无线传感器网络节点的三维质心定位算法研究

无线传感器网络可以在广泛的应用领域内实现复杂的大规模监测和追踪任务,而节点的自定位技术是传感器网络的关键技术。文章以二维质心定位算法为基础,提出了三维质心定位算法,用C＋＋仿真结果表明,二维质心定位算法升级为三维质心定位算法没有明显增加算法的复杂性,也不影响覆盖率、通信报丈量和二维定位误差,但却能提供三维定位坐标信息。     

Mobeyes: smart mobs for urban monitoring with a vehicular sensor network

Vehicular sensor networks are emerging as a new network paradigm of primary relevance, especially for proactively gathering monitoring information in urban environments. Vehicles typically have no strict constraints on processing power and storage capabilities. They can sense events (e.g., imaging from streets), process sensed data (e.g., recognizing license plates), and route messages to other vehicles (e.g., diffusing relevant notification to drivers or police agents). In this novel and challenging mobile environment, sensors can generate a sheer amount of data, and traditional sensor network approaches for data reporting become unfeasible. This article proposes MobEyes, an efficient lightweight support for proactive urban monitoring based on the primary idea of exploiting vehicle mobility to opportunistically diffuse summaries about sensed data. The reported experimental/analytic results show that MobEyes can harvest summaries and build a low-cost distributed index with reasonable completeness, good scalability, and limited overhead     

Energy-Aware Data Aggregation for Grid-Based Wireless Sensor Networks with a Mobile Sink

Wireless sensor networks (WSNs) are made up of many small and highly sensitive nodes that have the ability to react quickly. In WSNs, sink mobility brings new challenges to large-scale sensor networks. Almost all of the energy-aware routing protocols that have been proposed for WSNs aim at optimizing network performance while relaying data to a stationary gateway (sink). However, through such contemporary protocols, mobility of the sink can make established routes unstable and non-optimal. The use of mobile sinks introduces a trade-off between the need for frequent rerouting to ensure optimal network operation and the desire to minimize the overhead of topology management. In this paper, in order to reduce energy consumption and minimize the overhead of rerouting frequency, we propose an energy-aware data aggregation scheme (EADA) for grid-based wireless sensor networks with a mobile sink. In the proposed scheme, each sensor node with location information and limited energy is considered. Our approach utilizes location information and selects a special gateway in each area of a grid responsible for forwarding messages. We restrict the flooding region to decrease the overhead for route decision by utilizing local information. We conducted simulations to show that the proposed routing scheme outperforms the coordination-based data dissemination scheme (CODE) (Xuan, H. L., & Lee, S. Proceedings of the Sensor Networks and Information Processing Conference, pp. 13–18, 2004).     

Distributed audio sensing with homeostasis-inspired autonomous communication

Emerging applications of wireless sensor networks (WSN) requiring wide-band event signal communication such as multimedia surveillance sensor networks impose additional challenges including high communication bandwidth requirement and energy cost. Besides their partially or fully dependency on feedback messages from sink node, the existing protocols designed for WSN do not address the communication of wide-band event signals. Furthermore, the feedback messages may not reach in time to provide reliable communication of event information and save scarce network resources. Therefore, an autonomous communication protocol is imperative in order to provide wide-band event signal communication without any feedback from the sink. In nature, biological systems have self-organization capability, i.e., homeostasis, as they autonomously maintain a relatively stable equilibrium state for operation of vital functions. Hence, this natural phenomenon clearly gives promising inspirations in order to develop autonomous and efficient communication models and protocols for WSN domain. In this paper, the homeostasis-inspired autonomous communication (HAC) protocol is introduced for wireless audio sensor networks (WASN). Using the spectral properties of the wide-band event signal, i.e., audio signal, HAC enables WASN to maintain a relatively stable state in which sensor nodes reliably and energy-efficiently communicate the event signal to the sink node. Furthermore, with its self-organization capability, HAC does not rely on any feedback message from the sink node. Performance evaluations reveal that HAC successfully communicates wide-band event signal with minimum energy expenditure.     

Lower bounds on data collection time in sensory networks

Data collection, i.e., the aggregation at the user location of information gathered by sensor nodes, is a fundamental function of sensory networks. Indeed, most sensor network applications rely on data collection capabilities, and consequently, an inefficient data collection process may adversely affect the performance of the network. In this paper, we study via simple discrete mathematical models, the time performance of the data collection and data distribution tasks in sensory networks. Specifically, we derive the minimum delay in collecting sensor data for networks of various topologies such as line, multiline, and tree and give corresponding optimal scheduling strategies. Furthermore, we bound the data collection time on general graph networks. Our analyses apply to networks equipped with directional or omnidirectional antennas and simple comparative results of the two systems are presented.     

无线传感器网络节点的辅助式定位方法

节点定位是无线传感器网络的一个重要研究内容。针对传感器网络内所有节点物理位置都未知的情况，文中提出一种利用已知的外界参考信号源来对网络内传感器节点进行定位的方法，并建立了基于TDOA、TOA及AOA的定位估计模型。尽管参数测量有误差，但所提出的方法能够提供有效的位置信息及一定的精度，而且基于AOA的定位模型并不增加传感器节点的成本和复杂度。仿真实验结果表明，该方法能对节点进行有效的定位。     

Message delivery in heterogeneous networks prone to episodic connectivity

We present an efficient message delivery framework, called MeDeHa, which enables communication in an internet connecting heterogeneous networks that is prone to disruptions in connectivity. MeDeHa is complementary to the IRTF’s Bundle Architecture: besides its ability to store messages for unavailable destinations, MeDeHa can bridge the connectivity gap between infrastructure-based and multi-hop infrastructure-less networks. It benefits from network heterogeneity (e.g., nodes supporting more than one network and nodes having diverse resources) to improve message delivery. For example, in IEEE 802.11 networks, participating nodes may use both infrastructure- and ad-hoc modes to deliver data to otherwise unavailable destinations. It also employs opportunistic routing to support nodes with episodic connectivity. One of MeDeHa’s key features is that any MeDeHa node can relay data to any destination and can act as a gateway to make two networks inter-operate or to connect to the backbone network. The network is able to store data destined to temporarily unavailable nodes till the time of their expiry. This time period depends upon current storage availability as well as quality-of-service needs (e.g., delivery delay bounds) imposed by the application. We showcase MeDeHa’s ability to operate in environments consisting of a diverse set of interconnected networks and evaluate its performance through extensive simulations using a variety of scenarios with realistic synthetic and real mobility traces. Our results show significant improvement in average delivery ratio and a significant decrease in average delivery delay in the face of episodic connectivity. We also demonstrate that MeDeHa supports different levels of quality-of-service through traffic differentiation and message prioritization.     

Low overhead assignment of symbolic coordinates in sensor networks

Approximate information on the location of nodes in a sensor network is essential to many types of sensor network applications and algorithms. In many cases, using symbolic coordinates is an attractive alternative to the use of geographic coordinates due to lower costs and lower requirements on the available location information during coordinate assignment. In this paper, we investigate different possible methods of assigning symbolic coordinates to sensor nodes. We present a method based on broadcasting coordinate messages and filtering using sensor events. We show in the evaluation that this method allows a reliable assignment of symbolic coordinates while only generating a low overhead.     

An efficient network‐coding based back‐pressure scheduling algorithm for wireless multi‐hop networks

Back‐pressure scheduling has been considered as a promising strategy for resource allocation in wireless multi‐hop networks. However, there still exist some problems preventing its wide deployment in practice. One of the problems is its poor end‐to‐end (E2E) delay performance. In this paper, we study how to effectively use inter‐flow network coding to improve E2E delay and also throughput performance of back‐pressure scheduling. For this purpose, we propose an efficient network coding based back‐pressure algorithm (NBP), and accordingly design detailed procedure regarding how to consider coding gain in back‐pressure based weight calculation and how to integrate it into next hop decision making in the NBP algorithm. We theoretically prove that NBP can stabilize the networks. Simulation results demonstrate that NBP can not only improve the delay performance of back‐pressure algorithm, but also achieve higher network throughput. Copyright © 2016 John Wiley & Sons, Ltd.     

无线网络中基于变分消息传递的分布式协作定位算法

针对基于消息传递算法的节点定位方法复杂度和通信开销较高的问题,提出一种适用于节点可移动网络的低复杂度低协作开销的节点自定位算法。为降低通信负载,该算法将消息约束为高斯型函数,网络中只需传输各消息的均值和方差,并采用适用于指数模型的变分消息传递(VMP)算法以降低计算复杂度。首先,根据节点的历史轨迹对节点位置进行预测,得到当前时刻的先验信息。然后,在因子图上按照VMP消息更新规则、通过迭代近似求解节点位置变量的后验分布。在消息更新中,对于非线性测距模型引起的非高斯置信,通过非线性项的二阶泰勒级数展开将其近似为高斯型函数。最后,根据最大后验估计准则得到位置估计。仿真结果表明,该算法的定位精度与基于非参数化置信传播的SPAWN（Sum-Product Algorithm over a Wireless Network）接近,但计算复杂度和通信负载均显著降低。      

物联网中音频事件检测方法的研究

Recently, the Internet of Things (IoT) has attracted more and more attention. Multimedia sensor network plays an important role in the IoT, and audio event detection in the multimedia sensor networks is one of the most important applications for the Internet of Things. In practice, it is hard to get enough real-world samples to generate the classifiers for some special audio events (e.g., car-crashing in the smart traffic system). In this paper, we introduce a TrAdaBoost-based method to solve the above problem. By using the proposed approach, we can train a strong classifier by using only a tiny amount of real-world data and a large number of more easily colle cted samples (e.g., collected from TV programs), even when the real-world data is not sufficient to train a model alone. We deploy this approach in a smart traffic system to evaluate its performance, and the experiment evaluations demonstrate that our method can achieve satisfying results.     

Novel self-configurable positioning technique for multihop wireless networks

Geographic location information can effectively improve the performance (e.g., in routing or intelligent coordination) of large wireless networks. In this paper, we propose a novel self-configurable positioning technique for multihop wireless networks, based on a Euclidean distance estimation model and a coordinates establishment scheme. A number of nodes serve as the landmarks to establish a coordinates system. Specifically, any pair of landmarks estimate their Euclidean distance according to the shortest path length between them and establish the coordinates system by minimizing an error objective function. Other nodes in the network can accordingly contact the landmarks and determine their own coordinates. The proposed technique is independent of the Global Navigation Satellite Systems (GNSSs), and the established coordinates can be easily tuned to GNSS if at least one node in the network is equipped with GNSS receiver. Our simulation results show that the proposed self-configurable positioning technique is highly fault-tolerable to measurement inaccuracy and can effectively establish the coordinates for multihop wireless networks. More landmarks yield more accurate results. With the rectification of our Euclidean distance estimation model, four to seven landmarks are usually sufficient to meet the accuracy requirement in a network with hundreds of nodes. The computing time for coordinates establishment is in the order of milliseconds for a GHz CPU, acceptable for most applications in the mobile ad hoc networks as well as the sensor networks.     

Privacy Protected Spatial Query Processing for Advanced Location Based Services

Due to the popularity of mobile devices (e.g., cell phones, PDAs, etc.), location-based services have become more and more prevalent in recent years. However, users have to reveal their location information to access location-based services with existing service infrastructures. It is possible that adversaries could collect the location information, which in turn invades user’s privacy. There are existing solutions for query processing on spatial networks and mobile user privacy protection in Euclidean space. However there is no solution for solving queries on spatial networks with privacy protection. Therefore, we aim to provide network distance spatial query solutions which can preserve user privacy by utilizing K-anonymity mechanisms. In this paper, we propose an effective location cloaking mechanism based on spatial networks and two novel query algorithms, PSNN and PSRQ, for answering nearest neighbor queries and range queries on spatial networks without revealing private information of the query initiator. We demonstrate the appeal of our technique using extensive simulation results.     

无线传感器网络中AOA节点定位改进算法研究

基于信号到达角度(AOA)的定位算法是一种常见的无线传感器网络节点自定位算法,算法通信开销低,定位精度较高。由于各种原因,估测的多个节点位置可能存在不可靠位置,提出了一种改进的基于信号到达角的定位方法,通过过滤误差较大的估计位置,来提高定位的精度。仿真结果表明,本文提出的改进算法很好地提高了定位精度。     

移动无线传感器网络定位算法研究

为了解决移动无线传感器网络中节点的自身定位问题,提出了一种基于运动预测的定位算法。该算法利用节点运动的连续性和接收信号强度测距方式,保存其最近两组历史位置信息,并结合节点当前的状态来估计自身位置。它不需要额外的硬件支持与较高的信标节点密度,满足复杂传输环境的应用要求。仿真结果表明,该算法具有较好的鲁棒性和较高的定位精度,节点随机运动时的定位误差约为15%,而直线运动时只有12%。     

机会网络中基于ferry的低能耗路由算法

在节点移动规律无法预知、连通性较差的机会网络中,FIMF(Ferry-Initialed Message Ferrying)路由能够有效地提高网络中消息传递成功率.在FIMF路由机制中,普通节点在传递控制消息(如节点位置消息、Hello消息)时存在多余的通信开销,并且采用了大功率发送位置消息会耗费过多能量.提出了基于RSSI测距技术和跨层设计的消息摆渡节能路由算法AFIMF.AFIMF中采用基于RSSI测距技术,在普通节点上采用自适应调整功率技术和跨层检测技术按需发送Hello消息.仿真结果表明,AFIMF算法有良好的稳定性,在保证通信传递率的前提下,普通节点不仅有效地节约了能量,而且减少了开销.     

Dimensionality determination of unknown deployed underwater sensor network (UWSN) using cost function

This paper proposes a novel estimation technique for dimensionality of deployed underwater sensor network (UWSN). In order to obtain the dimension, probing requests are sent from two anchor nodes (i.e., receivers), which are placed inside the network through buoy, to sensor nodes. Then, the sensor nodes transmit Gaussian signal as feedback to the anchor nodes. The cross‐correlation function (CCF) is determined of these Gaussian signals, which varies according to network dimension. As reference, analytical CCF of five reference networks of different dimensions is determined. Thereafter, by comparing the CCFs of unknown and reference UWSN, cost function (CF) is obtained. The lowest value of CF attained by the specific combination of the one reference and the unknown network indicates that the dimension of these networks is identical. The dimension of two unknown deployed networks is investigated to demonstrate the feasibility of the proposed technique. From the illustrated results, it is justified that the new strategy can provide correct information about the dimension of the deployed network.     

Broadcasting in Sensor Networks: The Role of Local Information

Flooding based querying and broadcasting schemes have low hop-delays of $Theta {( {{ 1}over { R(n)}})}$ to reach any node that is a unit distance away, where $R(n)$ is the transmission range of any sensor node. However, in sensor networks with large radio ranges, flooding based broadcasting schemes cause many redundant transmissions leading to a broadcast storm problem. In this paper, we study the role of geographic information and state information (i.e., memory of previous messages or transmissions) in reducing the redundant transmissions in the network.      

Game-theoretic models for reliable path-length and energy-constrained routing with data aggregation in wireless sensor networks

Path length, path reliability, and sensor energy-consumption are three major constraints affecting routing in resource constrained, unreliable wireless sensor networks. By considering the implicit collaborative imperative for sensors to achieve overall network objectives subject to individual resource consumption, we develop a game-theoretic model of reliable, length and energy-constrained, sensor-centric information routing in sensor networks. We define two distinct payoff (benefit) functions and show that computing optimally reliable energy-constrained paths is NP-Hard under both models for arbitrary sensor networks. We then show that optimal length-constrained paths can be computed in polynomial time in a distributed manner (using O(E) messages) for popular sensor network implementations using geographic routing. We also develop sensor-centric metrics called path weakness to measure the qualitative performance of different routing schemes and provide theoretical limits on the inapproximability of computing paths with bounded weakness. Heuristics for computing optimal paths in arbitrary sensor networks are described along with simulation results comparing performance with other routing algorithms.     

无线传感器网络密钥预分配蜂窝模型

要达到无线传感器网络的安全通信,必须对网络中节点之间的通讯数据用密钥进行必要的加密。文章使用蜂窝模型分组方案,把节点按照预测的地理位置关系分组,给处于相同组或是相邻组的节点之间分配共享密钥,使节点的分组模式和查询更符合节点广播特征。蜂窝模型密钥预分配机制极大的提高密钥利用率,减少了密钥分配和维护代价,使传感器网络的安全性和连通性极大的提高。