基于感知网格的无线传感器网络动态采样策略

在分析无线传感器网络时空相关性模型的基础上,提出一种基于感知网格的无线传感器网络动态采样策略.将监测区域划分为多个感知网格,感知网格内只有簇头节点保持活跃状态,当出现异常数据后再激活感知网格内其他节点来获得更详细的信息.该策略通过减少无线传感器节点之间相同的或相近的采样数据上传来降低冗余信息的传输.仿真结果表明:该策略显著提高了无线传感器网络能量效率.     

一种基于顺序博弈的UWSNs覆盖控制算法

近年来,人们对海洋资源愈加重视,水下无线传感器网络在海洋数据监测、海洋军事、辅助导航等方面的应用引起了广泛关注。一个良好的水下无线传感器网络覆盖控制,首先能够降低覆盖冗余,优化网络空间资源的配置;其次可以减少节点的能耗、降低网络的成本并延长节点的生命周期,使水下无线传感器网络可以更好地完成目标水域环境感知任务。提出了一种基于顺序博弈的水下无线传感器网络覆盖控制方法,用于优化水下无线传感器网络的覆盖控制,期望能够降低节点的能耗,均衡节点之间的能量,最终实现延长网络的生命周期的目标。仿真实验表明,该算法能够提高网络覆盖率和延长网络生命周期。     

多节点协同传输无线传感器网络数据收集协议

为了使无线传感器网络在执行数据收集任务时付出更小的能量代价,并延长网络的生命周期,提出一种多节点协同传输的无线传感器网络数据收集协议(MCTP).协议通过考虑节点在覆盖问题上的能量优化问题,采取节点交替协作的模式来使覆盖重叠面积较大的节点之间进行睡眠模式切换,节省能量消耗.在数据转发过程中,采用簇头间协同传输的方法来最小化路由损耗并均衡簇头能量负载.仿真结果表明,MCTP算法在降低簇头节点的平均能量损耗,延长簇头节点平均生命周期上具有较好效果.     

视频传感器网络内容相关性感知的通信协议研究

无线视频传感器网络中节点的能量有限,如何充分利用有限的能量是当前的一个研究热点.提出了一种基于内容相关性感知的视频传感器网络通信协议(VCCP),通过数学建模对典型的WSN路由协议进行优化,在保证视频传输质量的前提下,将冗余数据进行适当压缩,目的是节约网络带宽、降低能量消耗、延长网络的生命周期.另外,为了尽可能提高监测区域整体覆盖率以及解决局部覆盖率“骤降”问题,分别提出了对节点感知角度调整和“伪簇头”的优化方案.仿真结果表明,VCCP延长了网络生命周期,且在一定程度上提高了监测区域覆盖率.     

基于网络编码的异构无线传感器网络数据广播协议

本文提出一种适应异构无线传感器网络的能量感知的网络编码数据广播协议(ENCBP)。传感器节点根据邻居能量信息列表实时地计算节点剩余能量的线性映射值。在此基础上,采用能量感知的网络编码转发概率机制,使具有较高剩余能量的节点比低能量节点拥有更高的数据转发优先级,以实现能量均衡的数据传输。另外,采用伪广播机制对协议进行优化,以提高数据包投递率。仿真结果表明,ENCBP不仅可以有效实现网络的能耗均衡,以延长网络的生命周期,还能在一定程度上降低数据包传输时延,从而提高数据通信性能。     

非均匀部署WSN的能量空洞避免策略

分析无线传感器网络中各个节点位置上的数据及能量负载,提出一种新的非均匀部署策略,在网络中均匀部署满足监测需要的工作节点,但在近sink区域部署更多不感知数据,只转发数据的中继节点,以实现网络的能量消耗均衡,并分析传感器节点最优传输半径优化问题。实验结果表明,该策略能够有效降低网络能耗,延长网络寿命。     

一种无线传感器网络非线性抽样能耗优化方案

无线传感器网络现有的各种能耗优化技术大多隐含假设应完整地收集和传递感知数据,从而侧重于信息收集和传输过程的能量节约和能耗平衡.提出了一种新的能耗优化方案,首先利用感知相关性完成监控同一目标的所有传感器的完全聚类;然后根据类内节点感知数据的空域相关性与事件源活动的随机性,在保证应用精度的前提下,非线性地选取感知数据收集节点,仿真结果表明方案能够充分削减感知数据中冗余细节的收集和传输,大大降低活动事件源监控节点的能耗,延长网络寿命.     

基于动态触发和协同的WSN节点寿命优化

网络能耗和能量均衡决定了无线传感器网络(WSN)的生存时间,为克服静态信息传输下单一节点工作量对网络生存时间的制约,延长无线传感器网络节点生命周期,提出了一种基于动态触发和协同操作的信息优化传递方式.借助可行性定理,确定多条可行的信息传递路径;网络在静态信息传输方式下以某条路径传递信息,当能量消耗过多、数据流量过大的跳跃节点能耗至一定程度时,通过触发机制使多条路径动态协同工作,以此降低节点的信息吞吐量,实现节点能耗均匀化,延长节点的生命周期,保证网络的有效性;并对各条路径工作时间的确定给出了最优的解决方法.通过Matlab仿真表明,动态触发机制下的协同传输有效的延长了网络寿命,同时提高了网络能量利用率.     

无线传感器网络中近似事件检测节点调度问题

在异构的无线传感器网络中,组成事件的不同类型的数据之间具有较强的相关性.为了减少能量的消耗,可以通过收集组成事件的部分感知数据来近似地检测该事件.提出近似事件检测的节点调度问题.将网络中的节点分成若干个集合,每个集合轮流工作,在保证收集到的部分数据能够有效地近似检测目标事件的同时,最大化网络的生命周期.证明了近似事件检测的节点调度问题是NP完全问题,并给出了基于贪心策略的近似比为1/2的近似算法.实验结果表明,方法能够有效延长网络的生命周期.     

无线传感器网络中事件驱动的能量均衡多流聚合路由算法

如何在均衡地使用监测节点能量的同时降低监测数据的回传时延是无线传感器网络被动式路由研究中亟待解决的一个难点.综合网络传输快速性与能量均衡性需求,针对过程特征性事件,提出一种能量均衡的多流聚合路由算法（EB-MPA）.该算法依据网络层次图选举区域中心节点,降低了数据到达基站的延迟.另外,EB-MPA引入能量耗损代价作为节点单跳路由选择的指标,在节点具备融合能力的情形下,进一步均衡了能量开销,延长了网络生命周期.     

DLRDG: distributed linear regression-based hierarchical data gathering framework in wireless sensor network

For many applications in wireless sensor network (WSN), the gathering of the holistic sensor measurements is difficult due to stringent constraint on network resources, frequent link, indeterminate variations in sensor readings, and node failures. As such, sensory data extraction and prediction technique emerge to exploit the spatio-temporal correlation of measurements and represent samples of the true state of the monitoring area at a minimal communication cost. In this paper, we present DLRDG strategy, a distributed linear regression-based data gathering framework in clustered WSNs. The framework can realize the approximate representation of original sensory data by less than a prespecified threshold while significantly reducing the communication energy requirements. Cluster-head (CH) nodes in WSN maintain linear regression model and use historical sensory data to perform estimation of the actual monitoring measurements. Rather than transmitting original measurements to sink node, CH nodes communicate constraints on the model parameters. Relying on the linear regression model, we improved the CH node function of representative EADEEG (an energy-aware data gathering protocol for WSNs) protocol for estimating the energy consumption of the proposed strategy, under specific settings. The theoretical analysis and experimental results show that the proposed framework can implement sensory data prediction and extracting with tolerable error bound. Furthermore, the designed framework can achieve more energy savings than other schemes and maintain the satisfactory fault identification rate on case of occurrence of the mutation sensor readings.     

无线传感器网络中能量有效自适应路由算法研究

针对无线传感器网络寿命最大化问题,基于无线传感器节点能耗分布特点和数据传输能耗模型,建立无线传感器网络生存周期的数学优化模型,并针对最小能耗路由的能耗不均衡问题和能量均衡路由的能耗开销问题,综合考虑网络中节点的剩余能量和节点间发送数据的能耗,提出一个适合无线多跳传感器网络的自适应路由算法。仿真结果表明,提出的路由算法能充分地利用有限的能量资源,较大地延长网络生存周期。     

Bio-inspired data transmission scheme to multiple sinks for the long-term operation of wireless sensor networks

Wireless sensor networks have a wide range of applications, such as natural environmental monitoring, object tracking, and environmental control in residential spaces or plants. In wireless sensor networks, many sensor nodes with limited resources are placed in an observation area and used to gather information about environments. Therefore, a data gathering scheme (or a routing algorithm) for saving and balancing the energy consumption of each sensor node is needed to prolong the lifetime of wireless sensor networks. This article proposes a new bio-inspired data transmission scheme for the long-term operation of wireless sensor networks. By using the proposed scheme, autonomous load-balancing data transmission to multiple sinks can be actualized. We evaluate the proposed scheme using computer simulations to verify its effectiveness, and also discuss its development potential.     

分布式粒子滤波实现无线传感器网络目标跟踪

为了延长无线传感器网络寿命,减小通信代价,提出一种层次型网络结构下基于粒子滤波的分布式跟踪算法.层次型网络由簇头节点和普通传感节点组成,簇头节点采用粒子滤波获得目标运动状态,联合当前时刻目标的本地估计位置、预测速度预测下一时刻的目标位置.并根据目标的预测位置判断是否转移簇首.目标离开节点探测范围后,节点进入休眠状态.实验表明,该方法能满足目标跟踪精度,并可有效的减少网络能耗,提高无线传感器网络使用寿命.     

基于蚁群的无线传感网最大化生存时间路由

为提高无线传感网的生存时间,对基于蚁群算法的最大化生存时间路由(MLRAC)进行了研究。该路由利用链路能耗模型和节点发送数据概率,计算一个数据收集周期内节点总能耗。同时考虑节点初始能量,建立了最大化生存时间路由的最优模型。为求解该最优模型,在经典蚁群算法的基础上,提出修正的蚁群算法。该算法采用新的邻居节点转发概率公式、信息素更新公式和分组探测方法,经过一定的迭代计算获得网络生存时间的最优值和每个节点的最优发送数据概率。最后,Sink节点洪泛通知网络中所有节点。节点根据接收到的最优概率,选择数据分组未经过的邻居节点发送数据。仿真实验表明,经过一定时间的迭代,MLRAC的生存时间可以收敛到最优值。该算法能延长网络生存时间,在一定的条件下,MLRAC算法比PEDAP、LET、Ratio-w、Sum-w等算法更优。     

Balancing Energy Consumption to Maximize Network Lifetime in Data-Gathering Sensor Networks

Unbalanced energy consumption is an inherent problem in wireless sensor networks characterized by multihop routing and many-to-one traffic pattern, and this uneven energy dissipation can significantly reduce network lifetime. In this paper, we study the problem of maximizing network lifetime through balancing energy consumption for uniformly deployed data-gathering sensor networks. We formulate the energy consumption balancing problem as an optimal transmitting data distribution problem by combining the ideas of corona-based network division and mixed-routing strategy together with data aggregation. We first propose a localized zone-based routing scheme that guarantees balanced energy consumption among nodes within each corona. We then design an offline centralized algorithm with time complexity O(n) (n is the number of coronas) to solve the transmitting data distribution problem aimed at balancing energy consumption among nodes in different coronas. The approach for computing the optimal number of coronas in terms of maximizing network lifetime is also presented. Based on the mathematical model, an energy-balanced data gathering (EBDG) protocol is designed and the solution for extending EBDG to large-scale data-gathering sensor networks is also presented. Simulation results demonstrate that EBDG significantly outperforms conventional multihop transmission schemes, direct transmission schemes, and cluster-head rotation schemes in terms of network lifetime.     

A two-hop clustered image transmission scheme for maximizing network lifetime in wireless multimedia sensor networks

In traditional wireless sensor networks, normal sensor nodes which measure scalar physical phenomena like temperature, pressure and humidity usually compress the data before sending them out to minimize the communication energy consumption. However, this strategy may not be suitable for image transmission in wireless multimedia sensor networks. In the traditional clustering structure, when the camera-equipped node or the cluster head compresses the images, an energy hole will appear. This is a key factor that affects the lifetime of the network. To avoid the energy hole problem, a two-hop clustered image transmission scheme is proposed in this paper. In the proposed scheme, many redirectors are used to compress and forward the images for the purpose of reducing energy consumption of the camera-equipped node and the cluster head. With adaptive adjustment of the transmission radius in the camera cluster and tasks allocation based on the residual energy of the normal sensor nodes by the camera-equipped node, the energy consumption of the nodes in the network is balanced. The experimental results show that the proposed scheme can prolong the network lifetime dramatically in the case of the sensor nodes deployed densely.     

Research of energy efficient clustering algorithm for multilayer wireless heterogeneous sensor networks prediction research

In designing wireless sensor networks of image transmitting, it is important to reduce energy dissipation and prolong network lifetime. This paper presents the research on existing clustering algorithm applied in heterogeneous sensor networks and then puts forward an energy-efficient prediction clustering algorithm, which is adaptive to sensor networks with energy and objects heterogeneous. This algorithm enables the nodes to select the cluster head according to factors such as energy and communication cost, thus the nodes with higher residual energy have higher probability to become a cluster head than those with lower residual energy, so that the network energy can be dissipated uniformly. In order to reduce energy consumption when broadcasting in clustering phase and prolong network lifetime, an energy consumption prediction model is established for regular data acquisition nodes. Simulation results and the application in image clustering show that compared with current clustering algorithms, this algorithm can achieve longer sensor network lifetime, higher energy efficiency, and superior network monitoring quality.     

层次型无线传感器网络节点布置方案的研究

对于大规模层次型的无线传感器网络,越靠近sink的节点,数据转发量越大,能量消耗速度越快,因此节点的密度分布状况对整个网络的生命期有着很大的影响。对层次型无线传感器网络的节点能耗分布状况和密度分布状况进行了分析,提出一种适合于大规模网络的节点布置方案。通过与均匀布置方案相比较,提出的方案能够使网络生命期得到很大的延长。     

基于感知数据概率模型的无线传感器网络采样和通信调度算法

在无线传感器网络中,如何动态地管理能量,最大限度地延长网络的生命周期是一个关键的问题。文中提出了一种基于感知数据概率模型的传感器网络的采样和通信动态调度算法,使传感器节点根据感知数据的概率模型来确定自己的采样和通信时机,最小化采样频率和通信量,减少传感器节点的能量消耗,延长传感器网络的生命期。该算法是一种分布式算法,适用于无线传感器网络。该算法采用了简单的概率模型,资源需求量小,适合于在目前普遍使用的资源受限的传感器节点上运行。模拟试验结果表明,这种方法与其他方法相比,具有很高的能量有效性。