An energy-saving routing architecture with a uniform clustering algorithm for wireless body sensor networks

Wireless body sensor networks are expected to extend human-centered applications in large-scale sensing and detecting environments. Energy savings has become one of the most important features of the sensor nodes to prolong their lifetime in such networks. To provide reasonable energy consumption and to improve the network lifetime of wireless body sensor network systems, new and efficient energy-saving schemes must be developed. An energy-saving routing architecture with a uniform clustering algorithm is proposed in this paper to reduce the energy consumption in wireless body sensor networks. We adopted centralized and cluster-based techniques to create a cluster-tree routing structure for the sensor nodes. The main goal of this scheme is to reduce the data transmission distances of the sensor nodes by using the uniform cluster structure concepts. To make an ideal cluster distribution, the distances between the sensor nodes are calculated, and the residual energy of each sensor node is accounted for when selecting the appropriate cluster head nodes. On the basis of the uniform cluster location, the data transmission distances between the sensor nodes can be reduced by employing an adaptive multi-hop approach. The energy consumption is reduced, and the lifetime is extended for the sensor nodes by balancing the network load among the clusters. Simulation results show that the proposed scheme outperforms the previously known schemes in terms of the energy consumption and the network lifetime for the wireless body sensor networks.     

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.     

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.     

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.     

无线传感器网络簇首提取压缩算法

对矢量数据压缩算法中DP压缩算法在引入无线传感器网络的同时进行了改进,针对压缩过程中对数据的扫描次数问题,提出簇首提取压缩算法。该算法中“簇首”即为“数据簇首”,簇首提取压缩算法设定步长减少压缩过程中对数据的扫描次数,并采用最佳曲线拟合方法对监测数据点做直线优化拟合,根据数据间的依附关系,将体现整体特征的簇首数据进行提取;同时,对非簇首数据进行子群划分。仿真结果表明,簇首提取压缩算法程序更为简单,对大波动数据有较好的簇首提取效果,减少了网络中数据的传输量,有效地节省了整个网络的能量消耗。     

用于工业监测的无线传感器网络多径路由协议

针对工业监测中多对一周期性数据采集应用,提出一个高可靠低开销逐跳多径路由协议PHMP.根据应用特点,综合利用定期和实时估计器评估链路质量,提高了选路质量.设计了一种高可靠低开销的逐跳多径路由,而且选路时还考虑了网络节点能耗的均衡性.仿真结果表明,PHMP能提高选路质量,以较小的能量和存储开销提高传输的可靠性,并且可提高网络节点能耗均衡性,从而尽可能地延长网络生存时间.     

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 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.     

Application specific study,analysis and classification of body area wireless sensor network applications

The evolution of wearable computing and advances in wearable sensor devices has motivated various applications of Body Area Sensor Networks (BASN). In the last few years body areas sensor networks have emerged as a major type of wireless sensor networks (WSN). This emerging networking technology can be used in various walks of life. A number of surveys have been published on MAC or the physical layer mechanism of BASN but very few have focused on studying it from the application point of view. In this paper, we first review, from literature, existing use of body area sensor network and classify and then its application domain. Within these application domains of BASN, we propose a feasibility of scenarios where BASN can be used for both application and technical aspects. In addition, we classify the use of BASN from literature, based on certain parameters. Finally, we discuss and highlight issues where further research can be conducted in the future.     

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.     

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.     

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.     

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.     

Healing on the cloud: Secure cloud architecture for medical wireless sensor networks

There has been a host of research works on wireless sensor networks (WSN) for medical applications. However, the major shortcoming of these efforts is a lack of consideration of data management. Indeed, the huge amount of high sensitive data generated and collected by medical sensor networks introduces several challenges that existing architectures cannot solve. These challenges include scalability, availability and security. Furthermore, WSNs for medical applications provide useful and real information about patients’ health state. This information should be available for healthcare providers to facilitate response and to improve the rescue process of a patient during emergency. Hence, emergency management is another challenge for medical wireless sensor networks. In this paper, we propose an innovative architecture for collecting and accessing large amount of data generated by medical sensor networks. Our architecture overcomes all the aforementioned challenges and makes easy information sharing between healthcare professionals in normal and emergency situations. Furthermore, we propose an effective and flexible security mechanism that guarantees confidentiality, integrity as well as fine-grained access control to outsourced medical data. This mechanism relies on Ciphertext Policy Attribute-based Encryption (CP-ABE) to achieve high flexibility and performance. Finally, we carry out extensive simulations that allow showing that our scheme provides an efficient, fine-grained and scalable access control in normal and emergency situations.     

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.     

一种分布式能量有效的无线传感器网络分簇路由协议

提出了一种分布式能量有效的无线传感器网络分簇路由协议DEEC(Distributed Energy-efficient Clustering Algorithm)。该协议采用基于时间的簇首选择算法,广播时间取决于自身剩余能量和其邻居节点的剩余能量。在数据传输阶段,采用簇内单跳与簇间多跳相结合的方式,引入权值函数优化簇首中继节点的选择。仿真实验结果表明,与LEACH,PEGASIS协议相比,DEEC能够有效地节约单个节点能量、均衡网络能耗、延长网络生存周期。     

无线传感器网络动态重传算法

无线传感器网络路由协议通过点到点的重传来提高数据传输的可靠性,其重传机制没有考虑不同业务数据的可靠性需求差异,统一设定一个静态的最大重传次数。本文提出了一种动态重传算法,为每种业务分别根据其可靠性需求动态设定最大重传次数。对于较低可靠性需求的业务,相比于传统重传机制减少了重传次数。仿真表明动态重传算法能有效降低网络能耗。     

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.     

基于锚节点的无线传感器网络分簇路由协议

该协议假设在观察区域内配置锚节点并随机抛洒普通节点,它包含分簇和路由两个部分.分簇过程是分布式的,采用从锚节点开始逐级分层的策略将网络分为3层,各节点感知邻居节点的信号强度并确定后继节点,然后将这些信息传送至锚节点;在路由过程中,通过分析上述信息,产生各簇的中转路径和冲突模式,于是路由调度方案由锚节点集中完成.实验结果显示,各簇结构均衡,簇内结构清晰,路由调度方案的产生简单高效.