A new genetic-based approach for maximizing network lifetime in directional sensor networks with adjustable sensing ranges

In recent years, the directional sensor networks have been attractive to researchers due to their wide and different applications. These networks normally contain a number of self-configurable directional sensors holding adjustable spherical sectors with limited angle. One of the most significant problems in such networks is how to monitor the targets scattered in these networks using sensors with adjustable sensing range and, at the same time, maximize the network lifetime. This problem is recognized as Maximum Network Lifetime With Adjustable Ranges; it has been already proved as an NP-complete problem. As an efficient solution to this problem, the present paper proposes a target-oriented GA-based algorithm that can form cover sets comprising sensors with appropriate directions and sensing ranges in a way to desirably monitor all targets in the network. We examined the efficiency of the proposed algorithm by comparing its obtained results with those of a greedy-based one introduced recently in literature. The comparative results confirmed the efficient performance of the proposed algorithm and also its superiority over the greedy-based algorithm in terms of extending the network lifetime.     

Optimal movement of mobile sensors for barrier coverage of a planar region

Intrusion detection, area coverage and border surveillance are important applications of wireless sensor networks today. They can be (and are being) used to monitor large unprotected areas so as to detect intruders as they cross a border or as they penetrate a protected area. We consider the problem of how to optimally move mobile sensors to the fence (perimeter) of a region delimited by a simple polygon in order to detect intruders from either entering its interior or exiting from it. We discuss several related issues and problems, propose two models, provide algorithms and analyze their optimal mobility behavior.     

一种蚁群优化的WSN分布式入侵检测模型

针对无线传感器网络中入侵者能在多个节点上移动并隐藏攻击源头的特点,提出了一种基于蚁群优化的无线传感器网络分布式入侵检测模型。分析了现有入侵检测对未知攻击检测率和误报率方面的不足,在此基础上提出了分布式入侵检测的体系结构,设计了基于蚁群优化的入侵检测算法。仿真实验表明提出的方案能够提高无线传感器网络对未知攻击的检测率和降低对正常网络流量的误报率,较好地解决了路由攻击、Sinkhole攻击问题,能够降低入侵检测的能耗。     

入侵轨迹建模与WSN栅栏覆盖分段调度算法研究

无线传感器网络栅栏覆盖在入侵检测方面发挥着重要作用,如何调度栅栏并延长网络的生存时间已成为重点研究问题.在无线传感器网络中设计合理的调度算法,分时激活传感器节点从而延长网络生存时间是大多数研究的方向,然而仅仅通过分时调度传感器节点已很难大幅度提高网络的生存时间.因此设计了一种分时与分段相结合的无线传感器网络栅栏调度算法,该算法通过分析入侵目标穿越传感器网络部署区域的行为特征,建立入侵目标的轨迹模型,该模型在保证栅栏对入侵目标具有较高检测率的情况下预测入侵目标可能穿越栅栏的区域并分段激活栅栏从而大大减少了传感器节点的能量消耗.最后仿真实验验证了本文算法与传统的分时调度算法相比能大幅度提高网络的生存时间.     

Optimal energy allocation in heterogeneous wireless sensor networks for lifetime maximization

We consider the problem of optimal energy allocation and lifetime maximization in heterogeneous wireless sensor networks. We construct a probabilistic model for heterogeneous wireless sensor networks where sensors can have different sensing range, different transmission range, different energy consumption for data sensing, and different energy consumption for data transmission, and the stream of data sensed and transmitted from a sensor and the stream of data relayed by a sensor to a base station are all treated as Poisson streams. We derive the probability distribution and the expectation of the number of data transmissions during the lifetime of each sensor and the probability distribution and the expectation of the lifetime of each sensor. In all these analysis, energy consumption of data sensing and data transmission and data relay are all taken into consideration. We develop an algorithm to find an optimal initial energy allocation to the sensors such that the network lifetime in the sense of the identical expected sensor lifetime is maximized. We show how to deal with a large amount of energy budget that may cause excessive computational time by developing accurate closed form approximate expressions of sensor lifetime and network lifetime and optimal initial energy allocation. We derive the expected number of working sensors at any time. Based on such results, we can find the latest time such that the expected number of sensors that are still functioning up to that time is above certain threshold.     

A novel intrusion detection framework for wireless sensor networks

Vehicle cloud is a new idea that uses the benefits of wireless sensor networks (WSNs) and the concept of cloud computing to provide better services to the community. It is important to secure a sensor network to achieve better performance of the vehicle cloud. Wireless sensor networks are a soft target for intruders or adversaries to launch lethal attacks in its present configuration. In this paper, a novel intrusion detection framework is proposed for securing wireless sensor networks from routing attacks. The proposed system works in a distributed environment to detect intrusions by collaborating with the neighboring nodes. It works in two modes: online prevention allows safeguarding from those abnormal nodes that are already declared as malicious while offline detection finds those nodes that are being compromised by an adversary during the next epoch of time. Simulation results show that the proposed specification-based detection scheme performs extremely well and achieves high intrusion detection rate and low false positive rate.     

Aggregated mobility-based topology inference for fast sensor data collection

We investigate the problem of efficient data collection in wireless sensor networks where both the sensors and the sink move. We especially study the important, realistic case where the spatial distribution of sensors is non-uniform and their mobility is diverse and dynamic. The basic idea of our protocol is for the sink to benefit of the local information that sensors spread in the network as they move, in order to extract current local conditions and accordingly adjust its trajectory. Thus, sensory motion anyway present in the network serves as a low cost replacement of network information propagation. In particular, we investigate two variations of our method: a) the greedy motion of the sink towards the region of highest density each time and b) taking into account the aggregate density in wider network regions. An extensive comparative evaluation to relevant data collection methods (both randomized and optimized deterministic), demonstrates that our approach achieves significant performance gains, especially in non-uniform placements (but also in uniform ones). In fact, the greedy version of our approach is more suitable in networks where the concentration regions appear in a spatially balanced manner, while the aggregate scheme is more appropriate in networks where the concentration areas are geographically correlated. We also investigate the case of multiple sinks by suggesting appropriate distributed coordination methods.     

Minimizing mobile sensor movements to form a line K-coverage

In wireless sensor networks and social networks, distributed nodes usually form a network with coverage ability for a lot of applications, such as the intrusion detection. In this paper, a new kind of coverage problem with mobile sensors is addressed, named Line K-Coverage. It guarantees that any intruder trajectory line cutting across a region of interest will be detected by at least K sensors. For energy efficiency, we aim to schedule an efficient sensor movement to satisfy the line K-coverage while minimizing the total sensor movements, which is named as LK-MinMovs problem. We firstly construct two time-efficient heuristics named LK-KM and LK-KM+ based on the famous Hungarian algorithm. By sacrificing optimality a little bit, these two algorithms have better time efficiency. Then we propose a pioneering layer-based algorithm LLK-MinMovs to solve LK-MinMovs in polynomial time. Here, we assume that all sensors are initially located in a closed region. We validate its correctness by theoretical analysis. Later, the more general situation are considered that all sensors are allowed to locate outside of the region. We improve LLK-MinMovs algorithm to the general version: GenLLK-MinMovs. More importantly, our GenLLK-MinMovs fixes a critical flaw for MinSum algorithm which was proposed by previous literature to solve line 1-coverage problem. We show the flaw using a counter example. Finally, we validate the efficiency of all our designs by numerical experiments and compare them under different experiment settings.     

Distributed Kalman filtering via node selection in heterogeneous sensor networks

In this paper, we propose a strategy for distributed Kalman filtering over sensor networks, based on node selection, rather than on sensor fusion. The presented approach is particularly suitable when sensors with limited sensing capability are considered. In this case, strategies based on sensor fusion may exhibit poor results, as several unreliable measurements may be included in the fusion process. On the other hand, our approach implements a distributed strategy able to select only the node with the most accurate estimate and to propagate it through the whole network in finite time. The algorithm is based on the definition of a metric of the estimate accuracy, and on the application of an agreement protocol based on max-consensus. We prove the convergence, in finite time, of all the local estimates to the most accurate one at each discrete iteration, as well as the equivalence with a centralised Kalman filter with multiple measurements, evolving according to a state-dependent switching dynamics. An application of the algorithm to the problem of distributed target tracking over a network of heterogeneous range-bearing sensors is shown. Simulation results and a comparison with two distributed Kalman filtering strategies based on sensor fusion confirm the suitability of the approach.     

Mobility Limited Flip-Based Sensor Networks Deployment

An important phase of sensor networks operation is deployment of sensors in the field of interest. Critical goals during sensor networks deployment include coverage, connectivity, load balancing, etc. A class of work has recently appeared, where mobility in sensors is leveraged to meet deployment objectives. In this paper, we study deployment of sensor networks using mobile sensors. The distinguishing feature of our work is that the sensors in our model have limited mobilities. More specifically, the mobility in the sensors we consider is restricted to a flip, where the distance of the flip is bounded. We call such sensors as flip-based sensors. Given an initial deployment of flip-based sensors in a field, our problem is to determine a movement plan for the sensors in order to maximize the sensor network coverage and minimize the number of flips. We propose a minimum-cost maximum-flow-based solution to this problem. We prove that our solution optimizes both the coverage and the number of flips. We also study the sensitivity of coverage and the number of flips to flip distance under different initial deployment distributions of sensors. We observe that increased flip distance achieves better coverage and reduces the number of flips required per unit increase in coverage. However, such improvements are constrained by initial deployment distributions of sensors due to the limitations on sensor mobility     

Coverage boundary of unknown environment using mobile sensor networks

In this article, we consider the problem of optimal coverage of unknown environmental boundary using sensor networks. Since the boundary is unknown to all sensors, it is necessary for the sensors to find it first. We give a new distributed estimate policy by tracking a virtual agent using the sensor networks. Then we consider the problem of optimal coverage of the estimate boundary instead of the actual one. Moreover, an algorithm is given to deploy the sensors to the optimal configuration corresponding to the coverage problem considered in this article.     

基于静态和移动传感器的WSN的k-覆盖研究

针对无线传感器网络的k-覆盖问题进行了研究。首先定义一个表征网络覆盖效率的过度提供因子,并在此基础上对静态传感器网络和全移动传感器网络的k-覆盖问题进行分析,得到这两种情形下的过度提供因子以及全移动传感器网络中移动传感器的最大移动距离;进而提出一种由静态传感器和少量移动传感器构成的混合网络结构,并得到了这种网络结构下不依赖于网络大小的k-覆盖以及调度移动传感器移动的分布式移动调度算法,从而实现有效覆盖。仿真结果表明,提出的混合网络结构不仅能够实现精确的k-覆盖,而且相比于其他k-覆盖算法,有更高的覆盖率。     

分布式无线传感器网络容错事件边界检测

事件监测是无线传感器网络的一种重要应用。针对该应用中软故障节点提供的错误数据会降低监测的准确性的问题,提出了一种分布式的容错事件边界检测算法。节点只需与邻节点交换一次传感数据,通过简单地计算识别故障;正常的事件节点利用统计比较的方法判断其是否处于事件边界,边界宽度可根据网络用户的要求调节。该算法执行时所需的通信量小,计算复杂度低,时延小,对大规模网络具有很好的可扩展性。仿真结果表明即使节点故障率很高,应用该算法仍可以获得很好的检测效果。     

综合覆盖调度的无线传感器网络跨层路由研究

无线传感器网络由大量微小的传感器节点构成,各节点协作完成环境现象的分布式感知。覆盖控制作为无线传感器网络中的一个基本问题,反映了网络所能提供的"感知"服务质量。基于现有的集中式计算覆盖集合算法MLMC,通过改变计算覆盖集合条件,结合能量不均衡消耗的I-RDDD协议,观察了网络生存期的变化。仿真结果和分析表明,基于能量考虑和单组覆盖集合轮询的工作方式能获得更长的网络生存期。     

基于非均匀成簇的无线传感器网络多跳路由算法

针对复杂、不规则场景下无线传感网络的高效能组网问题,提出了一种基于非均匀成簇的无线传感器网络多跳路由算法MRAUC。根据应用场景形状不规则、汇聚节点远离检测区域等特点,首先将检测区域近似成汇聚节点位于扇心的扇环,建立了扇型场景下无线传感器网络的非均匀成簇模型;通过等间隔划分扇环,以第一扇环能耗最小为原则确定各扇环的簇首数目,进一步推导出各扇环内的最佳簇首比例;通过簇首发射功率的自适应调整实现非均匀分簇;同时,以MTE原则竞选出最佳中继簇首,有效解决了簇首间的路由中继问题。仿真结果表明,与传统算法相比,在不同应用场景下所提MRAUC算法在均衡网络节点能耗、延长网络生命周期方面具有显著优势,更适用于工程实际。     

多等级通信半径的无源传感器网络中的覆盖问题

无源传感器网络是近年来兴起的一种新型的网络结构,可用于解决传统无线传感器网络能量有限、寿命受限的问题.在无源传感器网络中,每个无源传感器节点配备有能量收集模块,可以从周围环境中获取能量.由于周围环境中的能量是无限的,这样,从能量的角度来讲,无源传感器网络的网络寿命是无限的.这样就解决了传统无线传感器网络寿命受限的问题.然而,由于周围环境中的能量源具有能量低、分布不均匀等特点,导致无源传感器网络中的覆盖问题比传统的无线传感器网络中的覆盖问题更加复杂.为了解决无源传感器网络中的覆盖问题,同时也为了让无源节点更有效地利用环境中的能量,考虑了一种具有多等级通信半径的无源节点,并提出了基于多等级通信半径的无源传感器网络中的覆盖问题.证明了这个问题是NP-Hard问题.提出一种基于贪心策略的近似算法,解决了这个问题,并证明了该算法的近似比.同时,采用模拟实验的方式验证了该算法的性能.根据实验结果,该算法是有效且可靠的.     

无线传感器网络一种不相交路径路由算法

无线传感器网络经常被用来采集物理数据,监测环境变化.由于低功耗无线通信不确定性、链路质量不稳定性以及节点失效等问题,传感器网络很容易导致路由数据包丢失.为了提高网络路由的可靠性,人们提出多路径路由算法.多路径路由中源节点到目的节点的多条路径可能含有公共节点,或者公共边,如果公共节点或者公共链路失效,则这个数据包也丢失,因此又有人提出不相交多路径路由算法.不相交多路径路由算法又分为链路不相交多路径路由算法和节点不相交多路径路由算法.提出了一种不相交路径路由算法,可以将感知节点采集到的数据通过不相交路径传送到汇聚节点,提高路由的可靠性.而且,这个算法还可以很方便地应用到多Sink节点的网络当中.该路由算法用到的路由表大小为|K|,其中|K|表示路径数.算法的运行时间复杂度是O(|L|),其中|L|表示网络中的边数.     

基于体心立方格的三维传感器网络部署与组织

三维传感器网络有着重要的应用前景,而目前传感器网络的研究主要集中在二维。针对传感器节点在空间中的部署和组织,本文提出一种体心立方格结构传感器网络的确定部署方法,以及一种基于空间虚拟Voronoi单元的随机部署三维传感器网络的节点组织策略。     

传感器网络中多节点协商可逆的数字水印算法

数字水印技术已被用于保障传感器网络所采集数据的完整性与正确性,已有的无线传感器网络中的水印技术几乎都是不可逆的,因而嵌入的水印会对采集的数据具有一定的破坏。为此,将传统的基于差分扩展的可逆水印算法引入到无线传感器网络,并结合无线传感器网络节点协同工作的特点,将已有基于差分扩展的可逆水印算法发展为多节点协商可逆的数字水印算法。该算法针节点结构松散、自身防御能力弱等问题将整体水印分为一定数目的片段,并由各组节点进行随机化处理使所有的片段呈随机性分布,以增加共谋攻击的难度。同时在节点和终端间用一对同步的随机序列发生器解决了对数据的新鲜性鉴别的问题。     

基于观测器的移动执行器对二维分布参数系统的控制

研究二维分布参数系统在传感器执行器网络下的控制问题.传感器执行器网络由二维平面上固定的传感器与移动的执行器组成.首先,利用传感器对二维分布参数系统的测量信息设计观测器,用来估计二维分布参数系统的状态,并在观测器的基础上给出相应的控制器;然后,利用算子半群理论并结合Lyapunov方法,得到平面上移动的执行器的水平运动速度和垂直运动速度,该速度依赖于观测器的信息;最后,数值仿真表明,二维分布参数系统在该移动执行器控制下的性能得到了有效的提高.