遗传算法的全局性和EM算法的快速性相结合,提出了一种快速全局优化神经网络,并将其应用于数据融合中。理论与实验结果表明该算法在数据融合中具有很强的鲁棒性。     

传输网ECC组网及DCN网络优化

如何通过更多有效的手段来保证网络的安全稳定运行、降低运营成本,已经成为目前各运营商共同关注的课题。传输网络的管理、监视、控制是网络维持安全稳定运行的重要保障,本文通过对网络管理的网元数量、子网划分、网关网元及DCN网络设置等进行分析,采取重新划分子网、提供网络通信保护路由、DCN网络优化等方式,以保障网络通信的畅通。     

An integrated e-supply chain model for agile and environmentallyconscious manufacturing

This paper presents a mathematically sound model for the design and optimization of supply chains in terms of such important performance indexes as product cost, cycle time, quality, energy and environmental impact in the context of global and Internet-based manufacturing. The two layer model is a hyper-network of material flows overlaid with an e-business information network. It extends from a traditional supply chain having suppliers, distributors, and users to include end-of-life product collectors and de-manufacturers. Furthermore, it extends the performance considerations from cost and productivity to include environmental performance. Such extensions allow one to develop Internet-based manufacturing systems that are agile and can produce desired products with the minimum environmental impact over their life cycles. Fuzzy logic-based optimization goals are used in the proposed multiobjective optimization model. A personal computer containing such mechatronic components as hard disk driver, keyboard, and mouse is used as an example to illustrate the application of the proposed integrated e-supply chain model     

MSBR法污水处理模糊神经网络控制的研究

模糊神经网络(FNN)技术的迅速发展及其理论的不断完善为其在各个领域的应用奠定了基础。简述了FNN技术的发展以及在污水处理过程中的应用现状和重要性,详述了模糊神经网络控制在MSBR法污水处理中的应用,提出了一个具有5层的模糊神经网络控制器,通过仿真实验表明该控制系统具有很强的鲁棒性与容错性,该控制器能够自动调整隶属度函数、动态优化控制规则,将其应用于溶解氧控制和出水水质预测,结果表明可以快速、有效地使溶解氧浓度达到期望值,实际出水水质预测结果也具有很好的收敛性和预测精度。     

Relaying strategy for peer-to-peer content distribution based on genetic algorithm

This article proposes a cooperative relaying strategy to efficiently utilize the relaying resources of Internet service providers (ISPs), speedup distribution and save server bandwidth costs. ISPs cooperatively relay for each other, and peers assist in distributing and fetching the content as near as possible. Base on the fluid model, a constrained model is derived to get optimized global distribution performance in the channel-based system with limited relaying resources. The multi-objectives of the model are minimizing the average distribution time and the distribution time of the slowest channel. Genetic algorithm (GA) is designed to solve the optimization problem. The relaying strategy based on GA can be run periodically to update the allocation policy of ISPs. The distribution performance of the relaying strategy is analyzed in the experiments and results show that GA can provide proper solutions for various network topologies.     

Intelligent and Reliable Photonic Cross-Connect System Based on Overlay Model

We developed a carrier-based photonic cross-connect (PXC) system based on an optical switch, which provides wavelength-division-multiplexing transmission, generalized multiprotocol label switching, and optical-transport-network management. This system uses an overlay model in which the administrative authority between the client-network-element (NE) layer and the carrier's PXC layer is completely separated. The PXC system provides user-network interface signaling between the client NEs and the PXCs, which enables automatic optical path setting between the two client NEs through a PXC network. We considered new protection schemes for the PXC system and successfully carried out an experiment in a testbed network using one of the discussed schemes. The new concept of policy control in the control-plane management is introduced, and the feasibility of our PXC system is demonstrated. This system is promising as a prototype for a next-generation optical transport system. Furthermore, the PXC system will enable the creation of a new type of optical transport layer service, accommodate increased Internet traffic demand, and reduce network operation loads and costs for Internet service providers and carriers in the near future.     

Denoising image by matrix factorization in U-shaped convolutional neural network

Image denoising requires both spatial details and global contextualized information to recover a clean version from the deteriorative one. Previous deep convolution networks usually focus on modeling the local feature and stacked convolution blocks to expand the receptive field, which can catch the long-distance dependencies. However, contrary to the expectation, the extracted local feature incapacity recovers the global details by traditional convolution while the stacked blocks hinder the information flow. To tackle these issues, we introduce the Matrix Factorization Denoising Module (MD) to model the interrelationship between the global context aggregating process and the reconstructed process to attain the context details. Besides, we redesign a new basic block to ease the information flow and maintain the network performance. In addition, we conceive the Feature Fusion Module (FFU) to fuse the information from the different sources. Inspired by the multi-stage progressive restoration architecture, we adopt two-stage convolution branches progressively reconstructing the denoised image. In this paper, we propose an original and efficient neural convolution network dubbed MFU. Experimental results on various image denoising datasets: SIDD, DND, and synthetic Gaussian noise datasets show that our MFU can produce comparable visual quality and accuracy results with state-of-the-art methods.     

光分插复用网元节点的设计和实验研究

提出了一种用于光传送网（OTN）的光分插复用（OADM）网元（NE）节点的体系结构，采用模块化方法，划分并设计出各功能模块。研制出可以同时支持8个波长动态分插复用的可重构OADM NE节点，提供2个双向全光网接口和网络管理接口。     

Distributed control of performance management traffic with accuracy objectives

One of the important functions of a network management system (NMS) is performance management (PM). PM deals with collecting statistical information to track the effectiveness and utilization of the network and network elements (NE). While this may be done offline, it is often necessary to monitor the network statistics online in real time. The aim of real‐time monitoring is to achieve high accuracy of the statistics while minimizing the use of scarce network bandwidth. The accuracy objective can vary depending on the priority and dynamic severity state of the NE. We define cost, which needs to be optimized, as a function of network traffic and achieved accuracy. Based on the cost, a comparison of push and pull data collection alternatives is done. We have developed a push‐based distributed data collection system that tunes the accuracy objectives, based on the network traffic and the dynamic severity state of the NE. Copyright © 2009 John Wiley & Sons, Ltd.     

3G核心网技术路线选择

本文概要介绍了3G全球发展情况,并重点分析GSM＆GPRS传统架构、移动软交换以及基于IMS的全IP架构的技术、产品特点,产品应用状况,为3G核心网络技术路线选择提供参考.     

IDES: An Internet Distance Estimation Service for Large Networks

The responsiveness of networked applications is limited by communications delays, making network distance an important parameter in optimizing the choice of communications peers. Since accurate global snapshots are difficult and expensive to gather and maintain, it is desirable to use sampling techniques in the Internet to predict unknown network distances from a set of partially observed measurements. This paper makes three contributions. First, we present a model for representing and predicting distances in large-scale networks by matrix factorization which can model suboptimal and asymmetric routing policies, an improvement on previous approaches. Second, we describe two algorithms-singular value decomposition and non-negative matrix factorization-for representing a matrix of network distances as the product of two smaller matrices. Third, based on our model and algorithms, we have designed and implemented a scalable system-Internet Distance Estimation Service (IDES)-that predicts large numbers of network distances from limited samples of Internet measurements. Extensive simulations on real-world data sets show that IDES leads to more accurate, efficient and robust predictions of latencies in large-scale networks than existing approaches     

Robust Neural-Network-Based Data Association and Multiple Model-Based Tracking of Multiple Point Targets

Data association and model selection are important factors for tracking multiple targets in a dense clutter environment without using a priori information about the target dynamic. We propose a neural-network-based tracking algorithm, incorporating a interacting multiple model and show that it is possible to track both maneuvering and nonmaneuvering targets simultaneously in the presence of dense clutter. Moreover, it can be used for real-time application. The proposed method overcomes the problem of data association by using the method of expectation maximization and Hopfield network to evaluate assignment weights. All validated observations are used to update the target state. In the proposed approach, a probability density function (pdf) of an observed data, given target state and observation association, is treated as a mixture pdf. This allows to combine the likelihood of an observation due to each model, and the association process is defined to incorporate an interacting multiple model, and consequently, it is possible to track any arbitrary trajectory     

基于NX主模型的模具并行设计在PDM中的实现

NX主模型是在产品生命周期中,协调全局,指导并保证数据共享和数据全局一致性的统一的数字化几何模型。在产品数据管理中,主模型是以基于产品数据管理为核心的一个中央数据库文件。利用NX软件主模型设计原理,以三维模型为单一数据源,实现产品数据管理系统(PDM)下的产品并行研发,能有效提高模具设计的效率和质量。文章探讨了PDM系统中利用主模型进行并行设计的原理和实现方法,最后以具体设计实例验证了方法的有效性。     

Layer 1 virtual private network management by users

The layer 1 virtual private network (LlVPN) technology supports multiple user networks over a common carrier transport network. Emerging L1VPN services allow: L1VPNs to be built over multiple carrier networks; L1VPNs to lease or trade resources with each other; and users to reconfigure an L1VPN topology, and add or remove bandwidth. The trend is to offer increased flexibility and provide management functions as close to users as possible, while maintaining proper resource access right control. In this article two aspects of the L1VPN service and management architectures are discussed: management of carrier network partitions for L1VPNs, and L1VPN management by users. We present the carrier network partitioning at the network element (NE) and L1VPN levels. As an example, a transaction language one (TL1) proxy is developed to achieve carrier network partitioning at the NE level. The TL1 proxy is implemented without any modifications to the existing NE management system. On top of the TL1 proxy, a Web services (WS)-based L1VPN management tool is implemented. Carriers use the tool to partition resources at the L1VPN level by assigning resources, together with the WS-based management services for the resources, to L1VPNs. L1VPN administrators use the tool to receive resource partitions from multiple carriers and partner L1VPNs. Further resource partitioning or regrouping can be conducted on the received resources, and leasing or trading resources with partner LlVPNs is supported. These services offer a potential business model for a physical network broker. After the L1VPN administrators compose the use scenarios of resources, and make the use scenarios available to the L1VPN end users as WS, the end users reconfigure the L1VPN without intervention from the administrator. The tool accomplishes LlVPN management by users     

PTN技术在全球运营网中的典型应用案例分析

目前,分组传送网(PTN)技术在全球已经大规模地部署和建设,针对PTN这一全新技术和设备,在开始的规模部署期内,必然会面临许多新问题和新挑战,本文深入分析了PTN技术在全球运营网中的典型应用和部署方案,并分析了方案的优势和劣势,为国内各电信运营商部署PTN技术提供参考。     

无线传感器网络中支持并行传输的信道与功率联合优化博弈算法

针对无线传感器网络中干扰日益增大引起网络容量下降、能耗增加的问题,该文建立了信道分配与功率控制联合优化博弈模型。在该模型中链路将既能保持自身成功传输又不影响其它链路传输的信道作为可选信道,以实现链路的并行传输。继而基于该模型设计了一种支持并行传输的信道分配与功率控制联合优化博弈算法(JCPGC)。该算法利用最佳响应策略对模型求解,并通过超模博弈等理论证明了JCPGC能够收敛到纳什均衡。此外,该算法充分考虑信道分配和功率控制之间独立又相互影响的关系提高了网络容量。仿真实验结果表明,JCPGC具有大容量、低干扰和低能耗的特性。     

综合网络管理系统中抽象网元模型的设计与应用

综合网络管理是网管领域的一个重要研究课题,设计合理的网元模型是实现综合网管的基础。为了解决多技术、多设备制造商环境中网元模型难以准确有效描述实际网元的问题,该丈根据实际网络中设备的使用情况,遵循软件设计原则,提出了一种抽象网元模型。该模型充分考虑网络环境变化可能给网管系统造成的影响,对TMF网管系统中的网元模型进行改进和扩展,希望通过合理利用Java语言中面向对象的抽象,继承及接口实现等技术,并结合工厂方法模式、缺省适配模式以及模板方法模式,有效增加网管系统的适应性,灵活性,提高网管软件代码的复用性和可维护性。     

An Integrated Approach to Sensor Role Selection

Many sensor network applications require consistent coverage of the region in which they are deployed over the course of the network lifetime. However, because sensor networks may be deployed randomly, node distribution and data redundancy in some regions of the network may be lower than in others. The sensors in the sparsest regions should be considered more critical to the sensor network application since their removal would likely result in unmonitored regions in the environment. For this reason, sensors in the more densely deployed regions should be considered more favorable as candidates to route the traffic of other nodes in the network. In this work, we propose several coverage-aware routing costs that allow traffic to be routed around the sparsely deployed regions so that the coverage of the environment can remain high for a long lifetime. We also propose an integrated route discovery and sensor selection protocol called DAPR that further lengthens network lifetime by jointly selecting routers and active sensors, again with the goal of minimizing the use of sensors in sparsely covered areas. Simulation results show the effectiveness of our approach in extending network lifetime nearly to the extent that can be reached using a centralized approach based on global network knowledge.