共查询到20条相似文献,搜索用时 15 毫秒
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针对水下无线传感网络能量效率低、生命周期短的问题,提出了一种负载均衡且能量高效的水下分簇(load balanced and energy efficient underwater clustering,LBEEUC)协议。该算法在分簇过程中首先根据节点的经验负载来确定节点所在区域簇头的比例,使经验负载大的区域分布较多的簇头,分担数据转发的任务,均衡网络的能耗;其次在节点入簇时,在簇内设置中继节点,用于均衡远离簇头节点的传输能耗,并提前进行数据融合,减少数据冗余;最后在建立簇间路由时,利用Q 学习算法根据路径消耗的总能量最小的原则选择最优传输路径。仿真结果表明,本算法有效地均衡了网络的能耗,提高了能量利用效率,进而提高了网络的生存时间。 相似文献
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本文结合陆上无线网络原理,提出了一种水下信息网络教学实验系统设计方案。该实验系统分为水下和陆上两部分,基于水声通信机的水下声学网络通过浮标网关节点实现了与陆上无线传感器网络信息的交互,进而构成立体式水下信息网络教学实验平台。该系统不仅能够进行相关学科的教学演示,同时也能够作为该方向的基础科研平台。 相似文献
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To reduce excessive computing and communication loads of traditional fault detection methods, a neighbor-data analysis based node fault detection method is proposed. First, historical data is analyzed to confirm the confidence level of sensor nodes. Then a nodes reading data is compared with neighbor nodes which are of good confidence level. Decision can be made whether this node is a failure or not. Simulation shows this method has good effect on fault detection accuracy and transient fault tolerance, and never transfers communication and computing overloading to sensor nodes. 相似文献
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基于簇的无线传感器网络入侵检测系统 总被引:1,自引:1,他引:1
基于无线传感器网络的分簇结构,运用Agent技术设计了一个入侵检测系统.在网络中的每个节点部署IDS代理,其中包括本地检测Agent和全局检测Agent两个不同代理,分别完成不同的检测任务.提出采用蓝牙通信技术,引用蓝牙散射网形成算法TPSF构建传感器网络的簇节点层,完成簇的划分,进而对不同的Agent进行任务分配.通过限制节点的角色对算法进行改进,减轻节点的复杂度,从而使IDS代理能有效地工作,提高节点的安全系数. 相似文献
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Recently, underwater acoustic sensor networks (UASNs) have been considered as a promising approach for monitoring and exploring the oceans in lieu of traditional underwater wireline instruments. As a result, a broad range of applications exists ranging from oil industry to aquaculture and includes oceanographic data collection, disaster prevention, offshore exploration, assisted navigation, tactical surveillance, and pollution monitoring. However, the unique characteristics of underwater acoustic communication channels, such as high bit error rate, limited bandwidth, and variable delay, lead to a large number of packet drops, low throughput, and significant waste of energy because of packets retransmission in these applications. Hence, designing an efficient and reliable data communication protocol between sensor nodes and the sink is crucial for successful data transmission in underwater applications. Accordingly, this paper is intended to introduce a novel nature‐inspired evolutionary link quality‐aware queue‐based spectral clustering routing protocol for UASN‐based underwater applications. Because of its distributed nature, link quality‐aware queue‐based spectral clustering routing protocol successfully distributes network data traffic load evenly in harsh underwater environments and avoids hotspot problems that occur near the sink. In addition, because of its double check mechanism for signal to noise ratio and Euclidean distance, it adopts opportunistically and provides reliable dynamic cluster‐based routing architecture in the entire network. To sum up, the proposed approach successfully finds the best forwarding relay node for data transmission and avoids path loops and packet losses in both sparse and densely deployed UASNs. Our experimental results obtained in a set of extensive simulation studies verify that the proposed protocol performs better than the existing routing protocols in terms of data delivery ratio, overall network throughput, end‐to‐end delay, and energy efficiency. 相似文献
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在以监测为目的的水下传感器网络中,较好的网络覆盖率和连通率是完成监测任务的重要保证.以改善覆盖效果为目标的水下覆盖保持路由算法NCPR算法相对比LEACH-Coverage-U算法有效的延长了网络覆盖时间,但是该算法连通性表现较差,同时存在靠近SINK节点的簇首由于需要转发大量数据而过早死亡的问题.本文提出一种分布式的网络不均匀分层的覆盖保持路由(Network Unevenly Layered Coverage Preserving Routing,NULCPR)算法,由SINK节点开始逐层向下建立网络,同时每层网络节点通信半径也随层号增加而逐渐增大.每层网络独立运行NCPR算法以使该层节点成簇,并通过簇首向上建立连通链路以保证网络连通.仿真结果表明,与NCPR算法相比,NULCPR算法提高了网络连通率以及覆盖率,并且降低了网络能耗,证明了该算法的有效性. 相似文献
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Underwater wireless sensor network (UWSN) is a network made up of underwater sensor nodes, anchor nodes, surface sink nodes or surface stations, and the offshore sink node. Energy consumption, limited bandwidth, propagation delay, high bit error rate, stability, scalability, and network lifetime are the key challenges related to underwater wireless sensor networks. Clustering is used to mitigate these issues. In this work, fuzzy-based unequal clustering protocol (FBUCP) is proposed that does cluster head selection using fuzzy logic as it can deal with the uncertainties of the harsh atmosphere in the water. Cluster heads are selected using linguistic input variables like distance to the surface sink node, residual energy, and node density and linguistic output variables like cluster head advertisement radius and rank of underwater sensor nodes. Unequal clustering is used to have an unequal size of the cluster which deals with the problem of excess energy usage of the underwater sensor nodes near the surface sink node, called the hot spot problem. Data gathered by the cluster heads are transmitted to the surface sink node using neighboring cluster heads in the direction of the surface sink node. Dijkstra's shortest path algorithm is used for multi-hop and inter-cluster routing. The FBUCP is compared with the LEACH-UWSN, CDBR, and FBCA protocols for underwater wireless sensor networks. A comparative analysis shows that in first node dies, the FBUCP is up to 80% better, has 64.86% more network lifetime, has 91% more number of packets transmitted to the surface sink node, and is up to 58.81% more energy efficient than LEACH-UWSN, CDBR, and FBCA. 相似文献
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The design of energy‐efficient underwater wireless sensor networks (UWSNs) poses many challenges due to the intrinsic properties of propagation medium and limited battery power of sensor nodes. This paper proposes the concept of optimal clustering for three‐dimensional (3D) UWSNs leveraging compressive sensing (CS) and principal component analysis (PCA) technique of data compression. Optimal clustering reduces the energy consumption by selecting the optimal number of clusters whereas CS and PCA compression techniques reduce the energy consumption by considering a lesser number of samples and reduce the data redundancy at cluster heads (CHs) level, respectively. Moreover, three communication techniques like acoustic, electromagnetic (EM), and free‐space optical (FSO) wave are considered for communication in 3D UWSNs. We compared the energy efficiency for all three communication techniques by examining the three base station (BS) positions at the center, at the corner, and at the lateral midpoint of the 3D sensing area. Moreover, performance parameters (network lifetime, throughput, packet drop rate, and latency) are also evaluated for 3D UWSNs. It is observed that PCA outperforms the CS technique. The proposed technique is suitable for long‐term and densely deployed 3D UWSNs, in which saving energy is of crucial importance. 相似文献
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休眠机制是传感器网络节点节约能量、延长工作寿命的重要手段之一。现存的水下传感器网络MAC协议主要考虑提高网络传输性能,对休眠机制的研究和涉及较少,并且仅有的一些休眠策略存在着因节点工作时间较为分散而导致的节点休眠-唤醒频繁的问题。节点频繁唤醒不仅会浪费额外的能量来启动电路,折损硬件寿命,还会增加数据传输冲突的概率。针对水声网络信道的独特性质,提出了一个基于树形拓扑结构的水下传感器网络节点休眠算法,该算法能够有效缩短节点唤醒次数,延长休眠时间,并保证端到端的传播延迟不受休眠时间的影响。该算法无冲突也无需预约信道,保证了较高的网络流量。最后,通过仿真实验验证了算法的可用性和效能。 相似文献
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基于网格结构无线传感网络故障诊断算法 总被引:3,自引:0,他引:3
无线传感网中节点的数据信息具有空间相关性,可以通过邻居节点数据的比较来完成网络的故障诊断。网络中有时会出现瞬时故障,影响网络的诊断精确度。文中提出了一种基于网格结构的无线传感网络故障诊断算法,算法通过相邻节点历史数据信息之间的比较来确定节点最终状态,有效地避免了瞬时故障对节点诊断的影响。仿真结果表明,文中算法可保证较高地诊断精确度并能节省一定的能量。 相似文献
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In this paper, a localisation method for determining the position of fixed sensor nodes in an underwater wireless sensor network (UWSN) is introduced. In this simple and range-free scheme, the node localisation is achieved by utilising an autonomous underwater vehicle (AUV) that transverses through the network deployment area, and that periodically emits a message block via four directional acoustic beams. A message block contains the actual known AUV position as well as a directional dependent marker that allows a node to identify the respective transmit beam. The beams form a fixed angle with the AUV body. If a node passively receives message blocks, it could calculate the arithmetic mean of the coordinates existing in each messages sequence, to find coordinates at two different time instants via two different successive beams. The node position can be derived from the two computed positions of the AUV. The major advantage of the proposed localisation algorithm is that it is silent, which leads to energy efficiency for sensor nodes. The proposed method does not require any synchronisation among the nodes owing to being silent. Simulation results, using MATLAB, demonstrated that the proposed method had better performance than other similar AUV-based localisation methods in terms of the rates of well-localised sensor nodes and positional root mean square error. 相似文献
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提出一种基于阵列传输结构的无线传感器网络安全定位算法(USA)。该算法主要解决水下无线传感器网络(UWSN)面临的一些安全威胁问题。以提高无线传感器网络安全性,特别是位置信息的安全性为设计目标。利用节点协作形成的阵列作为天线阵列进行相互通信,在不增加额外硬件成本的同时,还获得阵列天线给无线传感器网络带来的优势,如减小多径效应、提高接收端的信噪比、增加系统容量等。USA算法基于这种阵列结构使网络得到很高安全特性,特别是,对Wormhole攻击具有非常好的抵御性能。仿真实验证明该算法的有效性。 相似文献
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Amit Karmaker Mohammad Shah Alam Md. Mahedee Hasan Andrew Craig 《International Journal of Communication Systems》2020,33(3)
Maximizing the lifespan of wireless sensor networks is currently drawing a lot of attention in the research community. In order to reduce energy consumption, sensor nodes that are far from the base station avoid sending data directly. As a result, several disjoint clusters are formed, and nodes within a cluster send their data through the cluster head to avoid long transmissions. However, several parameters related to transmission cost need to be considered when selecting a cluster head. While most of the existing research work considers energy and distance as the most stringent parameters to reduce energy consumption, these approaches fail to create a fair and balanced cluster. Consequently, unbalanced clusters are formed, resulting in the degradation of overall performance. In this research work, a cluster head selection algorithm is proposed that covers all parts of the sensing area in a balanced manner, saving a significant amount of energy. Furthermore, a capture effect–based intracluster communication mechanism is proposed that efficiently utilizes the time slot under various traffic conditions. A Näive Bayes classifier is used to adapt the window size dynamically according to the traffic pattern. Finally, a simulation model using OMNeT++ is developed to compare the proposed approach with the pioneer clustering approach, LEACH, and the contemporary LEACH‐MAC protocol in terms of performance. The results of the simulation indicate that the proposed approach improves the overall performance in terms of network lifetime, energy efficiency, and throughput. 相似文献
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Nishi Yadav;Pabitra Mohan Khilar;Suraj Sharma; 《International Journal of Communication Systems》2024,37(11):e5786
The underwater acoustic sensor network is a fundamental source for ocean exploration. The potential applications of underwater acoustic sensor network (UASN) include seismic imaging, disaster prevention, mine reconnaissance, pollution monitoring, exploration of natural resources, and military surveillance. To acquire accurate results, implementing all applications of underwater sensor networks requires an adequate network connection and communication technology. The precise placement of underwater sensor nodes needs to be identified in order to achieve effective communication. To accomplish the requirement, the paper presents an efficient localization algorithm to compensate the stratification effect based on an improved underwater salp swarm optimization technique (LAS-IUSSOT). To compute the location of sensor nodes with high accuracy, the nodes are initially randomly deployed in three-dimensional underwater acoustic sensor network (3D-UASN). After that, the hybridization of centroid-based localization and the ray theory technique is used, and then, the degree of coplanarity is analyzed among the underwater sensor nodes. Then, the computation of the location of unknown nodes is performed using improved underwater salp swarm optimization technique (IUSSOT) to obtain the optimized location and compensate the impact of the stratification. The comparison of the simulation results of the existing algorithm and the proposed algorithm is performed. The LAS-IUSSOT achieves 40.46% and 28.00% accuracy in terms of localization of underwater sensor nodes for both the sparse and dense regions in 3D-UASN. The LAS-IUSSOT achieves 49.39% and 62.57% accuracy in terms of ranging of underwater sensor nodes for both the sparse and dense regions in 3D-UASN. Simulation results illustrate that the proposed algorithm outperforms the existing algorithm in terms of localization and ranging accuracy in both sparse and dense regions in 3D-UASN, root mean square error (RMSE), normalized localization error (NLE), computation time, and convergence rate. 相似文献