基于量子PSO传感网络分簇算法仿真研究

研究无线传感器分簇节点优化问题,针对无线传感器网络分簇算法由于簇头的不均匀分布带来的能耗利用不均衡以及簇头的瓶颈,导致能量过早消耗,网络寿命周期缩短.为了延长无线传感网络生命周期,提高能量利用效率,提出了一种粒子群(PSO)算法优化的无线传感器网络分簇算法.采用量子粒子群算法分簇策略使簇间能量优化平衡,使整个网络分成若干个虚拟网格,每个虚拟网格形成一个簇,采用唯一簇头选举法产生簇头,且簇内成员可以根据局部的信息调整簇的大小.仿真结果表明,提出的分簇算法很好的使网络的能耗达到了均衡,节约了簇头节点的能量,从而延长网络的寿命,为优化网络通信提供了依据.     

煤矿无线多媒体传感器网络能量均衡路由方法

针对煤矿井下多媒体信息采集需求及巷道带状空间与传感器网络中节点能量受限的特点,构建了煤矿无线多媒体传感器网络(WMSN)系统模型,提出了一种由基于位置与剩余能量的虚拟网格中层次分簇(PREHCVG)算法及基于能量与距离的蚁群路由(EDACR)算法构成的煤矿WMSN能量均衡路由方法。该方法中,PREHCVG算法根据网络中节点的通信半径对节点进行虚拟网格划分来实现分簇管理,并结合节点的剩余能量及所处位置信息选取簇头节点;EDACR算法根据节点的剩余能量及节点间距离信息,从簇头节点及备选簇头节点中选出路由节点。仿真结果表明,与经典LEACH算法相比,煤矿WMSN能量均衡路由方法能够有效均衡WMSN中节点的能量消耗,减少WMSN中能量耗尽的节点数,延长WMSN生命周期。     

一种基于网格的无线传感器网络分簇路由协议

为延长网络生存时间,提出了一种基于网格的无线传感器网络分簇路由协议.整个网络分成若干个虚拟网格,每个虚拟网格形成一个簇,采用唯一簇头选举法产生簇头,且簇内成员可以根据局部的信息调整簇的大小,达到节省能量的目的.仿真实验和分析表明:该协议能均衡网络能量,延长网络的生存时间.     

一种基于地理位置的无线传感器网络分簇路由算法

针对大规模无线传感器网络,提出了一种基于地理位置的双基站分簇路由算法。该算法在网络覆盖区域边缘设置两个基站,按照地理位置将区域划分为若干均匀分布网格。每个网格根据节点剩余能量和到网格内其它节点平均距离远近选择簇头。通过仿真分析,证明该算法能减少网络能耗,延长网络生存时间。     

基于蚁群算法的DSR协议研究与仿真

为了延长无线网络的生存时间,避免簇内过早的出现盲节点,提出了一种利用蚁群算法优化的DSR协议。在划分簇和选择簇头的研究过程中,动态追踪无线网络中节点的变化情况,分权衡量节点的移动速度和剩余能量,选择合适的簇首和稳定的信息传播半径,并根据信息传播半径的大小对传感器节点的地理位置进行虚拟网格划分,最终实现信息的稳定传输和能量的有效利用。仿真结果表明,与LEACH和CDSR协议相比,该算法不仅有效地提高了信息传输效率、均衡了网络节点的能量消耗、延长了网络寿命,并且有效增强了无线自组织网络的鲁棒性。     

模糊边缘检测无线传感器网络分簇算法

针对传统分簇算法簇头选举仅单一考虑节点位置或能量分布的问题,提出了一种基于模糊边缘检测的无线传感网络分簇算法,该算法综合考虑拓扑边缘信息和节点能量分布,根据网络能量分布情况调整带宽内边缘节点参与簇头选举的概率.仿真结果表明,该算法簇头选举相对于LEACH算法分布更加合理,有效延长网络生命周期.     

基于网格的动态能量阈值的簇头选择算法

有效地使用传感节点的能量进而延长网络寿命成为设计无线传感网路由协议的一项挑战性的工作.而动态簇被认为提高能量利用率的有效技术之一.然而,簇头分布不均匀加速了网络能量的消耗,降低了网络寿命.为此,提出基于网格的动态能量阈值的簇头选择算法GDET-CH(Grid Dynamic Energy Threshold-based Cluster Header),平衡簇头分布.GDET-CH算法先将网络区域划分多个网格,并每个网格产生一个簇头.然后,利用节点离网格中心距离和节点剩余能量选择簇头.最后,引用动态能量阈值机制,只有当节点剩余能量大于能量阈值才可能成为簇头,进而平衡网络能耗.实验数据表明,与DDEEC和EDDDEC算法相比,GDET-CH算法的网络寿命分别提高了近24.5%和36%.     

能量高效的传感器网络虚拟骨干网构造算法

提出一种新的可用于无线自组传感器网络路由中的能量高效的虚拟骨干网构造算法。该算法将网络中的节点按照地理距离最近的原则划分为若干簇,簇头与簇成员的距离为k-hop,增大了簇的规模,减少了通信开销;利用最小连通支配集理论优化簇内结构,选择新的参数作为权值,在保证骨干网规模的同时,优先选择剩余能量高的节点担任骨干节点,均衡了网络的能量消耗,从而延长了网络寿命。仿真结果表明,该算法构造的虚拟骨干网规模较小,对降低路由复杂度、延长传感器网络寿命有较好的效果。     

基于虚拟网格的无线传感器网络分簇路由算法

针对WSNs路由协议中链路通信负载不均引发的能量空洞问题,提出一种基于虚拟网格的动态聚簇策略IDCS和考虑数据转发延迟的最大化网络生命周期的动态负载均衡路由算法DCDLB。IDCS依据节点的通信半径将网络划分成若干虚拟网格,采用考虑节点能量和位置因素的分布式簇首选举策略,并引入基于簇首能量水平的动态簇首轮换机制。DCDLB综合考虑簇首间能耗均衡和数据多跳转发延迟来构建路由,实现网络生命周期的最大化。实验结果表明,DCDLB路由算法在延长网络生命周期和降低数据转发延迟方面优于LEACH,HEED和CRVB路由算法。     

虚拟力导向的无线传感器网络覆盖策略

摘要;通过建立传感器节点与节点、节点与目标之间的虚拟力模型,制定一种新的簇头选择策略,将节点剩余能量和距离目标的大小作为参数,选择离目标近且剩余能量大的节点作为簇头,提高网络覆盖率;通过虚拟单元格进行分簇,以保持簇头节点之间的数据通信,同时休眠其它非簇头节点的周期性轮换簇头的方式来优化节点能耗,以此来延长网络寿命.与经典GAF算法比较,理论分析和仿真实验结果表明了该算法在网络覆盖率和节点生存时间上均有明显的优势.     

An energy-saving routing architecture with a uniform clustering algorithm for wireless body sensor networks

Wireless body sensor networks are expected to extend human-centered applications in large-scale sensing and detecting environments. Energy savings has become one of the most important features of the sensor nodes to prolong their lifetime in such networks. To provide reasonable energy consumption and to improve the network lifetime of wireless body sensor network systems, new and efficient energy-saving schemes must be developed. An energy-saving routing architecture with a uniform clustering algorithm is proposed in this paper to reduce the energy consumption in wireless body sensor networks. We adopted centralized and cluster-based techniques to create a cluster-tree routing structure for the sensor nodes. The main goal of this scheme is to reduce the data transmission distances of the sensor nodes by using the uniform cluster structure concepts. To make an ideal cluster distribution, the distances between the sensor nodes are calculated, and the residual energy of each sensor node is accounted for when selecting the appropriate cluster head nodes. On the basis of the uniform cluster location, the data transmission distances between the sensor nodes can be reduced by employing an adaptive multi-hop approach. The energy consumption is reduced, and the lifetime is extended for the sensor nodes by balancing the network load among the clusters. Simulation results show that the proposed scheme outperforms the previously known schemes in terms of the energy consumption and the network lifetime for the wireless body sensor networks.     

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.     

Dynamic cluster head for lifetime efficiency in WSN

Saving energy and increasing network lifetime are significant challenges in wireless sensor networks （WSNs）. In this paper, we propose a mechanism to distribute the responsibility of cluster-heads among the wireless sensor nodes in the same cluster based on the ZigBee standard, which is the latest WSN standard. ZigBee supports ad hoc on-demand vector （AODV） and cluster-tree routing protocols in its routing layer. However, none of these protocols considers the energy level of the nodes in the network establishing process or in the data routing process. The cluster-tree routing protocol supports single or multi-cluster networks. However, each single cluster in the multi-cluster network has only one node acting as a cluster head. These cluster-heads are fixed in each cluster during the network lifetime. Consequently, using these cluster-heads will cause them to die quickly, and the entire linked nodes to these cluster-heads will be disconnected from the main network. Therefore, the proposed technique to distribute the role of the cluster head among the wireless sensor nodes in the same cluster is vital to increase the lifetime of the network. Our proposed technique is better in terms of performance than the original structure of these protocols. It has increased the lifetime of the wireless sensor nodes, and increased the lifetime of the WSN by around 50% of the original network lifetime.     

基于混合量子进化算法的高效节能无线传感器网络路由算法

在无线传感器网络中,层次型路由算法能减少节点能量消耗和延长网络生存周期.因此在LEACH算法和PEGASIS算法的基础上,提出了一种基于混合量子进化算法的高效节能的无线传感器网络路由算法HERA.该算法中把网络分为多个簇,每个簇中的节点连接成为一条多跳通讯链路,并使用混合量子进化算法来得到最优的分簇组链方式,以减少链路...     

一种能量高效的无线传感器网络分簇路由算法

无线传感器网络中节点的能量有限,提高能量的有效性便成为无线传感器网络路由协议设计的首要目标。设计了一种能量高效的分簇路由算法,它提出让候选节点在一定的覆盖范围内以剩余能量为标准来竞选簇头,以使簇头分布均匀;处于簇类交界的节点则根据能量和距离来选择归属的簇头,以平衡网络负载;新算法还采用多跳的簇间通信方式来降低大部分簇头节点的通信负载。仿真结果表明:新算法能够有效降低网络能耗,延长网络生存时间。     

PEACH: Power-efficient and adaptive clustering hierarchy protocol for wireless sensor networks

The main goal of this research is concerning clustering protocols to minimize the energy consumption of each node, and maximize the network lifetime of wireless sensor networks. However, most existing clustering protocols consume large amounts of energy, incurred by cluster formation overhead and fixed-level clustering, particularly when sensor nodes are densely deployed in wireless sensor networks. In this paper, we propose PEACH protocol, which is a power-efficient and adaptive clustering hierarchy protocol for wireless sensor networks. By using overhearing characteristics of wireless communication, PEACH forms clusters without additional overhead and supports adaptive multi-level clustering. In addition, PEACH can be used for both location-unaware and location-aware wireless sensor networks. The simulation results demonstrate that PEACH significantly minimizes energy consumption of each node and extends the network lifetime, compared with existing clustering protocols. The performance of PEACH is less affected by the distribution of sensor nodes than other clustering protocols.     

Adaptive decentralized re-clustering protocol for wireless sensor networks

Wireless sensor networks are composed of a large number of sensor nodes with limited energy resources. One critical issue in wireless sensor networks is how to gather sensed information in an energy efficient way since the energy is limited. The clustering algorithm is a technique used to reduce energy consumption. It can improve the scalability and lifetime of wireless sensor network. In this paper, we introduce an adaptive clustering protocol for wireless sensor networks, which is called Adaptive Decentralized Re-Clustering Protocol (ADRP) for Wireless Sensor Networks. In ADRP, the cluster heads and next heads are elected based on residual energy of each node and the average energy of each cluster. The simulation results show that ADRP achieves longer lifetime and more data messages transmissions than current important clustering protocol in wireless sensor networks.     

一种异构传感器网络下的节能分簇路由算法

无线传感器网络存在着严重的能量约束,传统同构的传感网络路由协议和算法不适合异构网络,因此,设计异构传感网络下的节能路由算法具有现实意义。研究两种不同类型传感器节点构成的,具有不同的初始能量和不同感知数据能力的异构网络中基于簇头预测的节能分簇路由算法ECAH。根据簇内节点的剩余能量、能量消耗速率和跟上一轮簇头的距离预测出下一轮簇头,有效地减少了控制报文数量,降低了系统开销,节约了能量。仿真结果显示,在异构的网络中采用ECAH路由算法比LEACH算法网络生存时间大约提高了23%。     

一种基于时间延迟机制的无线传感器网络分簇算法

为了延长网络的生存时间,需要设计能量有效的路由协议以适应传感器网络的特点.成簇算法是传感器网络中减少能量消耗的一种关键技术,它能够提高网络的生存时间.本文提出一种基于时间延迟机制的分簇算法,称为CHTD.该算法建立了节点的时间延迟机制模型,使得能量较多的节点能够在每一轮中被优先选为簇首.同时,通过维持每个节点的簇首信息集合使得每轮产生的簇首数目稳定且位置均匀分布.模拟实验表明,CHTD有效地均衡了网络中节点的能量消耗,并显著地延长了网络的存活时间.