基于动态调整节点包发送速率的基站保护策略

无线传感器网络中,为了抵御全局流量监测的攻击者,提出了一种基于节点包发送速率动态调整的基站位置隐私保护策略SRA。SRA通过调整全网节点的发包率,实现源节点到基站的流量隐藏,继而能够有效抵御全局流量分析的攻击者。理论表明,SRA能够有抵御全局流量的攻击者对基站的定位。更进一步地,提出了基于贪心选择路径的基站位置隐私保护策略GCR,进一步降低网络通信开销。实验表明,与SRA相比,GCR能够有效保护基站的位置隐私且具有较低的通信开销。     

面向水环境监测的无线传感器网络数据视频基站设计

基于无线传感器网络的水环境监测系统包括数据监测节点、数据视频基站、远程监测中心等三部分,可对水温、pH值、浊度、电导率、溶解氧等水环境参数和重点区域的视频信息进行感知、采集、处理和传输,进而实现对水库、湿地、湖泊、江河、海洋等大范围水域的监测。数据视频基站在监测网络中充当数据监测节点和CDMA网络之间的网关,是整个系统的通信枢纽。本文研究了一种基于ARM-DSP双处理器架构的数据视频基站,并阐述了其硬件系统和软件系统设计。该基站采用ZigBee和CDMA无线传输技术,实现了基站与传感器网络、基站与远程监测中心的双向高效通信,满足了水环境远程实时监测系统的要求,在工业控制、智能家居、医疗监护、智能交通等领域亦具有广阔的应用前景。     

无线4G管网监测系统在新疆某工程中的应用

为了解决长距离供水管道运行状况及企业用水量巡查困难、实现对长距离供水管道运行状况及企业用水量实时监测,设计了以微功耗遥测终端、流量计、压力传感器作为现地控制单元,以操作员站、服务器、工程师站等作为信息管理及中央控制层的无线4G管网监测系统。该监测系统通过4G网络技术连接现地控制单元和中央控制层,实现了对管网的压力、流量、企业用水量的实时监测。介绍了系统组成、系统功能、通信网络、电源。实际应用表明,该系统在实现管网监测过程中的可靠性、准确性。该系统充分发挥了微功耗终端、4G网络的优势,使供水管网监测更经济、可靠、简单易行,为解决长距离、监测点多且分散的管网监测提供了参考。     

Ellipsoidal neighbourhood outlier factor for distributed anomaly detection in resource constrained networks

Anomaly detection in resource constrained wireless networks is an important challenge for tasks such as intrusion detection, quality assurance and event monitoring applications. The challenge is to detect these interesting events or anomalies in a timely manner, while minimising energy consumption in the network. We propose a distributed anomaly detection architecture, which uses multiple hyperellipsoidal clusters to model the data at each sensor node, and identify global and local anomalies in the network. In particular, a novel anomaly scoring method is proposed to provide a score for each hyperellipsoidal model, based on how remote the ellipsoid is relative to their neighbours. We demonstrate using several synthetic and real datasets that our proposed scheme achieves a higher detection performance with a significant reduction in communication overhead in the network compared to centralised and existing schemes.     

Environmental sensor networks

The developments in wireless network technology and miniaturization makes it possible to realistically monitor the natural environment. Within the field of environmental sensor networks, domain knowledge is an essential fourth component. Before designing and installing any system, it is necessary to understand its physical environment and deployment in detail. Sensor networks are designed to transmit data from an array of sensors to a server data repository. They do not necessarily use a simple one way data stream over a communication network rather elements of the system decide what data to pass on, using local area summaries and filtering to minimize power use while maximizing the information content. The Envisense Glacs Web project is developing a monitoring system for a glacial environment. Monitoring the ice caps and glaciers provides valuable information about the global warming and climate change.     

Diffusion of hurricane evacuation behavior through a home-workplace social network: A spatially explicit agent-based simulation model

With coastal populations experiencing the growing threat of hurricanes as a consequence of global climate change, models for predicting how household evacuation behavior may diffuse over time and space are needed for emergency management. This study models the effects of social influence on household evacuation behavior in anticipation of a hurricane event. An agent-based model was developed in this study to simulate: 1) a home-workplace social network between households residing in the Florida Keys, 2) the communication of a hurricane evacuation order among socially linked households, and 3) the resulting spatio-temporal diffusion of household evacuation behavior. Data sources informing model implementation include U.S. Census block group data, business databases, and statistics from hurricane evacuation surveys. Simulated model results from the model were validated with empirical traffic records observed at a Florida Keys monitoring station during evacuation from Hurricane Georges in 1998. This model builds upon previous research using agent-based models to simulate hurricane evacuation by incorporating multiple data sources and validating results with empirical traffic patterns. Such an empirically-grounded model facilitates locally relevant exploration of evacuation behavior to support the development of more effective evacuation plans and preparedness for future hurricane events.     

Codiagnosability of networked discrete event systems subject to communication delays and intermittent loss of observation

Failure diagnosis is a crucial task in modern industrial systems, and several works in the literature address this problem by modeling the system as a Discrete-Event System (DES). Most of them assume perfect communication between sensors and diagnosers, i.e., no loss of observation of events, or event communication delays between the measurement sites and the diagnosers. However, industrial systems can be large and physically distributed, in which cases, communication networks are used to provide an efficient way to establish communication between devices. In diagnosis systems, the use of networks can introduce delays in the communication of event occurrences from measurement sites to the local diagnosers, leading to an incorrect observation of the order of occurrence of events generated by the system and, as a consequence, to an incorrect diagnosis decision by the local diagnoser. In this paper, we address the problem of decentralized diagnosis of networked Discrete-Event Systems subject to event communication delays, and we introduce the definition of network codiagnosability of the language generated by a DES subject to both event communication delays and intermittent loss of observation, and present necessary and sufficient conditions for a language to be network codiagnosable, for short. We also propose an algorithm to verify this property.     

Estimation of a Population Size in Large-Scale Wireless Sensor Networks

Efficient estimation of population size is a common requirement for many wireless sensor network applications. Examples include counting the number of nodes alive in the network and measuring the scale and shape of physically correlated events. These tasks must be accomplished at extremely low overhead due to the severe resource limitation of sensor nodes, which poses a challenge for large-scale sensor networks. In this article we design a novel measurement technique, FLAKE based on sparse sampling that is generic, in that it is applicable to arbitrary wireless sensor networks (WSN). It can be used to efficiently evaluate system size, scale of event, and other global aggregating or summation information of individual nodes over the whole network in low communication cost. This functionality is useful in many applications, but hard to achieve when each node has only a limited, local knowledge of the network. Therefore, FLAKE is composed of two main components to solve this problem. One is the Injected Random Data Dissemination (Sampling) method, the other is sparse sampling algorithm based on Inverse Sampling, upon which it improves by achieving a target variance with small error and low communication cost. FLAKE uses approximately uniform random data dissemination and sparse sampling in sensor networks, which is an unstructured and localized method. At last we provide experimental results demonstrating the effectiveness of our algorithm on both small-scale and large-scale WSNs. Our measurement technique appears to be the practical and appropriate choice.     

一种网络事件分布式并行检测机制

如何有效地检测网络事件是大规模网络管理面对的一个挑战．本文在对网络事件进行定义和分类的基础上，提出了一种网络事件的分布式并行检测方法，有效地提高了事件检测的及时性和准确性。     

基于数据流管理平台的网络安全事件监控系统

复杂而繁多的网络攻击要求监控系统能够在高速网络流量下实时检测发现各种安全事件．数据流管理系统是一种对高速、大流量数据的查询请求进行实时响应的流数据库模型．本文提出了一种将数据流技术应用到网络安全事件监控中的框架模型．在这个模型中，数据流管理平台有效地支持了对高速网络数据流的实时查询与分析，从而保证基于其上的网络安全事件监控系统能够达到较高的处理性能．利用CQL作为接口语言，精确描述安全事件规则与各种监拉查询，具有很强的灵活性与完整性．另外，系统能够整合入侵检测、蠕虫发现、网络交通流量管理等多种监控功能，具有良好的可扩展性，     

基于双层复杂网络的城市交通网络协同优化方法

针对城市交通网络中旅客在公共交通出行路径选择时面临的地铁与公交双层网络在换乘衔接协同中存在的部分换乘站点之间距离过远、衔接导向不明确、局部换乘供需不平衡等问题，提出基于双层复杂网络的城市交通网络协同优化方法。首先，采用逻辑网络拓扑方法对城市交通网络进行拓扑，并基于复杂网络理论建立地铁-公交双层网络模型。然后，以换乘车站为研究对象，提出一种基于K-shell分解法和中心性权重分配的节点重要度评价方法，对大规模网络中的地铁、公交车站进行粗粒度和细粒度划分和识别，并在此基础上提出一种相互激励的双层城市交通网络协同优化方法，即在双层网络结构优化中引入复杂网络理论中对于网络拓扑中节点重要度的识别和筛选方法，通过对路径选择中高集聚效应的识别和有利节点的定位更新双层网络结构以优化现有网络的车站布局和衔接关系。最后，将提出的方法应用于成都市地铁-公交网络，优化了现有网络结构，得到了现有网络的最佳优化节点位置和优化数量，并且通过相关指标系统验证了该方法的有效性。实验结果表明，采用该方法优化32次后的网络全局效率达到最优，和平均最短路径的优化效果分别为15.89%、16.97%，旅客换乘行为提升57.44个百分点；优化方法对旅行成本在8000~12000 m的可达性影响最明显，优化效果平均达到23.44%；同时引入双层网络速度比和单位交通成本比，突出了不同运营状况下交通网络对协同优化过程的反应和敏感度的不同。     

Real-time network monitoring scheme based on SNMP for dynamic information

An efficient and automated network management is required in large and complex networks since it is very difficult to manage them only with human effort. In response to this need, the Simple Network Management Protocol (SNMP) has been developed and adopted as the de facto standard. Some management information changes with time and the management station needs to monitor its value in real time. In such a case, polling is generally used in the SNMP because the management station can query agents periodically. However, the polling scheme needs both request and response messages for management information every time, which results in network traffic increase. In this paper, we suggest a real-time network monitoring method for dynamic information to reduce the network traffic in SNMP-based network management. In the proposed strategy, each agent first decides its own monitoring period. Then, the manager collects them and approves each agent's period without modification or adjusts it based on the total traffic generated by monitoring messages. After receiving a response message containing the monitoring period from the management station, each agent sends management information periodically without the request of management station. To evaluate the performance of the proposed real-time monitoring method, we implemented it and compared the network traffic and monitoring quality of the proposed scheme with the general polling method.     

A hybrid monitor for behavior and performance analysis ofdistributed systems

The authors describe a hybrid monitor for measuring the performance and observing the behavior of distributed systems during execution. They emphasize data collection, analysis and presentation of execution data. A special hardware support, which consists of a test and measurement processor (TMP), was designed and has been implemented in the nodes of experimental multicomputer system consisting of eleven nodes. The operations of the TMP are completely transparent with a minimal, less than 0.1%, overhead to the measured system. In the experimental system, all the TMPs were connected with a central monitoring station, using an independent communication network, in order to provide a global view of the monitored system. The central monitoring station displayed the resulting information in easy-to-read charts and graphs. Experience with the TMP shows that it promotes an improved understanding of run-time behavior and performance measurements, which aids in deriving qualitative and quantitative assessments of distributed systems     

Rule-based inference and decomposition for distributed in-network processing in wireless sensor networks

Wireless sensor networks are application specific and necessitate the development of specific network and information processing architectures that can meet the requirements of the applications involved. A common type of application for wireless sensor networks is the event-driven reactive application, which requires reactive actions to be taken in response to events. In such applications, the interest is in the higher-level information described by complex event patterns, not in the raw sensory data of individual nodes. Although the central processing of information produces the most accurate results, it is not an energy-efficient method because it requires a continuous flow of raw sensor readings over the network. As communication operations are the most expensive in terms of energy usage, the distributed processing of information is indispensable for viable deployments of applications in wireless sensor networks. This method not only helps in reducing the total amount of packets transmitted in the network and the total energy consumed by the sensor nodes, but also produces scalable and fault-tolerant networks. For this purpose, we present two schemes that distribute information processing to appropriate nodes in the network. These schemes use reactive rules, which express relations between event patterns and actions, in order to capture reactive behavior. We also share the results of the performance of our algorithms and the simulations based on our approach that show the success of our methods in decreasing network traffic while still realizing the desired functionality.     

基于密集卷积神经网络的遥感飞机识别

传统的飞机识别方法受模糊、遮挡、噪声以及光照等多种因素的干扰时会降低识别率,且卷积神经网络主要依赖局部特征,却丢失了轮廓特征等重要的全局结构化特征,从而导致算法对于受干扰飞机图像识别效果不佳。因此,基于密集卷积神经网络提出一种结合局部与全局特征的联合监督识别方法,以密集卷积神经网络为基础得到图像特征,通过结合局部特征（卷积神经网络特征）与全局特征（方向梯度直方图特征）进行分类,分类器目标函数使用softmax损失和中心损失联合监督方法。实验结果表明,局部特征与全局特征的结合使算法更加智能化,且损失函数联合监督方法能够实现图像深层特征的类内聚合、类间分散,该算法能有效解决卷积神经网络对受到多种干扰的遥感图像识别率低的问题。     

Sensor Deployment and Relocation: A Unified Scheme

Sensor networks are envisioned to revolutionize our daily life by ubiquitously monitoring our environment and/or adjusting it to suit our needs. Recent progress in robotics and low-power embedded systems has made it possible to add mobility to small, light, low-cost sensors to be used in teams or swarms. Augmenting static sensor networks with mobile nodes addresses many design challenges that exist in traditional static sensor networks. This paper addresses the problem of topology control in mobile wireless networks. Limitations in communication, computation and energy capabilities push towards the adoption of distributed, energy-efficient solutions to perform self-deployment and relocation of the nodes. We develop a unified, distributed algorithm that has the following features. During deployment, our algorithm yields a regular tessellation of the geographical area with a given node density, called monitoring configuration. Upon the occurrence of a physical phenomenon, network nodes relocate themselves so as to properly sample and control the event, while maintaining the network connectivity. Then, as soon as the event ends, all nodes return to the monitoring configuration. To achieve these goals, we use a virtual force-based strategy which proves to be very effective even when compared to an optimal centralized solution. We assess the performance of our approach in the presence of events with different shapes, and we investigate the transient behavior of our algorithm. This allows us to evaluate the effectiveness and the response time of the proposed solution under various environmental conditions.     

A general framework for deterministic service guarantees intelecommunication networks with variable length packets

By extending the recently developed filtering theory under the min-plus algebra to the max-plus algebra, we develop a general framework for providing deterministic quality-of-service guarantees in telecommunication networks with variable length packets. The traffic in such networks is modeled by marked point processes that consist of two sequences of variables: the arrival times and the packet lengths. By modifying Cruz's characterization for a counting process, we propose a traffic characterization, called g-regularity, to characterize a marked point process. Based on the traffic characterization, we introduce two basic network elements: traffic regulators that generate g-regular marked point processes; and g-servers that provides quality-of-service for marked point processes. As in the filtering theory under the min-plus algebra, network elements can be joined by concatenation, “filter bank summation”, and feedback to form a composite network element. We illustrate the use of the framework by various examples that include G/G/1 queues, VirtualClock, guaranteed rate servers in tandem, segmentation and reassembly, jitter control, dampers, and window flow control     

基于最佳候选的蜂窝网络低能耗基站部署算法

无线异构蜂窝网络中微基站的过度增加会导致能量效率的降低。针对基站部署中的绿色通信问题,提出了一种基于最佳候选的低能耗基站部署算法。首先,设计了最佳候选点选择策略来选择一组基站候选点集合,然后再利用贪婪算法选择可以使得网络能量效率达到最大值的微基站,该方法限制了用户分布对基站部署的影响。仿真实验结果表明,在多种负载情况下,提出方法在满足网络容量的同时不仅增加了能量效率还增加了网络总流量,中负载能量效率提高了36%。     

An experimental evaluation of a peer-model monitoring system for the support of a parallel processing environment

The process of monitoring the machines or computing nodes in a network, and of monitoring the communication traffic between them, is very important to efficiently launch and execute parallel coarse-grained applications or even classical (serial-type) applications, taking advantage of machines in the network that are not heavily used. An experimental software system, named MONSYS, that is capable of monitoring the machines in a network, is presented. MONSYS can be used in the support of an Application Manager system capable of distributing parallel tasks (or classical programs) over the machines in a local area network with the objective of achieving load balancing. It can also be used as a tool in the administration of networks. MONSYS exhibits a highly decentralized and fault tolerant architecture based on the Peer-Model, which, together with its information diffusion algorithms, constitute its prime novelty. A set of experiments that investigate the performance and scalability of a prototype of MONSYS is presented and discussed. The experiments reported show that MONSYS offers a reasonably accurate picture of the internal state of the machines monitored, without being a burden to the network communication channels or to the machines themselves. In fact, the quantitative results obtained indicate that MONSYS can be several times more performant than an equivalent system using a multicast communication scheme for the exchange of machine state information.     

基于ARM和GPRS的环境监测系统设计

提出了一种基于GPRS技术的环境监测数据通信系统,此系统主要由监测站、传输网络和监控中心等部分组成,采用GPRS无线网络和Internet网络为通道来实现监测数据的远程传输和状态监控,采用基于ARM的S3C2440A芯片为核心设计的监测站的硬件电路,达到实时监控的目的。