Routing in wireless sensor networks for wind turbine monitoring

Smart wireless sensor devices are rapidly emerging as key enablers of the next evolution in wind turbine monitoring. The potential for in-situ monitoring of turbine elements, employing methodologies that are not possible with existing wired technology, make it possible to attain new levels of granularity and autonomy in the monitoring of these structures. Wireless sensor devices are limited in terms of communication by the range of their radio modules and, thus, need to form networks in order to transfer data from distant points. Routing protocols are primary enablers of such ad hoc wireless sensor networks and these require the implementation of reliable and energy-efficient mechanisms to maximize network reliability and availability. Existing routing protocols cannot be directly applied to the monitoring of wind turbines without addressing the unique context and operational characteristics of these structures in multi-hop wireless communication. This work identifies the potential effects associated with the operation, environment and structure of wind turbines in wireless sensor network multi-hop communication, and proposes and evaluates a reliable routing protocol for wireless sensor networks employed in these domains.     

Connectivity preserving localized coverage algorithm for area monitoring using wireless sensor networks

Efficient network coverage and connectivity are the requisites for most Wireless Sensor Network (WSN) deployments, particularly those concerned with area monitoring. Due to the resource constraints of the sensor nodes, redundancy of coverage area must be reduced for effective utilization of the available resources. If two nodes have the same coverage area in their active state, and if both the nodes are activated simultaneously, it leads to redundancy in network and wastage of precious sensor resources. In this paper, we address the problem of network coverage and connectivity and propose an efficient solution to maintain coverage, while preserving the connectivity of the network. The proposed solution aims to cover the area of interest (AOI), while minimizing the count of the active sensor nodes. The overlap region of two sensor nodes varies with the distance between the nodes. If the distance between two sensor nodes is maximized, the overall coverage area of these nodes will also be maximized. Also, to preserve the connectivity of the network, each sensor node must be in the communication range of at least one other node. Results of simulation of the proposed solution indicate up to 95% coverage of the area, while consuming very less energy of 9.44 J per unit time in the network, simulated in an area of 2500 m².     

A framework for use of wireless sensor networks in forest fire detection and monitoring

Forest fires are one of the main causes of environmental degradation nowadays. Current surveillance systems for forest fires lack in supporting real-time monitoring of every point of a region at all times and early detection of fire threats. Solutions using wireless sensor networks, on the other hand, can gather sensory data values, such as temperature and humidity, from all points of a field continuously, day and night, and, provide fresh and accurate data to the fire-fighting center quickly. However, sensor networks face serious obstacles like limited energy resources and high vulnerability to harsh environmental conditions, that have to be considered carefully. In this paper, we propose a comprehensive framework for the use of wireless sensor networks for forest fire detection and monitoring. Our framework includes proposals for the wireless sensor network architecture, sensor deployment scheme, and clustering and communication protocols. The aim of the framework is to detect a fire threat as early as possible and yet consider the energy consumption of the sensor nodes and the environmental conditions that may affect the required activity level of the network. We implemented a simulator to validate and evaluate our proposed framework. Through extensive simulation experiments, we show that our framework can provide fast reaction to forest fires while also consuming energy efficiently.     

A hierarchical architecture for detecting selfish behaviour in community wireless mesh networks

Wireless mesh networks (WMNs) consist of dedicated nodes called mesh routers which relay the traffic generated by mesh clients over multi-hop paths. In a community WMN, all mesh routers may not be managed by an Internet Service Provider (ISP). Limited capacity of wireless channels and lack of a single trusted authority in such networks can motivate mesh routers to behave selfishly by dropping relay traffic in order to provide a higher throughput to their own users. Existing solutions for stimulating cooperation in multi-hop networks use promiscuous monitoring or exchange probe packets to detect selfish nodes and apply virtual currency mechanism to compensate the cooperating nodes. These schemes fail to operate well when applied to WMNs which have a multi-radio environment with a relatively static topology. In this paper we, propose architecture for a community WMN which can detect selfish behaviour in the network and enforce cooperation among mesh routers. The architecture adopts a decentralized detection scheme by dividing the mesh routers into manageable clusters. Monitoring agents hosted on managed mesh routers monitor the behaviour of mesh routers in their cluster by collecting periodic reports and sending them to the sink agents hosted at the mesh gateways. To make the detection more accurate we consider the quality of wireless links. We present experimental results that evaluate the performance of our scheme.     

From secure wired networks to secure wireless networks – what are the extra risks?

This paper investigates the information security requirements for wireless networks, and then compares that with the information security requirements for wired networks. The extra requirements needed for wireless networks security are then identified and discussed.     

A kernel machine-based secure data sensing and fusion scheme in wireless sensor networks for the cyber-physical systems

Wireless sensor networks (WSNs) as one of the key technologies for delivering sensor-related data drive the progress of cyber-physical systems (CPSs) in bridging the gap between the cyber world and the physical world. It is thus desirable to explore how to utilize intelligence properly by developing the effective scheme in WSN to support data sensing and fusion of CPS. This paper intends to serve this purpose by proposing a prediction-based data sensing and fusion scheme to reduce the data transmission and maintain the required coverage level of sensors in WSN while guaranteeing the data confidentiality. The proposed scheme is called GM–KRLS, which is featured through the use of grey model (GM), kernel recursive least squares (KRLS), and Blowfish algorithm (BA). During the data sensing and fusion process, GM is responsible for initially predicting the data of next period with a small number of data items, while KRLS is used to make the initial predicted value approximate its true value with high accuracy. The KRLS as an improved kernel machine learning algorithm can adaptively adjust the coefficients with every input, while making the predicted value more close to actual value. And BA is used for data encoding and decoding during the transmission process due to its successful applications across a wide range of domains. Then, the proposed secure data sensing and fusion scheme GM–KRLS can provide high prediction accuracy, low communication, good scalability, and confidentiality. In order to verify the effectiveness and reasonableness of our proposed approach, we conduct simulations on actual data sets that are collected from sensors in the Intel Berkeley research lab. The simulation results have shown that the proposed scheme can significantly reduce redundant transmissions with high prediction accuracy.     

McTorrent: Using multiple communication channels for efficient bulk data dissemination in wireless sensor networks

This paper presents McTorrent, a reliable bulk data dissemination protocol for sensor networks. The protocol is designed to take advantage of multiple radio channels to reduce packet collisions and improve the latency of large object dissemination. We evaluated the performance of McTorrent via detailed simulations and experiments based upon an implementation on the TinyOS platform. Our results show that in comparison to Deluge, the de facto network reprogramming protocol for TinyOS, McTorrent significantly reduces the number of packet transmissions and the amount of time required to propagate a large data object through a sensor network.     

Theoretical analysis of the lifetime and energy hole in cluster based wireless sensor networks

Cluster based wireless sensor networks have been widely used due to the good performance. However, in so many cluster based protocols, because of the complexity of the problem, theoretical analysis and optimization remain difficult to develop. This paper studies the performance optimization of four protocols theoretically. They are LEACH (Low Energy Adaptive Clustering Hierarchy), MLEACH (Multi-hop LEACH), HEED (Hybrid Energy-Efficient Distributed Clustering Approach), and UCR (Unequal Cluster based Routing). The maximum FIRST node DIED TIME (FDT) and the maximum ALL node DIED TIME (ADT) are obtained for the first time in this paper, as well as the optimal parameters which maximize the network lifetime. Different from previous analysis of network lifetime, this paper analyzes the node energy consumption in different regions through the differential analysis method. Thus, the optimal parameters which maximize the lifetime can be obtained and the detailed energy consumption in different regions at different time can be also obtained. Moreover, we can obtain the time and space evolution of the network, from a steady state (without any death) to a non-steady state (with some death of nodes), and then to the final situation (all nodes die). Therefore, we are fully aware of the network status from spatial and temporal analysis. Additionally, the correctness of the theoretical analysis in this paper is proved by the Omnet++ experiment results. This conclusion can be an effective guideline for the deployment and optimization of cluster based networks.     

An asynchronous MAC protocol for wireless sensor networks

The MAC protocol for wireless sensor network plays a very important role in the control of energy consumption. It is a very important issue to effectively utilize power under the condition of limited energy. The most energy-wasting part of the MAC protocol for wireless sensor network is at the idling condition. Therefore it is crucial for power saving to be able to turn off the signal transducer of the wireless network when the equipment is idling. Pattern-MAC (PMAC) allows sensors that did not transfer for a long period of time to quickly enter a dormant state, so that the problem of sensor overhearing can be greatly improved, and the whole network structure can fully respond to the actual transfer rate without too much energy consumption, but this type of design requires precise time synchronization mechanism. Achieving time synchronization is a very energy consuming and very expensive mechanism in the sensor network structure, achieving the goal is coupled with excess energy consumption and reduction of the lifespan of the sensor. Additionally, the exchange action with the neighboring pattern after each cycle, not only generates additional energy consumption for data transfer, but is also accompanied by factors such as competition, collision and pattern exchange failure. We propose an asynchronous MAC protocol (AMAC) in this paper and expect to improve the problem of energy wasting and time synchronization due to sleeping schedule exchange under the PMAC basic protocol.     

Towards the fast and robust optimal design of wireless body area networks

Wireless body area networks are wireless sensor networks whose adoption has recently emerged and spread in important healthcare applications, such as the remote monitoring of health conditions of patients. A major issue associated with the deployment of such networks is represented by energy consumption: in general, the batteries of the sensors cannot be easily replaced and recharged, so containing the usage of energy by a rational design of the network and of the routing is crucial. Another issue is represented by traffic uncertainty: body sensors may produce data at a variable rate that is not exactly known in advance, for example because the generation of data is event-driven. Neglecting traffic uncertainty may lead to wrong design and routing decisions, which may compromise the functionality of the network and have very bad effects on the health of the patients. In order to address these issues, in this work we propose the first robust optimization model for jointly optimizing the topology and the routing in body area networks under traffic uncertainty. Since the problem may result challenging even for a state-of-the-art optimization solver, we propose an original optimization algorithm that exploits suitable linear relaxations to guide a randomized fixing of the variables, supported by an exact large variable neighborhood search. Experiments on realistic instances indicate that our algorithm performs better than a state-of-the-art solver, fast producing solutions associated with improved optimality gaps.     

CCS-MAC: Exploiting the overheard data for compression in wireless sensor networks

Both the overhearing and overhearing avoidance in a densely distributed sensor network may inevitably incur considerable power consumption. In this paper we propose a so-called CCS-MAC (collaborative compression strategy-based MAC) MAC protocol which facilitates to exploit those overheard data that is treated useless in traditional MAC protocols for the purpose of cost and energy savings. Particularly the CCS-MAC enables different sensor nodes to perform data compression cooperatively with regard to those overheard data, so that the redundancy of data prepared for the link layer transmission can be totally eliminated at the earliest. The problem of collaborative compression is analyzed and discussed along with a corresponding linear programming model formulated. Based on it a heuristic node-selection algorithm with a time complexity of (O(N²)) is proposed to the solve the linear programming problem. The node-selection algorithm is implemented in CCS-MAC at each sensor node in a distributed manner. The experiment results verify that the proposed CCS-MAC scheme can achieve a significant energy savings so as to prolong the lifetime of the sensor networks so far.     

基于无线传感器网络的水质监测系统设计

在研究无线传感器网络及Zigbee协议标准的基础上,对远程实时水质监测系统进行了分析.提出了基于Zigbee无线传感器网络与互联网结合的远程实时水质监测系统架构.设计了基于无线传感器的水质监测网络体系结构,实现了水质监测参数的荻取及传输.     

Development of wireless sensor network for combustible gas monitoring

This paper describes the development and the characterization of a wireless gas sensor network (WGSN) for the detection of combustible or explosive gases. The WGSN consists of a sensor node, a relay node, a network coordinator, and a wireless actuator. The sensor node attains early gas detection using an on board 2D semiconductor sensor. Because the sensor consumes a substantial amount of power, which negatively affects the node lifetime, we employ a pulse heating profile to achieve significant energy savings. The relay node receives and forwards traffic from sensor nodes towards the network coordinator and vice versa. When an emergency is detected, the network coordinator alarms an operator through the GSM/GPRS or Ethernet network, and may autonomously control the source of gas emission through the wireless actuator. Our experimental results demonstrate how to determine the optimal temperature of the sensor's sensitive layer for methane detection, show the response time of the sensor to various gases, and evaluate the power consumption of the sensor node. The demonstrated WGSN could be used for a wide range of gas monitoring applications.     

A wireless sensor networks MAC protocol for real-time applications

Wireless sensor networks (WSN) are designed for data gathering and processing, with particular requirements: low hardware complexity, low energy consumption, special traffic pattern support, scalability, and in some cases, real-time operation. In this paper we present the virtual TDMA for sensors (VTS) MAC protocol, which intends to support the previous features, focusing particularly on real-time operation. VTS adaptively creates a TDMA arrangement with a number of timeslots equal to the actual number of nodes in range. Thus, VTS achieves an optimal throughput performance compared to TDMA protocols with fixed size of frame. The frame is set up and maintained by a distributed procedure, which allows sensors to asynchronously join and leave the frame. In addition, duty cycle is increased or decreased in order to keep latency constant below a given deadline. Therefore, a major advantage of VTS is that it guarantees a bounded latency, which allows soft real-time applications.

Lifetime extension for surveillance wireless sensor networks with intelligent redeployment

For wireless sensor networks (WSNs), uneven energy consumption is a major problem. A direct consequence of this is the energy hole problem, formation of sensing voids within the network field due to battery depleted sensors in the corresponding region. Hole formations are inherent in the network topology, yet it is possible to develop strategies to delay the hole formations to later stages of the network operation and essentially extend the network lifetime without sensing quality loss. In this work, we initially propose and analyze an approach that can be used to mitigate the hole problem. The approach is presented in detail and the effects on the sustained surveillance quality are presented. The results are based on simulations with different network configurations with realistic sensor models, MAC and routing protocols. By using the proposed approach, sustaining a sensing quality above a given threshold and more than doubling the network lifetime are possible. The results clearly indicate the suitability of the approach for especially demanding WSNs such as the ones used for border surveillance tasks.     

传感器网络中无线电干涉定位系统的多径误差分析

根据多径信号的物理特性,从理论上推导了镜反射的多径误差简便模型,基于该模型进行了无线电干涉定位系统的多径误差分析.讨论了衰减因子、天线高度和水平距离等多径参数对测量结果的影响,并且进行了仿真计算和分析.结果表明,高精度定位必须考虑多径效应.     

Distributed iterative quantization for interference characterization in wireless networks

We consider the problem of estimating the distance to a device transmitting in the 2.4 GHz ISM band that is interfering with users of an 802.11b wireless network. Accurate estimation of this quantity enables the wireless network to dynamically change its operating characteristics, such as its transmit power levels and channel assignments, to minimize this interference. The estimate is made by a cluster of wireless sensor motes deployed along the edge of an 802.11b network. The motes perform a 1-bit quantization of the Received Signal Strength (RSS) using a dithered quantization framework. The quantized bits are transmitted over a Binary Symmetric Channel (BSC) to the Cluster Head (CH), which then uses a Maximum-Likelihood Estimation (MLE) technique to estimate the unknown parameter. We propose a framework in which the CH uses an iterative parameter estimation scheme in which it provides low-overhead feedback to the motes to adjust their threshold values for the 1-bit dithered quantization process. Evaluation of the Root Mean Squared Error (RMSE) of this iterative scheme shows that it performs significantly better than iterative approaches in which all the motes use either identical thresholds or the non-identical thresholds proposed in Ribeiro and Giannakis (2006) [5] and [19]. Our iterative scheme also tracks sudden changes in the distance to the interferer and is robust to fluctuations in the crossover probability in the BSC.     

无线传感器网络中信道仿真模型的研究

无线传感器网络是一种全新的技术,能够广泛应用于恶劣环境和军事领域中。针对无线传感器刚络的仿真也随之而来,大部分仿真重点在路由层和MAC层,研究传感器网络的连通性和网络生存周期,而忽略了物理信道的特征。该文主要针对无线传感器网络的特殊性分析和介绍了基于OPNET的无线信道模型,给出了必要的数学计箅。通过基于信道接入的分簇算法的网络仿真,验证了无线链路的关键参数对于无线传感器网络的网络结构的影响,给出了系统的仿真结果。     

基于ZigBee无线传感器网络的起重机监控系统

结合ZigBee无线通信技术,提出一种应用于起重机监控的无线传感网络系统架构。该方案网络节点硬件电路以MC9SDG128为控制器、CC2530为射频收发器,详细规划了网络中节点硬件和软件设计,并介绍上位监控系统。该系统具有低成本、低功耗、易扩展、安全性高等特点,能实时监控起重机的运行状况,可广泛应用于起重机监控系统。     

Accident aware localization mechanism for wireless sensor networks

Accurate location information is important for event reporting, coverage estimation, and location-aware routing in a Wireless Sensor Network (WSN). Recently, a number of range-free localization schemes have been proposed to provide each static sensor with location information, which is represented by a rectangular region. However, most WSN applications are applied in outdoor environments where the sensors’ location regions could be incorrect due to sudden accidents. This paper proposes an Active Location Correction Protocol, called ALCP, for detecting and correcting the occurrence of location error based on the bounding box technology. Performance study reveals that applying the ALCP to improve the location accuracies can enhance the performance of the well-known GPSR routing in terms of routing length, sensing coverage, and packet arrival rate.