采用转发优先级的水下传感网络的机会路由

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水下无线传感器网络

水下无线传感器网络摘要：水下无线传感器网络是一种包括声、磁场、静电场等的物理网络，它在海洋数据采集、污染预测、远洋开采、海洋监测等方面取得了广泛的应用，将在未来的海军作战中发挥重要的优势。

描述了水下无线传感器网络的研究现状，给出了几种典型的水下无线传感器网络的体系结构，并针对水下应用的特点，分析了水下无线传感器网络设计中面临的节点定位、传感器网络能量、目标定位等诸多难题，最后根据应用需求提出了水下无线传感器网络研究的重点。

关键词：水下无线传感器网络；能量；定位1．引言水下无线传感器网络是使用飞行器、潜艇或水面舰将大量的(数量从几百到几千个)廉价微型传感器节点随机布放到感兴趣水域，节点通过水声无线通信方式形成的一个多跳的自组织的网络系统，协作地感知、采集和处理网络覆盖区域中感知对象的信息，并发送给接收者。

近年来，水下无线传感器网络技术在国内外受到普遍关注，正在被广泛用于海洋数据采集，污染预测，远洋开采，海难避免，海洋监测等。

水下无线传感器网络具有传统传感器技术无法比拟的优点[1]：传感器网络是由密集型、成本低、随机分布的节点组成的，自组织性和容错能力使其不会因为某些节点在恶意攻击中的损坏而导致整个系统的崩溃；分布节点的多角度和多方位的信息融合可以提高数据收集效率并获得更准确的信息；传感网络使用与目标近距离的传感器节点，从而提高了接收信号的信噪比，因此能提高系统的检测性能；节点中多种传感器的混合应用使搜集到的信息更加全面地反映目标的特征，有利于提高系统定位跟踪的性能；传感器网络扩展了系统的空间和时间的覆盖能力；借助于个别具有移动能力的节点对网络的拓扑结构的调整能力可以有效地消除探测区域内的阴影和盲点。

因此，传感器网络能够应用于恶劣的战场环境。

在军事领域，通过多传感器系统的密切协调，形成空-舰-陆基传感器构成的多传感器互补监视网络，对目标进行捕获、跟踪和识别。

水下无线传感器网络由于其应用环境的特殊性，要考虑海水盐度、压力、洋流运动、海洋生物、声波衰减等对传感器网络的影响，使水下无线传感器网络的设计比陆地无线传感器网络更难，对硬件的要求更高。

水下无线传感网络（WSN）国内外研究进展综述

⽔下⽆线传感⽹络（WSN）国内外研究进展综述⽔下⽆线传感⽹络（WSN）国内外研究进展综述⼀.研究背景与意义21 世纪是⼈类开始全⾯研究海洋特性并认识、开发、保护海洋的新世纪。

海洋经济占各国经济的⽐重越来越⾼。

⽔下⽆线传感器⽹络已经成为各国重点研究的⽅向。

⽔下⽆线传感器⽹络已经⼴泛的应⽤在灾难预警、污染物监控、⽔⽂数据的监测和采集、海洋资源勘探、辅助导航和海洋军事等众多领域。

⽆线传感器⽹络集成了传感器、微机电系统和⽹络三⼤技术，是⼀种全新的信息获取和处理技术。

⼆.⽆线传感⽹络的简介（1）⽆线传感器⽹络构成⽆线传感器⽹络(Wireless Sensor Network，简称WSN)被认为是21世纪最重要的技术之⼀，它将会对⼈类未来的⽣活⽅式产⽣巨⼤影响。

⿇省理⼯学院的《技术评论》杂志(Technology Review)评出了对⼈类未来⽣活产⽣深远影响的⼗⼤新兴技术，⽆线传感器⽹络位于这⼗种新技术之⾸。

⽆线传感器⽹络是由随机分布的集成有传感器、数据处理单元和通信模块的微⼩节点通过⾃组织的⽅式构成，借助于节点中内置的各种传感器测量所在周边环境中的热、红外、声纳、雷达和地震波信号，从⽽探测包括温度、湿度、噪声、光强度、压⼒、⼟壤成分、移动物的⼤⼩、速度和⽅向等众多我们感兴趣的信息。

（2）⽆线传感器⽹络的节点⽆线传感器⽹络典型的体系结构下图所⽰。

节点具有传感、信号处理和⽆线通信功能，它们既是信息包的发起者，也是信息包的转发者。

通过⽹络⾃组织和多跳路由，将数据向⽹关发送。

⽹关可以使⽤多种⽅式与外部⽹络通信，如Internet、卫星或移动通信⽹络等，⼤规模的应⽤可能使⽤多个⽹关。

节点由于受到体积、价格和电源供给等因素的限制，通信距离较短，只能与⾃⾝通信范围内的邻居交换数据。

要访问通信范围以外的节点，必须使⽤多跳路由。

为了保证⽹络内⼤多数节点都可以与⽹关建⽴⽆线链路，节点的分布要相当的密集。

传感器⽹络节点具有以下⼏个典型组件：⽆线电收发装置（带有内部天线或外部天线连接装置）、微型控制器、传感器、数据采集接⼝、存储器、⽔声通信器，以及电源（通常为电池或嵌⼊式能量收集装置）等。

机会路由综述2014.6

机会路由综述机会路由是针对无线多跳网络信道广播特性、有损特性提出的一种MAC层路由协议，机会路由的各转发节点由多个候选节点的竞争选择产生，由此带来了比传统固定路径无线路由更高的传输可靠性以及端到端的吞吐量[1][2]。

2005年，MIT计算机科学与人工智能实验室的Sanjit Biswas和Robert Morris在SIGCOMM会议发表的论文首次提出了一种机会路由——ExOR[1](Extremely Opportunistic Routing)。

ExOR协议运行过程为：已知源节点准备将一信息包传输到多跳外的目的节点。

源节点广播信息包，协议选择一节点子集接收信息包，节点子集中离目的节点最近的节点再次广播信息包，协议选择下一节点子集，其中接收到该信息包的离目的节点最近的节点接收信息包并转发，循环运行该过程直到目的节点接收到信息包。

ExOR使用改进的ETX（expected transmission count）作为链路质量的衡量指标，经典的ETX指标：其中d f为前向链路投递率，代表信息包被成功接收的概率； d r为反向链路投递率，代表接收节点回复ACK被成功接收的概率。

ExOR中改进的ETX假设反向链路投递率100%，简化了衡量指标的计算，但也产生了忽略反向链路的缺点。

ExOR中令每个节点的ETX值为该点到目的节点路径上所有链路ETX之和的最小值，而我认为用链路ETX之和的最小值表示一节点的ETX值并不合理，因为该值并不能代表该节点到目的节点的路径质量，路径质量应与路径上所有链路的投递率的乘积相关。

因而，对ETX指标进行修正可能会带来更好的路由协议性能。

ExOR协议在MIT搭建的满足802.11b协议的室外无线网络Roofnet中进行了评估验证，证明了在相同的网络容量下，ExOR相比传统路由带来了更高的吞吐量。

Roofnet结构为：整个区域紧密分布着3到4座老房子，网络中大部分节点的天线比房子烟囱高23英尺，整个区域中还有几座高楼，有5个Roofnet节点分布在网络边界的高楼上，少数节点天线安装在窗口。

水下传感器网络路由协议的研究

AbstractUnderwater sensor networks are a kind of special sensor networks. It consists of a variable number of sensors and vehicles that are deployed to perform collaborative monitoring tasks over a given area. Underwater sensor networks are envisioned to enable applications for oceanographic data collection, pollution monitoring, offshore exploration, disaster prevention, assisted navigation and tactical surveillance applications.Complexity of underwater acoustic channel such as high delay, delay variance, multi-path propagation and Doppler spread , makes it impossible to apply direct protocols for terrestrial wireless communication networks to underwater. How to integrate a simple and efficient underwater sensor networks is still a new studying field on the base of the underwater acoustic communication.In the thesis, routing protocols in network layer are studied. The principle of many current existing routing protocols are introduced. In accordance with the feature of underwater acoustic channel and the architecture of underwater sensor networks，the routing protocols based on location-preset information is more fit for underwater sensor networks. Then GPSR protocol is studied.In underwater sensor networks, not only the energy expenditure of the sole node but also the whole networks’energy bal ance is cared for in the routing protocols to extend the network’s lifetime. A new routing approach is proposed to get the optimal path thinking over the geographical energy aware and loading equilibrium in this thesis. In the end this thesis presents the comparison between this algorithm and the common GPSR through OPNET.According to our simulations, we find that the new algorithm can not only maintain former performance but also prolong the survival time of the network.Key words: underwater sensor networks topology routing protocolforwarding algorithm GPSR energy aware and loading equilibriumOPNET目录摘要 (I)Abstract ........................................................................................................... I I 1 绪论1.1 课题研究的背景 (1)1.2 水下传感器网络 (2)1.3 课题研究的意义 (5)1.4 课题的国内外研究现状 (6)1.5 论文的主要研究内容 (8)2 水下传感器网络体系结构2.1 水下传感器网络拓扑结构 (10)2.2 水下传感器节点结构 (14)2.3 水下传感器网络网络协议栈 (15)2.4 本章小结 (15)3 水下传感器网络路由协议的研究3.1 先应式路由协议 (16)3.2 按需路由协议 (19)3.3 利用地理位置信息的路由协议 (25)3.4 水下传感器网络基于位置信息路由协议的设计 (30)3.5 本章小结 (32)4 贪婪路由协议研究4.1 贪婪转发策略的研究 (33)4.2 GPSR路由协议 (38)4.3 本章小结 (45)5 基于位置路由协议的改进5.1 问题的提出 (46)5.2 Ad hoc网络的生存时间 (47)5.3 基于位置的能量感知及负载均衡路由算法 (47)5.4 仿真实验及结果分析 (52)5.5 本章小结 (60)6 结论6.1 全文总结 (61)6.2 进一步研究方向 (62)致谢 (63)参考文献 (64)附录1 攻读学位期间发表的论文目录 (67)1 绪论1.1 课题研究的背景近年来，随着世界各国海洋开发步伐的加快，对水下传感器网络、水下监视系统、水声预警网络的需求愈来愈迫切，水下通信网络技术成为了世界范围内的研究热点[1][2]。

基于粒子群算法的水下无线传感器网络路由策略研究

第12期2019年4月No.12April ，2019刘守齐，张潮，冯锋（宁夏大学信息工程学院，宁夏银川750021）0引言随着海洋经济的发展以及世界各国对海洋权益的日益重视，水下无线传感器网络（Underwater Wire⁃less Sensor Network ，UWSN ）作为一种新型无线传感器网络技术正在受到人们的普遍关注，并用在环境监测、海洋数据采集、海难预防等方面具有广泛的应用前景。

水下无线传感器网络是通过潜艇或水面舰艇将大量的传感器节点布置到目的水域，形成的一个无线自组织网络［1］。

由于水下传感器网络部署环境的特殊性、水声通信方式的高时延性和易受干扰以及人工作业等因素，使得水下无线传感器网络的能耗性和网络生存时间方面存在着极大的挑战［2］。

因此，低功耗的路由优化策略是水下无线传感器网络的重要研究方向。

目前，有很多国内外学者做过类似的研究。

例如，Yan 等［3］提出了基于深度信息的网络路由策略，该算法设定只有当节点深度小于给定的深度值时才可以进行转发，但能耗方面依旧未得到很好的改善。

李成法等［4］提出了基于EEUC 算法的非均匀分簇网络路由协议，但该算法在簇首竞争方面未加入剩余能量这一条件，因此并不能很好解决路由高能耗的缺点。

LEE 等［5］提出了基于压强信息的路由策略，该算法在所有的周围节点中，选择压强最低的节点作为转发节点，没有考虑节点的全局位置信息和水流环境的影响，也没有很好解决能耗问题。

Huang 等［6］提出了一种基于转发节点选择器和转发树裁剪机制来解决能耗问题的算法，该算法在一定程度上解决了高能耗问题，但效率不高。

本文针对水下无线传感器网络的高能耗问题，并基于原来的无线传感器网络非均匀分簇路由算法，结合粒子群算法（Particle Swarm Optimization ，PSO ）的特点，提出一种新的基于粒子群算法的水下无线传感器网络路由策略。

1网络与能耗模型1.1网络模型本文主要考虑静态二维水下无线传感器网络，并对网络模型做出如下设定。

水下无线传感器网络路由算法概述

25Internet Technology互联网+技术引言：近些年，发现更多的水下资源以代替逐渐减少的有限的陆地资源，成为了众多学者的研究目标。

水下无线传感器网络在地震、海啸预警、生态系统监测、石油钻探和军事监视方面的应用也同样被关注。

水下传感器网络由于其特殊的运行环境，成为了探索水下资源最有效的方法，从而引起了学者们的极大兴趣。

而传感器技术的发展为水下无线传感器网络的发展奠定了技术基础，随着国家对海洋资源的重视程度加强，在政策层面，水下传感器网络的发展具有着前所未有的机遇。

然而，由于水下无线传感器网络工作环境的特殊，光的散射、折射及多普勒效应，导致光信号在水下衰减很快；而电磁波的快速衰减也不适合在水下进行通信；从而在水下传感器网络中使用声音信号进行通信。

由于水下无线传感器网络使用声音信号进行通信，且通信环境较为复杂，使其具有如下一些不同于陆地网络的特点[2]：1.有限的能量。

由于水下传感器网络工作在水下，节点配置的电池很难更换，且电池无法使用太阳能充电。

因此，一旦电池能量耗尽，节点死亡。

2.定位困难。

水下传感器网络精确定位困难主要有两方面原因：1) 在陆地网络中，用的最多的定位技术为GPS 定位，但由于在水下GPS 信号衰减太大，无法使用在水下；2）水下传感器网络中，节点随着水流的移动而移动，而非固定的位置，因此在动态的拓扑结构中，无法根据最初的位置确定变动后的拓扑结构。

3.信号传播延时大。

陆地网络中，信号的传播速度为 3×108米/秒，水下无线传感器网络中，信号传播速度为1500米/秒。

因此，水下无线传感器网络中信号的传播速度比陆地无线传感器网络信号传播速度慢五个数量级。

4.布置稀疏。

由于水下无线传感器网络节点昂贵，因此很少布置备用节点，一旦某个节点死亡，没有其他节点可以备用。

5.误码率高。

水下无线传感器网络通信环境复杂、拓扑中出现空洞、数据在传输过程易碰撞等原因，导致其丢包率较高，从而误码率增大。

水下无线传感网讲解

近年来，水下无线传感器网络技术在国内外受到普遍关注，正在被广泛用于海洋数据采集，污染预测，远洋开采，海难避免，海洋监测等。

因此，传感器网络能够应用于恶劣的战场环境。

在军事领域，通过多传感器系统的密切协调，形成空-舰-陆基传感器构成的多传感器互补监视网络，对目标进行捕获、跟踪和识别。

基于水下传感器网络特设路由的优先级度量研究(IJCNIS-V5-N12-1)

I. J. Computer Network and Information Security, 2013, 12, 1-11Published Online October 2013 in MECS (/)DOI: 10.5815/ijcnis.2013.12.01Priority Metric based Ad Hoc Routing for Underwater Sensor Network1Md. Ashraf Uddin, 2Md. Mamun-or-Rashid, 3Md. MustafizurRahman1Mawlana Bhashani Science and Technology University,2,3University of Dhaka 1ashrafuddin.mbstu@,2mamun@, 3mustafiz1952@.Abstract— Underwater sensor network has been burgeoned as an interesting research area which has to face a couple of challenges to provide scalable and efficient routing services because of its unique characteristics. In many aspects, it differs from the ground based terrestrial sensor network, Firstly, In UWSNs, acoustic signal is used instead of radio-frequency that attenuates much in underwater environment in comparison with radio-frequency channels. Acoustic channels attribute much lower bandwidth and the propagation speed of acoustic signals in water is several of magnitudes longer. Secondly, nodes of underwater sensor networks move with water current which results dynamic topology. Thirdly, underwater sensor networks consume more power than terrestrial networks due to the underwater channel characteristics and it has high error probability because of acoustic underwater channels' sensibility in noise, multi-path and Doppler spread. Some routing protocols have been proposed to deal with these challenges. But most of these protocols espouse the greedy technique to forward packets to the neighboring node which consumes a lot of energy when network is dense. In this thesis, we propose a Priority Metric Based Ad hoc Routing Protocol for UWSNs. The leading advantages of the protocol are that it consumes less energy in dense network as only one neighboring node needs to capture the packet and process it and it guarantees less number of packet loss in high mobile node environment. Extensive simulation is executed to attest the competence of the proposed routing protocol. The result and analysis bear the indication of the proposed routing protocol's surpassing the existing routing protocol in terms of total energy consumption and average end to end delay.Index Terms— UWSNs, Link Stability, Priority Metric, random node mobility, horizontal node mobility, updating timeI.I NTRODUCTIONWireless sensor networks have been a promising network technique that has been incorporated comprehensively in a lot of land-based applications. The earth is called a planet of water and about two-third of its surface is covered by oceans where a huge amount of resources and information lies and need to discover these hidden resources and provides important information such as Tsunami and earthquake information from the bottom of oceans to the surface. Data mining in oceans can also be carried out through UWSNs. Accordingly, a quickly increasing development towards the application of sensor networks such as ocean sampling networks, environmental monitoring, undersea explorations, disaster prevention and mine reconnaissance[1][2][3]in underwater environments that is forming underwater sensor networks (UWSNs) have been observed in current several years. In underwater sensor network, many research issues have been continued to study for constructing the UWSNs protocol stack. Routing, sending packet from a source node to a destination is one of the innovative and potential issues of UWSNs to be revised. A.Unique Characteristics of UWSNsAn UWSNs can be differentiated from any ground-based sensor network in the perspective of cost, deployment, power and memory of each node. In fact, it is very difficult to provide scalable and efficient routing services due to the unique characteristics of underwater sensor networks. Routing protocols need to meet the challenges of limited bandwidth, high bit error rates and temporary losses of connectivity (shadow zones). Underwater sensor nodes are prone to failures because of fouling and corrosion, limited battery power, high propagation delay, mobility of nodes.In details, firstly, radio frequency cannot be used as transmission media to guide a packet under water due to its fast attenuation. Acoustic communications are preferred in underwater environment but acoustics channels often suffer from low bandwidths and long propagation delays. For this reason the routing protocols that feature long end-to-end delays or high bandwidth requirement are not suitable in acoustic UWSNs. The available bandwidth is limited due to attenuation and high absorption factor of acoustic signals. The link quality is severely affected by the multi path fading and refractive properties of sound channels. Therefore, the bit error rates are typically very high. Secondly, UWSNs is a highly dynamic network topology because of most nodes' moving with water current (except that some gateway nodes are fixed at the water surface or anchored at the bottom). With a view to handling dynamic networks, using existing routing protocol for land based (static) sensor networks requires to update routing information frequently, which produces significant communication overhead. Thirdly, it is even2Priority Metric based Ad Hoc Routing for Underwater Sensor Networkharder to recharge or replace the batteries used by the sensor nodes of UWSNs like land-based sensor nodes in hash underwater environments. Thus, another essential apprehension for UWSNs is energy. UWSNs are usually deployed in a 3-dimensional space. This is different from the 2-dimensional deployment of most land-based sensor networks. UWSNs are very differentfrom ground-based existing networks due to the intrinsic properties of the underwater environments.B.Routing Challenges of UWSNsTo save energy is considered the key apprehension in UWSNsas like in terrestrial sensor networks. At the same time, UWSNsrouting should be able to handle node mobility. This requirementmakes most existing energy-efficient routing protocolsunsuitable for UWSNs [4]. Many routing protocols are proposedfor terrestrial sensor networks such as Directed Diffusion[5], and TTDD (Two-Tier Data Dissemination)[6].These protocols are designed for stationary network. Queryflooding is usually employed by these protocols to discoverdata delivery paths. In UWSNs, however, most sensor nodes are mobile, and the ”network topology” changes very rapidly even with small displacements. The frequent maintenanceand recovery of forwarding paths is very expensive in highdynamic networks, and even more expensive in dense 3-dimensional UWSNs. The multi-hop routing protocols interrestrial mobile ad hoc networks fall into two categories:proactive routing and reactive routing (aka. on-demand routing).In proactive ad hoc routing protocols like OLSR[7],TBRPF [8] and DSDV [9], the cost of proactive neighbordetection could be very expensive because of the largescale of UWSNs. On the other hand, in on-demand routing(with AODV [10] and DSR [11] as common examples),routing operation is triggered by the communication demandat sources. In the phase of route discovery, the source seeksto establish a route towards the destination by flooding aroute request message, which would be very costly in largescale UWSNs.It is clear that the routing protocol designed for terrestrialsensor networks is not suitable for UWSNs. In the recentyears, a major number of UWSNs routing protocol suchVBF [4], DBR[12], HH-VBF [13], FBR [14], DUCS[15],UWD[16] and MPT[17] has been developed. UWSNs routingprotocol can be divided into two categories: localizationbased routing protocol and localization free routing protocol.All of these routing protocols have tried to address the UWSNs challenges but have not been able to meet all therequirements to be an efficient and scalable UWSNs routing protocol. No direct method has been followed by theseprotocols to handle node mobility. Most of these apply thegreedy method to forward packet which results a huge amountof energy consumption. To design a UWSNs routing protocolthat provides scalability, robustness and efficiency at thesame time is also a big challenge. Existing UWSNs routingprotocols are suited for specific environment. To developa UWSNs routing protocol which presents the same performancefor dense network and sparse network is anotherrouting challenge. In this paper, we target a mobile UWSNs(where most sensors are not fixed, and they can float withwater current). This type of UWSNs is very useful in manyapplications, such as estuary dynamic monitoring and submarine detection[18], [19].C.ContributionOur key concern is to erect a routing protocol for UWSNs so that we can send data packet from source to destination efficiently meeting the challenges of UWSNs. With a view to saving energy, we have introduced unicast data packet forwarding technique. To handle node mobility, we calculate link stability and to maximize the update period, we present two methods for measuring the nodes’ survivability within a predefined region by considering both random node mobility and horizontal node mobility. Finally, we presume a priority metric based on depth, residual energy and link stability.The rest of this paper is organized as follows. We describe related works in Section 2. Our proposed PriorityMetric based Ad hoc Routing Protocol for UWSNs ispresented in Section 3 and the simulation results are presentedin Section 4. Finally, we conclude the paper in Section5 along with future research direction.II.R ELATED WORKSOne of the primary topics for any network is routing and routing protocols are regard as indictment of determining and preserving the routes. Most of the research works pertaining to underwater sensor networks have been on the issues related to physical layer. On the other hand, routing techniques are comparatively new arena of network layer of UWSNs. Thus providing an efficient routing algorithm becomes a significant mission. Although underwater acoustic has been continued to study for decades, underwater networking and routing protocols are still at the infant stage of research.Link Expiration Time Aware Routing Protocol for UWSNs(LETA)[20] is divided into three phases named selection of compatible forwarding node phase, routing table formation phase by sending node and target node selection phase by the sending node to send data packet. Each of the parts is discussed in this section. Selection of Compatible Forwarding Node phase: In this phase, most of the procedures are performed by the forwarding node. The sending node broadcast a hello message named RREQ to discover its one hop compatible forwarding node. Upon receiving the RREQ message of the sending node, the forwarding node estimates the probability of packet forwarding and packet discarding based on the depth difference of the forwarding node and sending node, residual energy and the distance from forwarding node to sending node. If the probability of packet forwarding is greater than that of packet discarding, the forwarding node responds to the sending node through RREP message incorporated its probability in the reply message. Routing Table Formation phase: After receiving RREP message from one hop neighbor node, the sending node reckons the link expiration time with each compatible forwarding node. The sending node keeps the forwardingnode in its routing table according to the decreasing order of the forwarding nodes' probability that means the node with highest probability is at first position in the routing table and the next highest is at second position. Target Node selection phase: After completing the formation of routing table, the sending node pick up the forwarding node with highest probability and corresponding link expiration time of the forwarding time in order to handle node mobility. The link expiration time is compared with the time to reach the packet to the forwarding node and return acknowledgement to the sending node from the forwarding node. If the link expiration time of the forwarding exceed the packet's reaching time and acknowledgement's receiving time, then the forwarding node is chosen as target node and the packet is forwarded to the node. Otherwise, another node is chosen in the same way. If no node in the routing table is found as target node, then routing table is formed anew[20].In Energy Efficient Fitness based Routing for Underwater Sensor Network[21], it is assumed that the location of the sink node is known. First, the source node calculates the fitness ofits own and incorporates the fitness value and its positionin the data packet and broadcasts it. The one hop neighboringnodes which get the packet calculate their own fitnessthat actually define whether they forward the packet or simplydiscard. After receiving the packet, the forwarding nodecompares its fitness with the sending node’s fitness incorporatedin the packet. If the fitness of the forwarding node isgreater than that of the sending node, then it forwards thepacket otherwise it discards the packet. In this process, morenodes may take part in forwarding packet; In order to preventmore nodes to forward the same packet, the forwardingnodes wait for a time period which is assumed based on theresidual energy, depth, and distance from the sending nodeto the forwarding node. The holding time of the forwardingnodes vary from each other. The node which is the fittestwaits less time than that of other forwarding nodes. Consequently,other forwarding nodes overhear the same packetand avoid forwarding the packet[21].An Energy Efficient Localization-Free Routing (EEDBR). In[22], the authors proposed an energy efficient localization freerouting protocol (EEDBR) for the greedy pressure-basedrouting group ofUWASNs.The aim of this protocol is to balancethe energy of nodes and improve the network lifetime.In the architecture of EEDBR, multiple sinks are deployedon the water surface and equipped with radio and acousticmodems, while ordinary nodes are randomly scattered in thearea of interest. They can move freely through water flow,and they are equipped with acoustic modem. Unlike DBRthat is a receiver-based routing protocol, EEDBR is a senderbasedrouting protocol in which sender node selects a set ofnext hop nodes based on their depth and residual energy.EEDBR is composed of two phases: knowledge acquisitionand data forwarding. In the first one, each node broadcastsits own depth and residual energy as a Hello packet to itsneighboring nodes. Therefore, all nodes collect and savetheir neighboring nodes’ information. In the second phase,a subset of forwarder nodes is selected based on their depthinformation and residual energy. In other words, a group ofneighboring nodes with a depth smaller than that of sendernode that have suitable residual energy are selected as nexthop node candidates. The sender node embeds a list ofselected nodes ID in data packet and forwards it. The nodeson the list are sorted based on their residual energy, whichshows their priorities. In order to prevent redundant datapacket forwarding, each candidate node considers a holdingtime according to its residual energy and priority in which ashorter holding time is assigned to a node withmoreresidualenergy. In addition, the nodes with the same residual energy have different priority which results in different holding time for these nodes [23].Depth Based Routing Protocol DBR (Depth based routing)[12] is an underwater sensor network routing protocol which isbased on the depth information of each sensor. In this routingprotocol, No complete dimensional information of locationof the sensor nodes is required and it can managea dynamic network. In DBR[12], to deliver a packet, it determinesthe closer to the destination the smaller the depth ofthe forwarding nodes becomes and to receive a packet itcompares depth dp retrieval of the previous hop and it’s receivingnode’s depth for the qualified candidates to forwardthe packet. DBR has good energy efficiency but not so muchgood performance for the dense network where it has significantend to end delay and high total energy consumption.In this paper, we have proposed a novel UWSNs routingprotocol which takes into account of the water current and articulates the link stability between two sensor nodes. The proposed protocol takes advantages of multiple sink node and localization technique to predict the link stability.III. D ETAILS OF THE P ROPOSED P ROTOCOLIn this section, we present our priority metric based ad hoc routing protocol (PMA) in detail. Multiple-Sink underwater sensor network architecture has been applied in the proposed routing protocol. We have divided the protocol into two parts named route information accumulation phase and target sensor node selection phase. In route information accumulation phase, the sensor nodes broadcast a hello message named by RREQ to form routing table within their range. In target sensor node selection phase, the forwarding node selects the sensor node with the highest priority to forward the data packet.work ArchitectureIt is pointed out before; the multiple-sink underwater sensor network architecture [12] can be used by the proposed routing protocol, the Priority Metric based Ad hoc (PMA) routing protocol. Like DBR [12], it also takes advantages of the multiple-sink underwater sensor network architecture. An example of such networks is demonstrated in Fig 1.Figure 1: Multiple-Sink underwater sensor networkarchitecture[12]In this multiple-sink network, the water surface nodesthat are called sink nodes are equipped with the modemthat is capable of capturing both radio-frequency andacoustic signal. The nodes that send and receive onlyacoustic signal are deployed in the underwater environment. Underwater sensor nodes with acoustic modems are placed in the interested 3−D area and eachsuch node is assumed likely to be a data source.Underwater acoustic nodes can accumulate data and alsoassist to convey data to the sinks. When a sink node receives a packet from an underwater acoustic node, thesink node can converse with each other efficiently viaradio channels. The protocol attempts to send a packet toany sink nodes on the surface because if a surface nodereceives a packet it can send the packet other sinks or remote data centers quickly due to the speed of radio- frequency (with a propagation speed of 3 ×108m/s in air) which is five orders of magnitudes higher than sound propagation (at the speed of 1.5 ×103m/s in water)[4]. Here, the protocol does not pay attention to thecommunication between surface nodes. Instead it tries totransmit a packet to any surfacesinks and assumes that thepacket reaches to its destination. The protocol has beenbuilt by considering the fact that every node knows its depth which is the vertical distance from the node's position to the surface.B.Overview of Priority Metric based Routing Protocolfor Underwater Sensor NetworksOverall view of the proposed UWSNs routing protocolis described in two phases. Firstly, a brief discussion on routing table formation is given in route information accumulation phase and secondly, target sensor node selection phase has been described.Route Information Accumulation Phase:Route information accumulation phase includes the broadcasting control packet by the each sensor node to the one hop neighboring sensor nodes and receiving the depth and residual energy of the one hop neighboring sensor nodes by each other. In this phase the information required to form routing table is obtained by each sensor node. The phase works as the following way. In this phase each sensor node broadcasts control packet to its one hop neighboring sensor nodes and let them know its depth and residual energy. In this way, every sensor node within a fixed range knows each other depth and residual energy. After that, each sensor node forms their routing table of its qualified one hop neighboring sensor nodes. During the formation of routing table, each sensor node takes into account only its neighboring sensor nodes which depth are less than that of the forwarding sensor node. Secondly, the each sensor node discards those neighboring sensor nodes which residual energy is less than threshold energy. Thirdly, it filters the neighboring sensor nodes which link stability does not permit to be stayed connected with its neighboring sensor node during the estimated time period. As a result the size of the routing table becomes small and it lessens the burden of storing so much information for all one hop neighboring sensor nodes. In UWSNs, the topology of the network changes frequently because of water current that forces each sensor node broadcast control packet to find the most suitable neighboring node which packet can be transmitted. Moreover, in harsh environment the sensor nodes tend to be more mobile. Therefore, each time after passing an estimated time, each sensor node has to update the routing table by broadcasting control packet. Generally, control packet overhead occurs for this kind of approach, for the purpose of reducing control packet overhead, we have estimated the update time based on node mobility. Two approaches for presuming updating time is discussed in this paper by considering the random node mobility and the horizontal node mobility.Target Node Selection Phase: In this phase, each sensor node qualifies only one node to forward the packet based on not only depth and residual energy but also link stability of the node that means how much time the target node and the forwarding node remain connected within a fixed range. When a sensor node finds the depth and residual energy of its one hop neighboring nodes, it calculates the link stability of the neighboring sensor nodes for the estimated time t. In this protocol, in order to control congestion and reduce total energy consumption, only one sensor node is selected to forward the packet. Hence,the link stability of the node is necessary to ensure that the node remains within the range up to the whole time of receiving the whole data from the forwarding node. To calculate the Link stability, to know the locationinformation of each sensor node is required which can be achieved through localization technique. The process for selecting the most suitable target node is to estimate a priority metric based on depth, link stability and residual energy where link stability and residual energy must exceed the threshold link stability and threshold residual energy respectively. The priority metric is stored in descending order in the routing table. If any neighboring sensor node's residual energy or link stability is below minimum requirements then its priority metric is not calculated and the protocol avoid storing it in the routing table and the sensor node prevents itself from further broadcasting control packet. The candidate sensor node with the highest priority metric of the routing table is picked to forward the packet and the selected candidate sensor node is called target sensor node. In this protocol, mobility of node is handled with the help of linkstability. The protocol chooses it target forwarding sensornode by considering the depth that helps packet to reach sink by using minimum number of hop, residual energy that ensure that the node has enough energy to forward the packet and link stability that guarantees the durability of the connection between the forwarding sensor node and the target node.C.Reckoning Link StabilityTo identify the link stability of any two one hop neighboring nodes, Distance between these two nodes for the time t is calculated. Link stability of any two nodes means the duration of the connectivity of the two nodes within a fixed range R.When the distance between two nodes becomes larger than the transmission range R link stability L st between any two nodes overtime period t can be calculated [20]:LL ssss=DD RRD.Estimation of Updating TimeIn this section, we have estimated the update time of routing table for a sensor node. Our data forwarding technique is unicast so we can reduce the control packet overhead by increasing update time. This time is calculated based on the presumption that minimum required number of sensor nodes can be founded within range of the forwarding sensor node. We have calculated updating time in two ways, firstly we assume that the nodes randomly move and secondly the nodes move horizontally. Updating Time for Random Node Mobility: In Fig 2, we consider F as forwarding node. By broadcasting RREQ message, F can discover N1, N2 ,N3, N4, N5 and N6 candidate neighboring sensor nodes. These sensor nodes are called candidate because they accomplish the minimum constraint to be a candidate neighboring node.Figure 2:Updating time for random node mobilityNow we would like to estimate a time t that makes certain that most of these sensor (at least 80%) nodes will stay within the upper half region of the R range. Here, we have assumed that the nodes can move in randomdirection with V velocity. As a node can take random movement, we have considered a circle by taking the sensor node’s position as the center of that circle andradius is min (|Z i− Z f|, R − d i). Z i is the Z− axis value of the sensor node N i‘s position, and Z f is the Z−axis value of the forwarding sensor node. |Z i− Z f|is the distance of the parallel line drawn for the sensornode N i’s position to the plane AB and R − d i is the minimum distance from the nodes position to circumstance of the circle whose radius is range R. Now, for the worst case scenario of each sensor node, we can estimate the lasting time within fixed half region of the range R as follows:ss1=|ZZ1−ZZ ff|VVss3=|RR−dd3|VVTime(t1,t2,t3,t4,t5 and t6for node (N1,N2 ,N3,N4,N5,and N6) indicates the sustainability with in the half region of the range of the forwarding node. We are interested to prefer a time t among (t1,t2,t3,t4,t5 and t6)so that at least 80% of the candidate nodes (N1,N2 ,N3,N4,N5,and N6)remain within the region during this period(t). If we choose the smallest time, then we can guarantee that 100% sensor nodes stay within this region over time period t.But it becomes too small period to choose for updating routing table. The routing table frequently updates it information consequently it causes congestion of control packet and consume additional energy for control packet. Thus, the minimum time is not opting for calculating stability and updating routing table. On the other hand if we choose the highest value of the calculated time, then we get very few nodes within our range after this time period. In the case of average time period, it has the possibility to have 50% sensor node within the region. Therefore, a time period (t) among this time period is needed to select so that 80% sensor node can be found within the region. To determine this expected time we can follow the following process.First, arrange the time period in ascending order by applying a sorting algorithm like merge sort.Second, use the percentile formula to know the value of nth position of the observances for a fixed percentage.We know,n =�P100�×N+12 where P= Percentages, N= number of sensor node. n is the n th position of the observances that gives us P percentages of observances having to the left side of this position.Updating Time for Horizontal Node Mobility:The sensor nodes move with water currents in horizontal direction, and the movements in vertical direction are almost negligible [26].So in this section, we consider the horizontal node mobility and find out the updating time. Two cases happen in this calculation.We assume the forwarding node F stationary.First case, theplacement of C illustrated in Fig 3 is shown in right half region of FY vertical line.Figure 3:Updating time for horizontal node mobility Node C can move in the left and right direction. If the C node moves in its right direction it passes CF distance. In this case, we calculate the distance CE and CH in the following way. From C, a perpendicular called CO is drawn. ∠COF=90 °, therefore, FO =√(CF2−CO2) where we know CO = |Z f-Z c|. FG is perpendicular on the plane XX′. So, ∠FGE=90° and FG =√(FE2−EG2) where FE = R and EG =|Z f−Z c|. Now we can compute the distance OG = CE = FG−FO.The time (t) to pass the distance CE is CE V where V is the velocity of water current. Second case, the node C illustrated in Fig 4 exists in the left half region of FY vertical line, if the node’s movement is in direction left of the node then CE =FG−OF and if the node’s movement is in the direction of its right CH= OF+FI.Figure 4:Updating time for horizontal node mobility E.Estimation of Priority MetricIt is not good decision to select the target node based on only depth or link stability or residual energy. Weneed to develop a metric with the combining effect ofdepth, link stability and residual energy and this metric isthe best selection criteria for choosing the best suitabletarget sensor node. We are interested to select a node withthe smallest depth that means the smaller the depth, the more suitable target node is. We do also care for higher residual energy (RE) and link stability (L st), the larger the value of residual energy and link stability, the morereliable the target node is. So we can say that the besttarget sensor node’s selection metric is inversely proportional tothe range R divided by depth difference of the sending node(depth s) and forwarding node(depth f)and directly proportional to the product of its path stability and residual energy. The name of target selection is given priority metric (PM) which can be calculated as follows:PM = RE×L st Rs f(1)F.Routing TableEach node forms a routing table of two columns; candidate sensor nodes and theircorresponding priority metric calculated by using eq(1.) Routing table ofunderwater sensor network is demonstrated in Table1. Let the forwarding nodebe F a nd its one hop candidate neighboring sensor nodes be(N1 ,N2 ,…,N n ) within range R. Routing table is updated over the estimated time because linkstability between forwarding node and the candidate sensor nodes alter becauseof water current.TABLE 1: Routing table for PMAG.Algorithm for PMAThe proposed routing algorithm is divided into twoparts called routing table formation algorithm and targetnode selection algorithm that are illustrated in this section.In routing table formation algorithm, Ni represents theone hop neighboring node of the forwarding node and R is transmission range. In the algorithm, depth f indicates the depth of the forwarding node itself. The forwardingsensor node repeats the routing table formation algorithmwhenever the update time elapses. The routing tableformation algorithm is as follows.。

水下无线传感器网络路由协议 - 副本-推荐下载

水下无线传感网络路由协议摘要目前,水下无线传感器网络(UWSNs)已成为一个有前途的各种水下应用的网络技术。

一种能量高效的路由协议在数据传输和实际应用方面起着至关重要的作用。

然而,由于UWSNs的具体特征,如动态结构、窄带宽、能源消耗迅速,和高延迟,很难构建UWSNs路由协议。

在本文中,我们专注于测量UWSNs现有的路由协议。

首先,我们将现有的路由协议分为两类基于决策者。

然后现有的路由协议的性能被详细的比较。

此外,未来路由协议的研究问题在UWSNs中将被仔细分析。

简介在过去的几年中,UWSNs的研究数量迅速增长，由于在许多水下场景中其广泛的应用,例如海洋气候观测、污染跟踪,辅助导航、战术水下监测、防灾等。

几乎所有的应用程序需要水下传感器节点能够有效地提供准确的感知数据。

然而,由于复杂的水下环境,如何快速、有效地收集到的数据传输到汇聚节点在海洋表面是一个非常具有挑战性的研究问题。

实际上,有许多路由协议,提出了陆地无线传感器网络(TWSNs)。

然而,这些不适合UWSNs,主要是因为UWSNs的具体特点,如动态结构、窄带宽、快速能源消耗和高速传播。

通常，UWSNs的传感节点是随着洋流移动和自由浮动的，因此，已存在的路由需要定期的更新和维护，这显然介绍高能源消耗。

然而,它通常是已知的所有传感器节点能量有限,因此它是为UWSNs建造节能路由协议的挑战。

在UWSNs路由协议中,决策者的路线可以分为两类:发送方和接收方。

在基于发送者的路由协议中,发送节点选择下一跳节点本身,而在基于接收者的路由协议中,选择下一跳节点的邻居节点为发送者。

相对基于发送者的路由协议比基于接收者的路由协议更节能,减少通信开销是必需的。

因此,在本文中,路由协议是基于两类调查,基于发送者和基于接收者,如图1所示本文的其余部分组织如下:协议的施工和设计详细介绍。

这些协议的性能比较的在关于能源效率、传输延迟、网络吞吐量方面。

最后,在最后一部分是开放的问题,结论。

无线传感器网络中的数据优先级与服务质量策略

无线传感器网络中的数据优先级与服务质量策略无线传感器网络（Wireless Sensor Network，WSN）是一种由大量分布式的传感器节点组成的网络，用于收集、处理和传输环境中的数据。

在WSN中，数据的优先级和服务质量策略对于网络的可靠性和性能至关重要。

本文将探讨WSN中的数据优先级与服务质量策略，并分析其对网络性能的影响。

首先，数据优先级是指在WSN中传输的数据的重要程度。

不同类型的数据可能具有不同的优先级，例如温度传感器数据和声音传感器数据。

在某些应用场景中，某些数据可能具有更高的优先级，需要更快、更可靠地传输。

因此，为了满足不同数据的传输需求，需要制定相应的数据优先级策略。

一种常见的数据优先级策略是基于事件触发的优先级。

当某个特定事件发生时，与该事件相关的数据将具有更高的优先级。

例如，在火灾监测系统中，当传感器检测到火焰时，与火焰相关的数据将具有更高的优先级，以确保及时传输和处理。

此外，还可以根据数据的重要性和紧急程度分配不同的优先级，以满足不同应用需求。

其次，服务质量策略是指在WSN中为不同数据类型提供不同的服务质量保证。

服务质量包括数据传输的可靠性、时延和带宽等方面。

在WSN中，由于资源有限，无法为所有数据提供相同的服务质量。

因此，需要采取合适的服务质量策略来平衡资源利用和数据传输需求。

一种常见的服务质量策略是基于优先级的服务质量保证。

根据数据的优先级，为高优先级数据分配更多的资源，以确保其可靠性和时延要求。

例如，可以为高优先级数据分配更多的传输带宽和存储空间，以保证其及时传输和存储。

而对于低优先级数据，则可以采用较低的传输速率和存储空间，以节约资源。

此外，还可以采用自适应的服务质量策略来根据网络状态和负载情况动态调整服务质量。

例如，当网络拥塞时，可以降低低优先级数据的传输速率，以保证高优先级数据的传输质量。

当网络负载较轻时，可以提高低优先级数据的传输速率，以提高资源利用效率。

最后，数据优先级和服务质量策略对WSN的性能有重要影响。

采用转发优先级的水下传感网络的机会路由

采用转发优先级的水下传感网络的机会路由吴名星;康松林;陶志勇;谢英辉【摘要】机会路由OR(Opportunistic Routing)在水下传感网络中广泛应用.然而,现存OR协议忽略了一个问题:转发节点采用恒定转发优先级,其加剧了部分节点的能耗,也未能平衡节点间的能量消耗.为此,提出基于轮换转发优先级的机会路由RFP-OR(Rotating Forwarding Priority-based OR).RFP-OR路由利用节点剩余能量,链路可靠性和水压差值构建候选转发节点集,再计算候选转发节点集内每个节点的适度值,并依据适度值给节点设置转发优先级.最后,依据节点的转发优先级设置定时器,进而产生下一跳转发节点.仿真数据表明,提出的RFP-OR路由的活动节点数得到有效的提高,并且数据包传递率也得到了提升.%For underwater sensor networks(USNs),Opportunistic routing(OR) has emerged as a promising paradigm to the design of routing protocols. However, it neglects a critical problem: the immutable transmission priority level of the next-hop forwarding nodes. The characteristics can lead to quickly deplet its battery, and not achieve energy balance. Therefore,Rotating Forwarding Priority-based OR(RFP-OR) is proposed in this paper. RFP-OR considers the remaining energy, link reliability and different depth to select candidate nodes.Then the fitness of each node in candidate nodes set is computed, and the time of timer is set by the fitness to select the next-hop node. Simulation results show that RFP-OR protocol has a good performance in terms of numbers of alive nodes and packet delivery ratio.【期刊名称】《传感技术学报》【年(卷),期】2019(032)001【总页数】6页(P133-138)【关键词】水下传感网;机会路由;转发优先级;数据包传递率;能耗【作者】吴名星;康松林;陶志勇;谢英辉【作者单位】长沙民政职业技术学院软件学院,长沙 410004;中南大学信息科学与工程学院,长沙 410083;长沙民政职业技术学院软件学院,长沙 410004;长沙民政职业技术学院软件学院,长沙 410004【正文语种】中文【中图分类】TN914近期,水下传感网络USNs(Underwater Sensor Networks)被广泛应用于潜艇跟踪、港口监控等水面应用[1-2]。

基于层级的水下传感器网络自适应地理路由协议

ｄａｔｅｓｂａｓｅｄｏｎａｖａｉｌａｂｌｅｅｎｅｒｇｙ，ｄｅｎｓｉｔｙ，ｌｏｃａｔｉｏｎ．ａｎｄｌｅｖｅｌｄｉｆｆｅｒｅｎｃｅｂｅｔｗｅｅｎｎｅｉｇｈｂｏｒｎｏｄｅｓ．ＴｈｅｓｉｍｕｌａｔｉｏｎｓｓｈｏｗｔｈａｔＬＢ — ＡＧＲｃａｎｐｒｏｌｏｎｇｔｈｅｌｉｆｅｔｉｍｅｏｆｔｈｅｗｈｏｌｅｎｅｔｗｏｒｋｓｇｒｅａｔｌｙｂｙｒｅｄｕｃｉｎｇａｎｄｂａｌａｎｃｉｎｇｅｎｅｒｙｇｃｏｎｓｕｍｐｔｉｏｎ．Ｍｏｒｅｏｖｅｒ，ｔｈｅｅｎｄ —
ＵＷＳＮｒｏｕｔｉｎｇｐｒｏｔｏｃｏｌｓｒａｔｅｄｆｏｒｗａｒｄｉｎｇｆａｃｔｏｒｔｏｄｅｔｅｒｍｉｎｅｔｈｅｂｅｓｔｎｅｘｔ — ｈｏｐｆｒｏｍｍｕｌｔｉｐｌｅｑｕａｌｉｉｆｅｄｃａｎｄｉ —
（ＳｃｈｏｏｌｏｆＣｏｍｐｕｔｅｒ，ＱｉｎｇｈａｉＮｏｒｍａｌＵｎｉｖｅｒｓｉｔｙ，Ｘｉｎｉｎｇ８１０００８，Ｃｈｉｎａ）
Ａｂｓｔｒａｃｔ：Ｕｎｄｅｒｗａｔｅｒｓｅｎｓｏｒｎｅｔｗｏｒｋ（ＵＷＳＮ）ｃａｌｌｓｆｏｒｓｐｅｃｉａｌｉｚｅｄｒｏｕｔｉｎｇｐｒｏｔｏｃｏｌｓｔｏａｄｄｒｅｓｓａｄａｐｔａｂｉｌｉｔｙ，ｒｏｂｕｓｔｎｅｓｓ，ｅｎ — ｅｒｇｙｅｆｉｆｃｉｅｎｔａｎｄｂａｌａｎｃｅｄｅｎｅｒｇｙ — ｃｏｎｓｕｍｉｎｇ．Ｔｈｉｓｐａｐｅｒｐｒｏｐｏｓｅｄｌｅｖｅｌ－ｂａｓｅｄａｄａｐｔｉｖｅｇｅｏ・ｒｏｕｔｉｎｇ（ＬＢ・ＡＧＲ）ｐｒｏｔｏｃｏｌｉｎ

动态分层的水下传感器网络分簇路由算法

动态分层的水下传感器网络分簇路由算法洪昌建;吴伟杰;唐平鹏【摘要】To deal with the limitation that flat routing can hardly be accustomed to large scale Underwater Sensor Networks (USN), a new clustering routing algorithm Dynamic Layered Clustering Routing (DLCR) is proposed, which can be accustomed to larger scale networks. This algorithm divides the networks into several layers from top to bottom, and selects the nodes which have more remaining energy and shorter distance to sink as the cluster head nodes, thus, clusters' communication energy consumption are reduced. In order to avoid the same nodes being elected to be cluster head nodes continuously, a dynamic layered mechanism that the networks are divided into different layers in each circle of data gathering is proposed. The experiment shows that DLCR not only has a better stability, but also reduces the energy consumption and prolongs the lifetime of the whole networks.%针对平面路由难以适应较大规模水下传感器网络的局限,该文提出一种能更好地适用于较大规模网络的分簇路由算法DLCR(Dynamic Layered Clustering Routing).该算法将网络自上向下划分为多层,并选择层内与sink节点距离较近、剩余能量较高的节点作为簇头节点,从而降低簇头节点的通信能耗.为了避免同一节点连续被选举为簇头节点,提出一种动态分层机制,每一轮数据采集周期都将网络重新划分为多层.实验证明DLCR不仅具有良好的稳定性,还降低了网络的能耗,延长了网络的寿命.【期刊名称】《电子与信息学报》【年(卷),期】2015(037)006【总页数】7页(P1291-1297)【关键词】水下传感器网络;动态分层机制;分簇路由【作者】洪昌建;吴伟杰;唐平鹏【作者单位】武汉第二船舶设计研究所武汉 430064;武汉第二船舶设计研究所武汉 430064;武汉第二船舶设计研究所武汉 430064【正文语种】中文【中图分类】TP393随着世界各国对海洋权益的日益重视、发展海洋经济热潮的兴起和陆地无线传感器网络研究的迅速发展，水下传感器网络(Underwater Sensor Networks, USN)已经成为新的研究热点[1,2]。

水下无线传感网络路由性能参数研究

水下无线传感网络路由性能参数研究作者：刘小明来源：《科技资讯》 2014年第26期刘小明（淮海工学院信息中心江苏连云港 222005）摘要：水下无线传感网络通信不同与基于电磁波通信的无线传感网络；文章分析了水下通信信号的特征，并与陆地无线传感网络进行比较，并详细描述在水下无线传感网络路由传输中，评价路由通信性能的参数，并对这些参数进行了详细的解释。

关键词：水下无线传感网络通信性能跳数中图分类号:TP393 文献标识码：A 文章编号：1672-3791(2014)09（b)-0006-02在水下无线传感网络中，由于在不同的场景和应用对不同参数，如能耗、时延等参数不同的要求，因此，首先要分析水下水下无线传感网络是利用声信号建立起来的无线自组织网络，它一般是使用飞行器、潜艇或水面舰艇将大量廉价的微型传感器节点随机布放在海底或海中指定的感兴趣水域，节点通过水声无线通信形成的一个多跳的自组织、分布式、多节点、大面积覆盖的水下网络，协作对信息进行采集、处理、分类和压缩，并可通过水声无线传感网络节点直接或中继方式发送到陆基或船基的信息控制中心的综合网络系统。

这样建立起来的交互式网络环境中，岸上的用户能够实时地存取水下传感器节点的数据，并把控制信息传送给水下传感节点。

水下无线传感网络被认为具有广泛的应用前景，如实时或者延时的空间连续水生监控系统在海洋学资料收集，水生环境监控，海洋科学考察，水下考古探险和近海岸保护，污染监控，海上勘探，地震图像传输、海洋环境检测、灾难预防和辅助导航等领域的应用有着极为重要的价值[1,2,3,4]。

1 水声通信特点水下传感网络采用声波作为传播手段[7],水声通信是一种典型的水下通信网络的物理层技术,基于声通信的水下传感网络易于布设，是由大量分布式的水下传感器节点，水下仪器等节点组成的多跳网络。

由于水声信号的传播速度只有1500m/s，使得网络的吞吐量很低。

传输时延和传播损耗是水声信道主要面临两个问题。

一种新的水下无线传感网络的路由协议

一种新的水下无线传感网络的路由协议姜慧霖;滑涛;符意德【期刊名称】《仪表技术与传感器》【年(卷),期】2016(000)009【摘要】针对水下无线传感网络UWSNs（ underwater wireless sensor networks）的数据采集低效的问题，提出一种基于地理位置－机会的水下无线传感网络的路由协议，记为GOR－UWSNs协议。

当传感节点需要传输数据包时，UWSNs协议就利用数据包优先权值ADV（AD vancement）构建候选转发集，再利用归一化的权值NADV（ normalized advance）评估候选转发集内节点成为下一跳节点的“适度性”，并依据节点的NADV值，进行从高至低的排序，形成有序的候选转发集。

NADV融合了距离以及水下信道链路质量信息。

然后，将有序的候选转发集划分不同的簇，使得簇内节点均在彼此的通信范围内，再计算每个簇的期望权值EPA（ expected packet advanced），具有最大EPA的簇成为下一跳转发集。

仿真结果表明，提出的GOR－UWSNS协议有效地提高数据包传输率、降低冗余数据包数。

【总页数】4页(P108-111)【作者】姜慧霖;滑涛;符意德【作者单位】商丘师范学院计算机与信息技术学院，河南商丘 476000;商丘师范学院计算机与信息技术学院，河南商丘 476000;南京理工大学计算机科学与工程学院，江苏南京 210094【正文语种】中文【中图分类】TP393【相关文献】1.一种水下无线传感网络中节能跨层路由协议 [J], 高玲;郑兴旺;陈彭;杨光松;陈朝阳2.水下无线传感网络路由协议研究 [J], 刘春秋;刘小明3.一种面向无线传感网络的AODV改进路由协议 [J], 刘蓉;李红艳4.一种改进的基于蚁群算法的无线传感网络故障容错路由协议 [J], 胡国伟5.一种基于LEACH的无线传感网络路由协议 [J], 纪磊;张欣;文章;高进因版权原因，仅展示原文概要，查看原文内容请购买。