Energy-aware routing for delay-sensitive underwater wireless sensor networks

The energy reduction is a challenging problem in the applications of underwater wireless sensor networks （UWSNs）. The embedded battery is difficult to be replaced and it has an upper bound on its lifetime. Multihop relay is a popular method to reduce energy consumption in data transmission. The energy minimum path from source to destination in the sensor networks can be obtained through the shortest path algorithm. However, because of the node mobility, the global path planning approach is not suitable for the routing in UWSNs. It calls for an energy-efficient routing protocol for the high dynamic UWSNs. In this paper, we propose the modified energy weight routing （MEWR） protocol to deal with the energy-efficient routing of delay- sensitive UWSNs. MEWR is a low flooding routing protocol. It can tolerate the node mobility in UWSNs and achieve a low end-to-end packet delay. MEWR can provide lower energy consumption than the existing low delay routing protocols through the dynamic sending power adjustment. The simulation results demonstrate the effectiveness of MEWR.     

基于链接预测的水下WSN消息转发算法

随着移动自组织网络的发展以及为了更加便捷地监测和探索水下环境,水下无线传感器网络开始出现并逐渐受到研究人员的重视.水下无线传感器网络可广泛应用于海洋环境监测、资源开采、水下生物研究、海难搜救等诸多水下场景.与传统的无线传感器网络不同,通常,水下无线传感器网络中存在锚定节点和移动节点两种类型的节点,并且由于水声通信的不规...     

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。     

基于洋流模型的水下传感器网络实时定位算法

针对近海监控领域内水下传感器网络的节点随着海洋运动具有流动性的问题,提出了基于洋流模型的水下传感器网络实时定位算法(RTLC).利用洋流模型表示节点的运动模型消除流动性对定位造成的影响,成功模拟了节点在水中的移动速度.通过卡尔曼预测方法结合观测值与估计值优化运动模型,使其更贴近节点运动规律.采用信息记录机制及列表更新机制保证信息的时效性从而提高了定位准确度.通过仿真分析,RTLC算法性能优于基于移动预测的大规模水下传感器网络可扩展定位算法(SLMP),具有较高的定位覆盖度,较低的平均定位误差及平均通信能耗.     

Ergodic secrecy rate of two-user MISO interference channels with statistical CSI

This paper considers a two-user multiple-input single-output （MISO） interference channel with confidential messages （IFC-CM）, where the beamforming vectors at the two transmitters are jointly optimized using the closed-form Pareto-optimal parameterization. We prove that artificial noise cannot improve the secrecy rate performance, and coordinated beamforming is secrecy-rate optimal which is achieved by agreeing on the parameters between the two transmitters. We analyze the feasible set of the beamforming parameters that guarantees positiveness of the secrecy rates when the transmitters know only statistical CSI, and then analysis in the ergodic secrecy rate region is discussed. More importantly, we derive the closed form of the ergodic secrecy rates and illustrate the Pareto-optimal structure of the beamforming vectors.     

三维水下监视传感器网络的拓扑生成算法

当前大多数传感器网络研究假设传感器节点在二维平面部署,然而许多水下传感器网络应用要求节点在三维空间分布。针对三维水下监视应用,提出一种新颖的分布式传感器网络拓扑生成算法（ETG）。基于格理论,ETG算法将节点的移动控制与活动设备的调度相结合。初始时刻监视设备密集部署在二维海平面上,ETG算法根据局部信息选择活动设备,并通过控制其传感器节点在垂直方向的移动,形成一个三维水下网络。仿真实验表明,ETG算法能够以较小的平均节点移动距离覆盖较大的空间,从而有效减少网络建立阶段的能量开销。     

水下传感器网络中的多路径路由技术研究

水下声信道是一种复杂信道,由于各方面因素影响,在数据传输过程中,水下传感器网络数据链路层会有可能产生随机中断.研究了一种虚拟汇聚节点的多路径水下传感器网络路由技术,在随机布设的传感器节点中选取了缓存节点,并创建了局部的汇聚节点,通过多路径的路由技术,有效减少了网络吞吐率受链路中断的影响,并且避免了汇聚节点处的数据冲突.通过网络的冗余性,增强了网络稳定性、鲁棒性.     

Mutual-information based weighted fusion for target tracking in underwater wireless sensor networks

Underwater wireless sensor networks (UWSNs) can provide a promising solution to underwater target tracking. Due to limited energy and bandwidth resources, only a small number of nodes are selected to track a target at each interval. Because all measurements are fused together to provide information in a fusion center, fusion weights of all selected nodes may affect the performance of target tracking. As far as we know, almost all existing tracking schemes neglect this problem. We study a weighted fusion scheme for target tracking in UWSNs. First, because the mutual information (MI) between a node’s measurement and the target state can quantify target information provided by the node, it is calculated to determine proper fusion weights. Second, we design a novel multi-sensor weighted particle filter (MSWPF) using fusion weights determined by MI. Third, we present a local node selection scheme based on posterior Cramer-Rao lower bound (PCRLB) to improve tracking efficiency. Finally, simulation results are presented to verify the performance improvement of our scheme with proper fusion weights.     

Interacting multiple model filter-based distributed target tracking algorithm in underwater wireless sensor networks

This paper deals with the problem of accurately tracking a single target, which has various trajectories, moving through the environment of underwater wireless sensor networks (UWSNs). This paper addresses the issues of estimating the states of the target, improving energy efficiency by using a distributed architecture. Each underwater wireless sensor node composing the UWSNs is battery-powered, so the energy conservation problem is a critical issue. This paper provides algorithms increasing the energy efficiency of each sensor node by using the proposed Wake-Up/Sleep (WUS) scheme. An interacting multiple model (IMM) filter is applied to the proposed distributed architecture in order to cope with a target maneuver. Simulation results illustrate the performance of the proposed tracking filter according to the various target maneuver patterns.     

自适应异构传感网节能优化拓扑控制研究

针对传统的节能优化算法没有充分考虑节点间的通信距离和节点失效后重新分簇等问题,为了延长网络的生存期,提出一种自适应优化异构无线传感器网络拓扑结构控制算法.提出的算法首先基于传输数据跳数和相邻传感器之间通信距离,依据相似三角形几何原理,结合具体应用场景对传感器节点的分簇、成簇等操作进行自适应优化控制.仿真实验表明:改进的...     

水下移动无线传感器网络研究综述

水下移动传感器网络是水下机器人与水下传感器网络的结合,解决了传统水下监控网络存在的无法自动实现节点投放与回收,容易存在监测盲区以及不能动态组网等问题,按照自下而上的体系结构,对水下移动传感器网络的研究内容及发展方向进行了归纳阐述,包括水下节点设计、节点互联和动态组网,即点、线、面的层次结构;着重分析了节点移动特性对水下传感器网络的影响及相应的解决方法.虽然水下移动传感器网络的研究面临很多挑战,但它必将具有广阔的应用前景.     

A smart node architecture for adding mobility to wireless sensor networks

Adding a few mobile nodes into the conventional wireless sensor networks can greatly improve the sensing and control capabilities of the networks and can help researchers solve many challenges such as network deployment and repair. This paper presents an enhanced node architecture for adding controlled mobility to wireless sensor networks. The structural model, the power model and the networking model of the proposed mobile node have been built respectively for better node control. And it provides a novel robotic platform for experimental research in hybrid sensor networks or other distributed measurement and control systems. A testbed has finally been created for validating the basic functions of the proposed mobile sensor node. The results of a coverage experiment show that the mobile node can provide additional support for network coverage and can ensure that the sensor network will work properly in undesirable environments.     

Key distribution scheme for peer-to-peer communication in mobile underwater wireless sensor networks

Wireless Sensor Networks (WSN) consist of small battery-limited devices called sensor nodes. The communication between sensor nodes is a type of peer-to-peer communication, since each node has the same capability and role. One of the recent application areas of these nodes is underwater sensing. Communication in Underwater Wireless Sensor Networks (UWSN) is challenging since radio frequencies cannot be used. Instead acoustic waves, which cause extra challenges, are used in UWSN. Since UWSNs are deployed in hostile environment, nodes can be captured by an adversary. In order to secure UWSNs, key distribution problem must be addressed. Moreover, UWSNs are inherently mobile since the nodes may be drifted in the sea. In this paper, we propose a key distribution model which is applied for two group mobility models, namely nomadic mobility model and meandering mobility model. In both schemes hierarchical structure is used and communication is handled via well-known Blom’s key distribution scheme. Our simulation results show that mobility causes some temporary decreases in the connectivity, but our schemes help to heal the connectivity performance in time. Moreover, our schemes show good resiliency performance such that capture of some nodes by an adversary only causes very small amount of links between uncaptured nodes to be compromised.     

基于新量子遗传算法的无线传感器网络感知节点的分布优化

无线传感器网络中,感知节点的合理分布对于提高网络的感知能力和收集信息能力都具有重要作用。对于随机分布方式产生的感知网络,可以利用节点的移动性对特定感知节点的位置进行调整从而改善网络整体的感知覆盖范围。为此,针对无线传感器网络感知节点的分布优化问题进行了研究,给出了无线传感器网络覆盖控制模型,并提出了一种基于新量子遗传算法的分布优化机制。仿真结果表明新量子遗传算法在优化性能上优于传统遗传算法,能够有效提高网络整体的感知能力。     

无线传感器网络连通性研究

为优化无线传感器网络的配置参数,减少网络拓扑结构变化次数,需对其组网算法和连通性问题进行研究。从概率论角度出发研究了网络参数之间的关系,在分析了节点连通度概率分布模型后,推导出了节点通信半径、节点个数、监测区域、连通度之间的关系,并在此基础上给出了一种连通性好且节能的无线传感器网络组网算法。通过仿真实验对算法进行验证,实验结果表明使用该方法组建的无线传感器网络连通性好,有很好的应用前景。     

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.     

一种无线传感器网络能耗均衡的自适应拓扑博弈算法

针对无线传感器网络节点能量有限与能耗不均衡导致网络生命周期提前结束的问题,运用势博弈理论将节点的平均寿命、节点最短寿命、网络的连通性以及覆盖性应用到效益函数的设计中,建立一种基于序数势博弈的能耗均衡的拓扑控制模型,以证明博弈模型是序数势博弈.基于该势博弈模型,提出一种能耗均衡的自适应拓扑博弈算法.该算法根据节点平均寿命调整自身的功率,帮助最短寿命节点降低功率,延长整个网络的生存时间.仿真实验及对比分析表明,所提出的算法相比于其他基于博弈论的拓扑控制算法,能够改善网络能量的均衡性,提高网络能量效率,保证网络拓扑的健壮性,增强网络拓扑的自适应性.     

Adaptive clustering in wireless sensor networks by mining sensor energy data

Clustering has been well received as one of the effective solutions to enhance energy efficiency and scalability of large-scale wireless sensor networks. The goal of clustering is to identify a subset of nodes in a wireless sensor network, then all the other nodes communicate with the network sink via these selected nodes. However, many current clustering algorithms are tightly coupled with exact sensor locations derived through either triangulation methods or extra hardware such as GPS equipment. However, in practice, it is very difficult to know sensor location coordinates accurately due to various factors such as random deployment and low-power, low-cost sensing devices. Therefore, how to develop an adaptive clustering algorithm without relying on exact sensor location information is a very important yet challenging problem. In this paper, we try to address this problem by proposing a new adaptive clustering algorithm for energy efficiency of wireless sensor networks. Compared with other work having been done in this area, our proposed adaptive clustering algorithm is original because of its capability to infer the location information by mining wireless sensor energy data. Furthermore, based on the inferred location information and the remaining (residual) energy level of each node, the proposed clustering algorithm will dynamically change cluster heads for energy efficacy. Simulation results show that the proposed adaptive clustering algorithm is efficient and effective for energy saving in wireless sensor networks.     

三维网络拓扑结构的水声传感器网络MAC协议

水声传感器网络Underwater Acoustic Sensor Network(UWASN)由于其广阔的应用前景,近年来逐渐被人们关注。然而由于水下环境的限制性,水声传感器网络具有其一些独特性。例如,与二维的陆地传感器网络不同,水声传感器网络是三维的。如今,现有的介质访问控制Medium Access Control(MAC)协议大多是针对二维无线传感网络,很少有基于三维水声传感器网络的 MAC 协议。针对水下三维网络,提出了基于三维网络拓扑结构的水声传感器网络 MAC 协议。该协议将网络中的节点生成树结构,并利用子节点与父节点之间的关系,通过动态节点算法实现三维动态的水声传感器网络。此外,详细分析了节点间的碰撞并有效解决各种碰撞,从而大大提高了信道利用率。通过仿真软件对比不同协议在同一网络拓扑中的实验结果,证实文中协议能够有效节约大量能源。     

基于距离的分布式无线传感器网络定位算法*

针对水下无线传感器节点的定位问题进行研究,提出了一种可实现网络规模升级的分布式无信标节点的自定位算法。该定位算法无须额外的硬件支持,仅采用节点间的距离信息建立相对坐标系,确定各节点的相对位置。详细介绍了该算法的实现过程,通过仿真讨论了求精过程、通信半径等对定位误差的影响,并验证了该算法的合理性。为目标跟踪、地理路由、网络管理等系统功能提供了有力的技术支持。