Privacy preserving secure expansive aggregation with malicious node identification in linear wireless sensor networks

The Wireless Sensor Networks(WSNs)used for the monitoring applications like pipelines carrying oil,water,and gas;perimeter surveillance;border monitoring;and subway tunnel monitoring form linearWSNs.Here,the infrastructure being monitored inherently forms linearity(straight line through the placement of sensor nodes).Therefore,suchWSNs are called linear WSNs.These applications are security critical because the data being communicated can be used for malicious purposes.The contemporary research of WSNs data security cannot fit in directly to linear WSN as only by capturing few nodes,the adversary can disrupt the entire service of linear WSN.Therefore,we propose a data aggregation scheme that takes care of privacy,confidentiality,and integrity of data.In addition,the scheme is resilient against node capture attack and collusion attacks.There are several schemes detecting the malicious nodes.However,the proposed scheme also provides an identification of malicious nodes with lesser key storage requirements.Moreover,we provide an analysis of communication cost regarding the number of messages being communicated.To the best of our knowledge,the proposed data aggregation scheme is the first lightweight scheme that achieves privacy and verification of data,resistance against node capture and collusion attacks,and malicious node identification in linear WSNs.

Two-Level Linear Clustering Protocol Based on Wireless Sensor Networks

Aiming at the defects of the nodes in the low energy adaptive clustering hierarchy （LEACH） protocol, such as high energy consumption and uneven energy consumption, a two-level linear clustering protocol is built. The protocol improves the way of the nodes distribution at random. The terminal nodes which have not been a two-level cluster head in the cluster can compete with the principle of equivalent possibility, and on the basis of the rest energy of nodes the two-level cluster head is selected at last. The single hop within the cluster and single hop or multiple hops between clusters are used. Simulation experiment results show that the performance of the two-level linear clustering protocol applied to the Hexi corridor agricultural field is superior to that of the LEACH protocol in the survival time of network nodes, the ratio of success, and the remaining energy of network nodes.

Energy-constrained ferry route design for sparse wireless sensor networks

In recent years,using message ferries as mechanical carriers of data has been shown to be an effective way to collect information in sparse wireless sensor networks.As the sensors are far away from each other in such highly partitioned scenario,a message ferry needs to travel a long route to access all the sensors and carry the data collected from the sensors to the sink.Typically,practical constraints(e.g.,the energy)preclude a ferry from visiting all sensors in a single tour.In such case,the ferry can only access part of the sensors in each tour and move back to the sink to get the energy refilled.So,the energy-constrained ferry route design(ECFRD)problem is discussed,which leads to the optimization problem of minimizing the total route length of the ferry,while keeping the route length of each tour below a given constraint.The ECFRD problem is proved to be NP-hard problem,and the integer linear programming(ILP)formulation is given.After that,efficient heuristic algorithms are proposed to solve this problem.The experimental results show that the performances of the proposed algorithms are effective in practice compared to the optimal solution.

Maximum Data Collection Rate in Rechargeable Wireless Sensor Networks with Multiple Sinks

In rechargeable wireless sensor networks, a sensor cannot be always benefi cial to conserve energy when a network can harvest excessive energy from the environment due to its energy replenished continually and limited energy storage capacity. Therefore, surplus energy of a node can be utilized for strengthening packet delivery efficiency and improving data collection rate. In this work, we propose an algorithm to compute an upper data generation rate that maximizes it as an optimization problem for a network with multiple sinks, which is formulated as a linear programming problem. Subsequently, a dual problem by introducing Lagrange multipliers is constructed, and subgradient algorithms are used to solve it in a distributed manner. The resulting algorithms are guaranteed to converge to an optimal data generation rate, which are illustrated by an example in which an optimum data generation rate is computed for a network of randomly distributed nodes. Through extensive simulation and experiments, we demonstrate our algorithm is efficient to maximize data collection rate in rechargeable wireless sensor networks.

AN ADAPTIVE-WEIGHTED TWO-DIMENSIONAL DATA AGGREGATION ALGORITHM FOR CLUSTERED WIRELESS SENSOR NETWORKS

In this paper,an Adaptive-Weighted Time-Dimensional and Space-Dimensional(AWTDSD) data aggregation algorithm for a clustered sensor network is proposed for prolonging the lifetime of the network as well as improving the accuracy of the data gathered in the network.AWTDSD contains three phases:(1) the time-dimensional aggregation phase for eliminating the data redundancy;(2) the adaptive-weighted aggregation phase for further aggregating the data as well as improving the accuracy of the aggregated data; and(3) the space-dimensional aggregation phase for reducing the size and the amount of the data transmission to the base station.AWTDSD utilizes the correlations between the sensed data for reducing the data transmission and increasing the data accuracy as well.Experimental result shows that AWTDSD can not only save almost a half of the total energy consumption but also greatly increase the accuracy of the data monitored by the sensors in the clustered network.

A Synchronous and Deterministic MAC Protocol for Wireless Communications on Linear Topologies

Linear topology is useful in several pervasive application scenarios. Even though a linear topology can be handled by unspecific routing algorithms over general purpose MAC protocols, better performance can be obtained by specialized techniques. This paper describes a new communication scheme called Wireless Wire (WiWi), which builds up a bidirectional wireless communication channel with deterministic properties in terms of throughput and latency over a strip of pervasive devices with short-range transmission capabilities. The system is synchronous and fault tolerant. With low cost and extremely simple devices, WiWi builds up a “wire-like” dielectric link, but its applications are not limited to end-to-end communications. For example, WiWi can be used to collect data from sensors along the path, thus acting as a virtual conveyor belt.

Efficient Algorithm for K-Barrier Coverage Based on Integer Linear Programming

Barrier coverage of wireless sensor networks is an important issue in the detection of intruders who are attempting to cross a region of interest.However,in certain applications,barrier coverage cannot be satisfied after random deployment.In this paper,we study how mobile sensors can be efficiently relocated to achieve k-barrier coverage.In particular,two problems are studied:relocation of sensors with minimum number of mobile sensors and formation of k-barrier coverage with minimum energy cost.These two problems were formulated as 0–1 integer linear programming(ILP).The formulation is computationally intractable because of integrality and complicated constraints.Therefore,we relax the integrality and complicated constraints of the formulation and construct a special model known as RELAX-RSMN with a totally unimodular constraint coefficient matrix to solve the relaxed 0–1 ILP rapidly through linear programming.Theoretical analysis and simulation were performed to verify the effectiveness of our approach.

铁路沿线线型无线传感器网络高效路由协议

为防止网络“热区”现象,针对铁路沿线无线传感器网络多呈线型分布的结构特点,提出一种基于服务质量的能耗均衡分簇路由协议(ECRPQ)。首先,部署网络节点,计算节点能量消耗,建立能耗均衡的非均匀节点部署模型并进行网络分簇。然后,设计路由协议,在簇首选举时引入节点动态剩余能量和节点担任簇首轮次的影响因素,在通信阶段采用TDMA机制和CDMA机制相结合的方式,在进行时间同步校准时严格保证簇内节点时间同步。最后,通过MATLAB进行仿真实验,从网络生命周期、网络吞吐量和节点平均时延3个方面将ECRPQ与LEACH、LEACH-C这2种经典协议进行对比。结果表明:当网络节点总数为200个时,ECRPQ的网络生命周期明显更长,达到600 s;ECRPQ的网络吞吐量更大,分别比LEACH和LEACH-C提高128.7%和84.6%;ECRPQ的节点平均时延更低,分别比LEACH和LEACH-C降低52.8%和43.2%。

频率互异多相位粒度线性脉冲耦合WSN时间同步模型

针对无线传感器网络在运行过程中,传感器节点晶振频率的一致性难以保证而影响时间同步的问题,提出一种基于频率互异的多相位粒度线性脉冲耦合无线传感器时间同步模型。首先基于萤火虫同步机制,在无线传感器网络中采用去中心化的脉冲激励耦合方式,考虑每一个节点可能存在频率的差异,构建出表征不同振荡频率的动态方程。其次对两个振荡器和多振荡器系统进行数学分析,跟踪同步演进过程得出同步条件。最后通过仿真实验,验证了所提模型在节点频率不一致的无线传感器网络中能够实现稳定的同步状态,并且较未考虑频率变化的线性脉冲耦合振荡器同步模型具有更快的同步收敛速度。

一种新型的无线传感器网络能效路由算法

为了解决重复分簇而加剧能量消耗的问题,提出了一种新的无线传感器网络能效路由算法——基于簇树的非均匀分簇路由算法(UCCT)。该算法分为两步。第一步,划分网络区域为面积不相等的两个区域,对每个区域内的节点集,利用K-中心算法确定其质心节点;以每个质心作为一个簇,计算其中继能耗开销;确定各簇间的通信路由。第二步,利用线性规划方法来确定非质心节点所属的簇,选取各簇中剩余能量最高的节点为相应的簇头。该算法的特点是无须重复分簇。仿真结果表明,与ANRB相比,采用UCCT进行通信路由,无线传感器网络的寿命延长10.97%,数据吞吐量提高了13.09%。

煤矿井下线型无线传感器网络节点定位算法

针对煤矿井下线型无线传感器网络节点定位精度较低的问题,提出了基于RSSI(接收信号强度指示)的对角差分修正定位算法。该算法在对线型无线传感器网络节点定位的横向和纵向误差进行分析的基础上,首先利用差分原理对测量距离进行修正,并使用极大似然估计法进行初步定位;然后应用信标节点构建煤矿井下巷道模型,在该模型下对移动节点进行横向修正。仿真结果表明,该算法较传统的极大似然估计算法具有较高的定位精度和稳定性,适用于煤矿井下线型无线传感器网络节点定位。

0.13 μm CMOS Stacked-FET两级功率放大器设计

基于TSMC 0.13μm CMOS工艺设计了一款适用于无线传感网络、工作频率为300~400 MHz的两级功率放大器。功率放大器驱动级采用共源共栅结构,输出级采用了3-stack FET结构,采用线性化技术改进传统偏置电路,提高了功率放大器线性度。电源电压为3.6 V,芯片面积为0.31 mm×0.35 mm。利用Cadence Spectre RF软件工具对所设计的功率放大器电路进行仿真,结果表明,工作频率为350 MHz时,功率放大器的饱和输出功率为24.2 d Bm,最大功率附加效率为52.5%,小信号增益达到38.15 d B。在300~400 MHz频带内功率放大器的饱和输出功率大于23.9 d Bm,1 d B压缩点输出功率大于22.9 d Bm,最大功率附加效率大于47%,小信号增益大于37 d B,增益平坦度小于±0.7 d B。

线性无线传感器网络能耗均衡算法

在中继节点等间距线性部署的无线传感器网络中,所有普通节点的能耗不均衡,因而网络过早死亡.为解决这个问题,在综合考虑所有普通节点能耗的基础上,提出一种网络能耗均衡算法.算法采用改进的粒子群算法对网络中中继节点的位置进行优化,适应度函数选取普通节点的能耗值的标准差.首先采用自适应的动态惯性权重替代基本粒子群算法的静态权重,加快了其收敛速度;然后利用提出的迭代多阶段粒子群算法优化中继节点的位置,均衡普通节点的能耗.仿真实验结果表明经改进后的粒子群优化的网络,能耗更为均衡,网络的生存周期得以延长.

线型无线传感器网络中一种联合优化中继节点选择策略

在无线传感器网络中,时延与功耗性能往往是一对不可兼得的指标,如何优化和平衡这两个指标是路由和MAC算法中的难点。线型无线传感器网络由于拓扑结构的线型性,功耗-时延的均衡问题显得更加突出。基于线型无线传感器网络拓扑模型,理论分析了能耗最优传输距离,然后基于节点剩余能量,构建联合优化目标函数。进一步地,将数据包类型在时间敏感性方面分为紧急数据包和普通数据包,并相应调整发射功率,以便在当前通信范围内找到最优下一跳中继节点。最终提出了一个功率可调的时延-能耗自适应优化中继节点选择算法(LEARS)。通过仿真实验将该算法与经典及类似算法比较,LEARS能够在保证紧急数据包传输实时性的同时,进一步降低网络的整体功耗,延长网络的生命周期。

基于L-WSNs的货运列车轴承在线监测方法

针对货运列车的结构与运行特点,应用线性无线传感器网络(linear wireless sensor networks,L-WSNs),提出货运列车轴承在线监测方法,并开发监测系统。研究并解决网络路由协议、振动数据压缩编码传输以及Zigbee节点设计3个关键问题,在高速电主轴转子及液压系统上进行振动与温度信号组网监测试验,并分析试验结果及节点能耗,最后预估节点寿命。试验与分析结果表明:监测系统可同时实现4路振动及温度信号的同步采集与组网传输,实时性好、误码率低;同时,网络节点能耗与寿命也满足系统要求。

基于改进PSO的铁路监测线性无线传感器网络路由算法

为了解决铁路监测场景中线性无线传感器网络的节点间能耗不均衡导致的网络生命周期短、数据传输时延大的问题,提出了一种基于粒子群优化理论和广度优先搜索的路由算法。以候选簇头节点的相对能耗、簇头间距和簇头负载为指标构建适应度函数,通过调整惯性权重系数增强粒子群算法局部搜索能力,获得簇头最优解集;构建能耗与时延驱动的路径成本函数,基于广度优先搜索获得源节点到sink节点的最优主路径;设计基于Markov决策过程(MDP)模型的Q-learning备选路径更新与路由维护机制。仿真结果表明,所提算法能够有效均衡节点间能耗,在延长网络生命周期和降低数据传输时延方面具有较优的性能。

节点位置固定的线性无线传感器网络节能路由

无线传感器网络节点一般采用电池供电,能量非常有限,因此提高网络能量效率、最大化网络生命周期成为亟待解决的重要问题。线性无线传感器网络在某些实际应用中,由于监测环境和对象的特殊性,监测点位置往往是事先确定的,并非随机分布,故现有的线性路由和变距离节点布置方案应用性受限。针对这一问题,提出了一种等距离分组多跳路由,建立了其能耗数学模型,得到了网络平均能耗与网络长度、节点数和分组数的数学关系,并给出了最小网络平均能耗下的分组数求解方法,最后用Matlab软件仿真分析。结果表明,与单跳、多跳、分簇多跳三种常见路由相比,等距离分组多跳路由由于没有簇头,因此具有最小的网络平均能耗和最大的网络生命周期。

基于AOA的无线传感器网络节点定位算法

在无线传感器网络节点SDP定位算法基础上，提出了一种改进的基于信号到达角（AOA）信息的无线传感器网络节点自身定位算法。本算法在所有节点的坐标轴方向都是未知的假定下，将AOA测量值用于计算信号到达差分角信息，将所有节点之间的角度关系表述为凸规划约束条件，从而将定位问题转化为一个凸集优化问题。在理想情况下，将定位问题转化为一个线性规划问题。实际情况中，考虑到测量误差，通过引入辅助变量，将定位问题转化为一个二次规划问题。仿真结果表明：改进算法与原算法相比，对AOA测量误差在10°以下时，定位精度提高约为5％～20％。

线状WSN中基于概率分流的负载均衡路由协议

针对线状无线传感器网络中节点能量消耗不均衡现象,本文提出基于概率分流的负载均衡路由协议,以一定规则建立多条路由路径,通过使负载较轻路径上的节点以一定概率分担负载较重路径上节点的数据传输任务,均衡网络中各个节点的负载。仿真结果表明,本协议能有效地改善各个节点能量消耗的均衡性,延长网络生存时间。

机械振动无线传感器网络数据分块大小研究

机械振动无线传感器网络节点因存储容量有限、信道带宽窄导致节点需将高采样频率下产生的大量振动数据进行分块存储、读取与发送,而数据分块大小将直接影响数据存储、读取与发送能耗。为研究各过程数据分块大小与能耗的关系,首先通过实验得出数据存储、读取与发送过程中工作电流、工作时间与数据分块大小间离散关系;然后利用最小二乘法对离散关系进行线性拟合,建立各过程能耗数学模型,结合处理器自身存储容量与通信协议物理层载荷等限制因素,得出使各过程能耗最低的数据分块大小。对比实验结果表明,各过程均采用最优数据分块大小能有效降低机械振动无线传感器网络节点能耗。