Wireless sensor network survey

A wireless sensor network (WSN) has important applications such as remote environmental monitoring and target tracking. This has been enabled by the availability, particularly in recent years, of sensors that are smaller, cheaper, and intelligent. These sensors are equipped with wireless interfaces with which they can communicate with one another to form a network. The design of a WSN depends significantly on the application, and it must consider factors such as the environment, the application’s design objectives, cost, hardware, and system constraints. The goal of our survey is to present a comprehensive review of the recent literature since the publication of [I.F. Akyildiz, W. Su, Y. Sankarasubramaniam, E. Cayirci, A survey on sensor networks, IEEE Communications Magazine, 2002]. Following a top-down approach, we give an overview of several new applications and then review the literature on various aspects of WSNs. We classify the problems into three different categories: (1) internal platform and underlying operating system, (2) communication protocol stack, and (3) network services, provisioning, and deployment. We review the major development in these three categories and outline new challenges.     

A survey on wireless sensor network infrastructure for agriculture

The hybrid wireless sensor network is a promising application of wireless sensor networking techniques. The main difference between a hybrid WSN and a terrestrial wireless sensor network is the wireless underground sensor network, which communicates in the soil. In this paper, a hybrid wireless sensor network architecture is introduced. The framework to deploy and operate a hybrid WSN is developed. Experiments were conducted using a soil that was 50% sand, 35% silt, and 15% clay; it had a bulk density of 1.5 g/cm³ and a specific density of 2.6 cm^? 3. The experiment was conducted for several soil moistures (5, 10, 15, 20 and 25%) and three signal frequencies (433, 868 and 915 MHz). The results show that the radio signal path loss is smallest for low frequency signals and low moisture soils. Furthermore, the node deployment depth affected signal attenuation for the 433 MHz signal. The best node deployment depth for effective transmission in a wireless underground sensor network was determined.     

A survey of urban vehicular sensing platforms

Vehicular sensing where vehicles on the road continuously gather, process, and share location-relevant sensor data (e.g., road condition, traffic flow) is emerging as a new network paradigm for sensor information sharing in urban environments. Recently, smartphones have also received a lot of attention for their potential as portable vehicular urban sensing platforms, as they are equipped with a variety of environment and motion sensors (e.g., audio/video, accelerometer, and GPS) and multiple wireless interfaces (e.g., WiFi, Bluetooth and 2/3G). The ability to take a smartphone on board a vehicle and to complement the sensors of the latter with advanced smartphone capabilities is of immense interest to the industry. In this paper we survey recent vehicular sensor network developments and identify new trends. In particular we review the way sensor information is collected, stored and harvested using inter-vehicular communications (e.g., mobility-assist mobility-assisted dissemination and geographic storage), as well using the infrastructure (e.g., centralized and distributed storage in the wired Internet). The comparative performance of the various sensing schemes is important to us. Thus, we review key results by carefully examining and explaining the evaluation methodology, in the process gaining insight into vehicular sensor network design. Our comparative study confirms that system performance is impacted by a variety of factors such as wireless access methods, mobility, user location, and popularity of the information.     

A plug-and-play data gathering system using ZigBee-based sensor network sensor network

In order to quickly establish a data gathering system in a flexible manufacturing environment, this paper presents a ZigBee-based wireless sensor network combined with a data processing system. The proposed system includes a system simulator, instrument definition module and network monitor module. System functions include network parameter setting, real-time system status sensing and data collecting, intelligent event monitoring and warning, and ad hoc response mechanisms. The proposed system enables users to quickly plug-and-play any digital instrument in their production systems and automatically capturing production data. Production controller can adopt these data to make decisions in real-time.     

机器人视觉伺服研究综述

首先对于3种机器人视觉伺服策略,即基于位置的视觉伺服、基于图像的视觉伺服以及2.5维视觉伺服进行了讨论.然后,对于视觉伺服的研究方向和面临的主要问题,如机器人位姿提取、视觉伺服系统的不确定性研究、图像空间的路径规划、智能视觉伺服等进行了分析和讨论.在此基础上,对于机器人视觉伺服领域的未来研究重点,包括如何使参考点位于视场之内,高速伺服策略以及鲁棒视觉伺服技术进行了分析和展望.     

A survey of network virtualization

Due to the existence of multiple stakeholders with conflicting goals and policies, alterations to the existing Internet architecture are now limited to simple incremental updates; deployment of any new, radically different technology is next to impossible. To fend off this ossification, network virtualization has been propounded as a diversifying attribute of the future inter-networking paradigm. By introducing a plurality of heterogeneous network architectures cohabiting on a shared physical substrate, network virtualization promotes innovations and diversified applications. In this paper, we survey the existing technologies and a wide array of past and state-of-the-art projects on network virtualization followed by a discussion of major challenges in this area.     

A survey on run-time supporting platforms for cyber physical systems

Cyber physical systems (CPSs) incorporate computation, communication, and physical processes. The deep coupling and continuous interaction between such processes lead to a significant increase in complexity in the design and implementation of CPSs. Consequently, whereas developing CPSs from scratch is inefficient, developing them with the aid of CPS run-time sup-porting platforms can be efficient. In recent years, much research has been actively conducted on CPS run-time supporting plat-forms. However, few surveys have been conducted on these platforms. In this paper, we analyze and evaluate existing CPS run-time supporting platforms by first classifying them into three categories from the viewpoint of software architecture: com-ponent-based platforms, service-based platforms, and agent-based platforms. Then, for each type, we detail its design philosophy, key technical problems, and corresponding solutions with specific use cases. Subsequently, we compare existing platforms from two aspects: construction approaches for CPS tasks and support for non-functional properties. Finally, we outline several im-portant future research issues.     

A study on visual sensor network cross-layer resource allocation using quality-based criteria and metaheuristic optimization algorithms

Visual sensor networks (VSNs) consist of spatially distributed video cameras that are capable of compressing and transmitting the video sequences they acquire. We consider a direct-sequence code division multiple access (DS-CDMA) VSN, where each node has its individual requirements in compression bit rate and energy consumption, depending on the corresponding application and the characteristics of the monitored scene. We study two optimization criteria for the optimal allocation of the source and channel coding rates, which assume discrete values, as well as for the power levels of all nodes, which are continuous, under transmission bit rate constraints. The first criterion minimizes the average distortion of the video received by all nodes, while the second one minimizes the maximum video distortion among all nodes. The resulting mixed integer optimization problems are tackled with a modern optimization algorithm, namely particle swarm optimization (PSO), as well as a hybrid scheme that combines PSO with the deterministic Active-Set optimization method. Extensive experimentation on interference-limited as well as noisy environments offers significant intuition regarding the effectiveness of the considered optimization schemes, indicating the impact of the video sequence characteristics on the joint determination of the transmission parameters of the VSN.     

多平台间网络通信的实现方案

网络通信无处不在,通信设备及通信应用软件层出不穷。分析了一种应用通信控制器解决多平台之间网络通信的方案,可以实现多种接口、多种协议之间的互连,并给出了UNIX平台终端客户代理的实现实例。     

一种用于地震检波的传感器网络节点的设计

将传感器网络的思想应用于地震检波,实现对被测区域勘测信息的分布式监测和处理。对交流相位跟踪零差解调算法(PTAC)和温度补偿原理进行了研究,并根据该算法设计了解调电路。以C8051f020单片机为核心,设计了数据采集和网络通信模块,从而实现了集信号解调和网络通信功能于一体的地震检波传感器网络节点。实验结果表明,该节点可以对10～1000Hz的加速度信号进行解调,且对温度漂移有良好的抑制作用,可以实现基于UDP/IP协议的数据通信。     

A survey of network flow applications

It has been over 16 years since Cisco's NetFlow was patented in 1996. Extensive research has been conducted since then and many applications have been developed. In this survey, we have reviewed an extensive number of studies with emphasis on network flow applications. First, we provide a brief introduction to sFlow, NetFlow and network traffic analysis. Then, we review the state of the art in the field by presenting the main perspectives and methodologies. Our analysis has revealed that network security has been an important research topic since the beginning. Advanced methodologies, such as machine learning, have been very promising. We provide a critique of the studies surveyed about datasets, perspectives, methodologies, challenges, future directions and ideas for potential integration with other Information Technology infrastructure and methods. Finally, we concluded this survey.     

A survey of network anomaly visualization

Network anomaly analysis is an emerging subtopic of network security. Network anomaly refers to the unusual behavior of network devices or suspicious network status. A number of intelligent visual tools are developed to enhance the ability of network security analysts in understanding the original data, ultimately solving network security problems. This paper surveys current progress and trends in network anomaly visualization. By providing an overview of network anomaly data, visualization tasks, and applications, we further elaborate on existing methods to depict various data features of network alerts, anomalous traffic, and attack patterns data. Directions for future studies are outlined at the end of this paper.     

A survey of neural network accelerators

Machine-learning techniques have recently been proved to be successful in various domains, especially in emerging commercial applications. As a set of machine-learning techniques, artificial neural networks (ANNs), requiring considerable amount of computation and memory, are one of the most popular algorithms and have been applied in a broad range of applications such as speech recognition, face identification, natural language processing, ect. Conventionally, as a straightforward way, conventional CPUs and GPUs are energy-inefficient due to their excessive effort for flexibility. According to the aforementioned situation, in recent years, many researchers have proposed a number of neural network accelerators to achieve high performance and low power consumption. Thus, the main purpose of this literature is to briefly review recent related works, as well as the DianNao-family accelerators. In summary, this review can serve as a reference for hardware researchers in the area of neural networks.     

A parallel network for visual cognition

The authors describe a parallel dynamical system designed to integrate model-based and data-driven approaches to image recognition in a neural network, and study one component of the system in detail. That component is the translation-invariant network of probabilistic cellular automata (PCA), which combines feature-detector outputs and collectively performs enhancement and recognition functions. Recognition is a novel application of the PCA. Given a model of the target object, conditions on the PCA weights are obtained which must be satisfied for object enhancement and noise rejection to occur, and engineered weights are constructed. For further refinement of the weights, a training algorithm derived from optimal control theory is proposed. System operation is illustrated with examples derived from visual, infrared, and laser-radar imagery.     

基于贝叶斯网络的软测量建模方法

软测量技术对化工生产过程中提高产品质量和保证安全生产具有重要的作用,因此对化工软测量建模方法的研究具有重要意义.本文将贝叶斯网络应用于化工软测量建模,采用高斯混合模型来近似表达贝叶斯网络模型中的联合概率分布,通过Expectation Maximization算法求解出高斯混合模型参数并给出了贝叶斯网络估计公式.应用此法分别对某炼油厂脱丁烷塔塔底丁烷含量和某双酚A生产过程中脱水塔出口组分苯酚含量建立了软测量模型,取得了良好的离线估计结果.仿真结果表明,与支持向量机相比,在估计精度相当的情况下,省去了许多过程参数的估计,是1种有效的软测量建模方法.     

一种有线传感器网络节点测距方法

针对有线传感器网络节点间需要定位问题,提出了一种有线传感器网络节点测距的方法,其中有线传感器网络中测距主机和若干个传感器节点顺序分布于二线制总线上,测距主机具有脉冲反射和接收电路,被测距节点具有短路电子开关,能按照预定命令控制电子开关闭合,主动使自身连接点处的传输线失配。利用传输线时域脉冲反射原理,进行了相关测距实验测定各个传感器节点到测距主机间的距离。实验结果表明:该方法可测定有线传感器网络主机到传感器节点间的距离并判定它们的连接顺序,效果良好。     

A feasible method for sensor network localization

A nonlinear programming (NLP) model with partial orthogonality constraints, relaxed from the polynomial optimization problem, is proposed and analysed for solving sensor network localization. The NLP model is difficult to solve as the orthogonality constraints are not only non-convex but numerically expensive to preserve during iterations. To deal with this difficulty, we apply the Cayley transform (a Crank–Nicolson-like update scheme) to preserve it. Combining with the gradient descent method, we develop a curvilinear search algorithm, and analyse its convergence. In practice, we accelerate our method by taking nonlinear conjugate gradient method and Barzilai–Borwein steps. Numerical experiments are given to demonstrate the efficiency of the proposed method, for the problems with the number of sensors up to 15,000 and the distance constraints up to 135,817.     

A survey on context-aware mobile visual recognition

The phenomenal growth of the usage of mobile devices (e.g., mobile phones and tablet PCs) opens up a new service, namely mobile visual recognition, which has been widely used in many areas, such as mobile shopping and augmented reality. The rich contextual information (e.g., location, time and direction information), easily acquired by the mobile devices, provides useful clues to facilitate mobile visual recognition, including speeding up the recognition time and improving the recognition performance. This survey focuses on recent advances in Context-Aware Mobile Visual Recognition (CAMVR) and reviews related work regarding to different contextual information, recognition methods, recognition types, and various application scenarios. Finally, we discuss future research directions in this field.