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1.
在分析了无线传感器网络中传统的LEACH和LEACH-C路由协议基础上,结合MTE路由协议思想,提出了一种新的改进型分簇分层路由协议(improved clustering hierarchical routing protocol,ICH).文中簇首节点可以采用多跳方式传输数据包,且在选择中继节点时考虑节点剩余能量,对进入下一轮的条件进行了限制.实验表明,改进后的ICH协议的节点存活率比LEACH-C好.  相似文献   

2.
分析了低功耗自适应分簇路由协议(LEACH)算法,对算法中簇头选举数目的随机性做了改进并且在簇头选举时加入了对节点剩余能量的考虑,同时提出采用欧式平面上两条曲线交叉概率很大的思想,在簇头与基站之间建立多跳链路,从而解决了原协议中簇头与基站单跳通信能量消耗过大的问题.性能分析和仿真实验表明:改进的协议有效均衡了节点能耗,提高了网络寿命.  相似文献   

3.
基于能耗均衡的水下传感器网络分簇路由算法   总被引:1,自引:0,他引:1  
姜卫东  郭勇  刘胤祥 《声学技术》2015,34(2):134-138
针对水下传感器网络能耗不均衡问题,提出一种能耗均衡的多跳非均匀分簇路由算法。算法在水下传感器网络非均匀分簇的基础上,通过改进节点簇头竞选的阈值计算方式,解决了网络后期簇头竞选阈值低导致的网络能耗激增;通过引入多跳路由选择公式,综合考虑节点剩余能量和链路能耗,延长网络生命周期。仿真表明,提出的算法生成簇头数目稳定,能耗较低,并且能有效延长水下传感器网络的生命周期。  相似文献   

4.
    
Wireless Sensor Network (WSN) comprises a massive number of arbitrarily placed sensor nodes that are linked wirelessly to monitor the physical parameters from the target region. As the nodes in WSN operate on inbuilt batteries, the energy depletion occurs after certain rounds of operation and thereby results in reduced network lifetime. To enhance energy efficiency and network longevity, clustering and routing techniques are commonly employed in WSN. This paper presents a novel black widow optimization (BWO) with improved ant colony optimization (IACO) algorithm (BWO-IACO) for cluster based routing in WSN. The proposed BWO-IACO algorithm involves BWO based clustering process to elect an optimal set of cluster heads (CHs). The BWO algorithm derives a fitness function (FF) using five input parameters like residual energy (RE), inter-cluster distance, intra-cluster distance, node degree (ND), and node centrality. In addition, IACO based routing process is involved for route selection in inter-cluster communication. The IACO algorithm incorporates the concepts of traditional ACO algorithm with krill herd algorithm (KHA). The IACO algorithm utilizes the energy factor to elect an optimal set of routes to BS in the network. The integration of BWO based clustering and IACO based routing techniques considerably helps to improve energy efficiency and network lifetime. The presented BWO-IACO algorithm has been simulated using MATLAB and the results are examined under varying aspects. A wide range of comparative analysis makes sure the betterment of the BWO-IACO algorithm over all the other compared techniques.  相似文献   

5.
The most important problem in a Wireless Sensor Network (WSN) is to optimize the use of its limited energy provision, so that it can fulfil its monitoring task as long as possible. Among known available approaches that can be used to improve power management, lifetime coverage optimization provides activity scheduling which ensures sensing coverage while minimizing the energy cost. In this article an approach called Perimeter-based Coverage Optimization protocol (PeCO) is proposed. It is a hybrid of centralized and distributed methods: the region of interest is first subdivided into subregions and the protocol is then distributed among sensor nodes in each subregion. The novelty of the approach lies essentially in the formulation of a new mathematical optimization model based on the perimeter-coverage level to schedule sensors' activities. Extensive simulation experiments demonstrate that PeCO can offer longer lifetime coverage for WSNs compared to other protocols.  相似文献   

6.
在研究了一些分簇算法基础上,提出基于连通可靠度约束的、适合大规模随机部署的快速成簇算法。仿真表明基于连通可靠度约束的快速成簇算法得到的分簇覆盖面广、簇头分布合理、稳定性强,与最小ID分簇及优化的最大连接数分簇算法相比,得到簇头数量少,分簇更合理,各成员节点与簇头的连通可靠度好,能保证网络的稳定性与健壮性,大大减少重构开销带来的通信代价,有利于均衡网络能量消耗,延长网络生命周期。  相似文献   

7.
嵌入式无线传感器网络研究   总被引:2,自引:0,他引:2  
简要叙述了无线传感器网络的发展史,讨论了传感器节点的功耗、成本、组网方面的属性及要求,概述了传感器节点的传感单元、通信单元、处理单元及供电单元等四大基本功能单元和两个辅助单元,介绍了一些常用电池和几款适合嵌入式节点设计的微控制器和射频器件,阐述了无线传感器网络领域一些挑战性的问题以及传感器节点的能量管理问题.  相似文献   

8.
水下无线传感器网络   总被引:3,自引:0,他引:3  
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。  相似文献   

9.
    
During the last two decades, mobile communication systems (such as GSM, GPRS and 3G networks), wireless broadcasting networks, wireless local area networks (WLAN or WiFi), and wireless sensor networks have been successfully developed and widely deployed through different technological routes for providing a variety of communication services in different application scenarios. While making tremendous contributions to social progress and economic growth, these heterogeneous wireless networks consume a lot of energy in achieving overlapped service coverage, and at the same time, generate strong electromagnetic interference (EMI) and radiation pollution, especially in big cities with high building density and user population. In order to guarantee the overall return on investment (ROI), improve user experience and quality of service (QoS), save energy, reduce EMI and radiation pollution, and enable the sustainable deployment of new profitable applications and services, this paper proposes a cross-network cooperation mechanism to effectively share network resources and infrastructures, and then adaptively control and match multi-network energy distribution characteristics according to actual user/service requirements in different geographic areas. Some idle or lightly-loaded Base Stations (BS or BSs) will be temporally turned off for saving energy and reducing EMI. Initial simulation results show the proposed approach can significantly improve the overall energy efficiency and QoS performance across multiple cooperative wireless networks.  相似文献   

10.
提出了在具有移动基站的无线传感器网络中的一种新的路由协议,该协议在基站移动时只需要在一个小的区域内更新基站的位置信息,因此既节省了传感器节点的能量,又使基站在移动过程中仍可保持与传感器节点的持续通信.理论分析和模拟研究表明,与全局更新基站位置信息的路由协议相比,该协议降低了基站位置信息更新的代价,减少了无线信道的冲突概率,减少了延迟,可适用于对延迟要求较高的大规模无线传感器网络.  相似文献   

11.
    
Energy conservation is a significant task in the Internet of Things (IoT) because IoT involves highly resource-constrained devices. Clustering is an effective technique for saving energy by reducing duplicate data. In a clustering protocol, the selection of a cluster head (CH) plays a key role in prolonging the lifetime of a network. However, most cluster-based protocols, including routing protocols for low-power and lossy networks (RPLs), have used fuzzy logic and probabilistic approaches to select the CH node. Consequently, early battery depletion is produced near the sink. To overcome this issue, a lion optimization algorithm (LOA) for selecting CH in RPL is proposed in this study. LOA-RPL comprises three processes: cluster formation, CH selection, and route establishment. A cluster is formed using the Euclidean distance. CH selection is performed using LOA. Route establishment is implemented using residual energy information. An extensive simulation is conducted in the network simulator ns-3 on various parameters, such as network lifetime, power consumption, packet delivery ratio (PDR), and throughput. The performance of LOA-RPL is also compared with those of RPL, fuzzy rule-based energy-efficient clustering and immune-inspired routing (FEEC-IIR), and the routing scheme for IoT that uses shuffled frog-leaping optimization algorithm (RISA-RPL). The performance evaluation metrics used in this study are network lifetime, power consumption, PDR, and throughput. The proposed LOA-RPL increases network lifetime by 20% and PDR by 5%–10% compared with RPL, FEEC-IIR, and RISA-RPL. LOA-RPL is also highly energy-efficient compared with other similar routing protocols.  相似文献   

12.
    
Recently, Wireless sensor networks (WSNs) have become very popular research topics which are applied to many applications. They provide pervasive computing services and techniques in various potential applications for the Internet of Things (IoT). An Asynchronous Clustering and Mobile Data Gathering based on Timer Mechanism (ACMDGTM) algorithm is proposed which would mitigate the problem of “hot spots” among sensors to enhance the lifetime of networks. The clustering process takes sensors’ location and residual energy into consideration to elect suitable cluster heads. Furthermore, one mobile sink node is employed to access cluster heads in accordance with the data overflow time and moving time from cluster heads to itself. Related experimental results display that the presented method can avoid long distance communicate between sensor nodes. Furthermore, this algorithm reduces energy consumption effectively and improves package delivery rate.  相似文献   

13.
    
Artificial intelligence (AI) techniques have received significant attention among research communities in the field of networking, image processing, natural language processing, robotics, etc. At the same time, a major problem in wireless sensor networks (WSN) is node localization, which aims to identify the exact position of the sensor nodes (SN) using the known position of several anchor nodes. WSN comprises a massive number of SNs and records the position of the nodes, which becomes a tedious process. Besides, the SNs might be subjected to node mobility and the position alters with time. So, a precise node localization (NL) manner is required for determining the location of the SNs. In this view, this paper presents a new quantum bird migration optimizer-based NL (QBMA-NL) technique for WSN. The goal of the QBMA-NL approach is for determining the position of unknown nodes in the network by the use of anchor nodes. The QBMA-NL technique is mainly based on the mating behavior of bird species at the time of mating season. In addition, an objective function is derived based on the received signal strength indicator (RSSI) and Euclidean distance from the known to unknown SNs. For demonstrating the improved performance of the QBMA-NL technique, a wide range of simulations take place and the results reported the supreme performance over the recent NL techniques.  相似文献   

14.
姜卫东  雷辉  郭勇 《声学技术》2014,33(2):176-179
针对水声传感器网络的簇间路由选择问题,提出了一种基于前向网关的低时延能耗均衡路由算法,该算法采用最优方向角原则和能耗均衡原则选择中继簇头和中继网关,以减小长延迟和高能耗对水声通信的影响。仿真结果表明该算法在网络平均能耗、端到端时延和网络生命周期等方面具有较好的性能。  相似文献   

15.
    
An IoT-based wireless sensor network (WSN) comprises many small sensors to collect the data and share it with the central repositories. These sensors are battery-driven and resource-restrained devices that consume most of the energy in sensing or collecting the data and transmitting it. During data sharing, security is an important concern in such networks as they are prone to many threats, of which the deadliest is the wormhole attack. These attacks are launched without acquiring the vital information of the network and they highly compromise the communication, security, and performance of the network. In the IoT-based network environment, its mitigation becomes more challenging because of the low resource availability in the sensing devices. We have performed an extensive literature study of the existing techniques against the wormhole attack and categorised them according to their methodology. The analysis of literature has motivated our research. In this paper, we developed the ESWI technique for detecting the wormhole attack while improving the performance and security. This algorithm has been designed to be simple and less complicated to avoid the overheads and the drainage of energy in its operation. The simulation results of our technique show competitive results for the detection rate and packet delivery ratio. It also gives an increased throughput, a decreased end-to-end delay, and a much-reduced consumption of energy.  相似文献   

16.
提出一种能量有效的按需缓存策略BESS,中间节点收到源节点到sink节点数据包后,用二分法根据节点位置选择缓存节点;并由节点剩余能量和能量阈值判断是否应该存储数据项,能量阈值根据每个节点缓存数据项个数不同动态确定;缓存替换中通过建立模型得到影响缓存发现能量的一些因素,根据这些因素构造出缓存替换策略的权值函数.仿真结果表明,与已存在的GCCS策略相比,平均时延降低4.8%~31.6%,平均能耗减少15.1%~35.6%,缓存字节命中率提高3.64%~8.16%.  相似文献   

17.
    
Wireless Sensor Networks (WSNs) are large-scale and high-density networks that typically have coverage area overlap. In addition, a random deployment of sensor nodes cannot fully guarantee coverage of the sensing area, which leads to coverage holes in WSNs. Thus, coverage control plays an important role in WSNs. To alleviate unnecessary energy wastage and improve network performance, we consider both energy efficiency and coverage rate for WSNs. In this paper, we present a novel coverage control algorithm based on Particle Swarm Optimization (PSO). Firstly, the sensor nodes are randomly deployed in a target area and remain static after deployment. Then, the whole network is partitioned into grids, and we calculate each grid’s coverage rate and energy consumption. Finally, each sensor nodes’ sensing radius is adjusted according to the coverage rate and energy consumption of each grid. Simulation results show that our algorithm can effectively improve coverage rate and reduce energy consumption  相似文献   

18.
根据有风时气体浓度衰减模型,采用量子粒子群优化(quantum particle swarm optimization,QPSO)算法实现无线传感网络中的气体源点定位,考虑到传感器节点测量气体浓度时存在门限值的实际情况,引入力导向思想,通过使传感器节点产生虚拟力来影响QPSO算法的位置更新过程,使粒子移动更有目的性,引...  相似文献   

19.
通过对无线传感器网络(Wireless Sensor Network,WSN)和AODV路由协议的特性进行分析,认为AODV协议(Ad—hoc On—Demand Distance Vector Routing)具有在无线传感器网络中应用的可行性,只是在网络能量效率方面考虑不多.本文详细给出了改进方案,利用协议头中原有的保留选项来存储平均路径能量,选路时采用最小路由最大路径能量策略,同时增加转发RREQ和发送RREP的延迟时间.用NS-2软件对改进后方案从吞吐量、延时、剩余能量等角度进行仿真,结果证明该方案可行.  相似文献   

20.
考虑到无线传感器分簇网络中簇的规模、簇头数量和节点剩余能量是能量有效型分簇路由算法关注的重要指标,提出了一种基于能量优化模型(EOM)的分布式分簇算法——EOMC,该算法通过建立网络能耗优化模型,以最优簇头数构建分簇通信规模,并结合功率控制将候选簇头限制在一定宽度的选举环带,使得簇头分布均衡,同时兼顾到节点剩余能量进行分簇,以达到均衡节点能耗,延长网络生存期的目的。与低能耗自适应分簇分层(LEACH)协议的对比仿真的结果表明,该算法能够达到预期指标,算法的开销相对较小。  相似文献   

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