仿血管路径的无线传感器网络故障容错路由算法

为提高无线传感器网络故障容错性和传输稳定性,实现网络负载均衡,提出了一种仿血管路径的无线传感器网络故障容错路由算法.研究了人体血管路径特性及属性关联,对网络节点分区域等级标定并以不同概率值进行静态分簇,运用改进的蚁群算法BWAS(最优最差蚂蚁系统)生成节点路径,以路径信息素值作为传输路径的选择概率建立仿血管拓扑结构路由...     

无线传感器网络动态分簇路由BWAS的算法研究

为加快无线传感器网络(WSN)路径搜索速度,减少了路径寻优能量消耗,提出了基于最优-最差蚂蚁系统(BWAS)算法的无线传感器网络动态分簇路由算法。该算法是基于WSN动态分簇能量管理模式,在簇头节点间运用BWAS算法搜寻从簇头节点到汇聚节点的多跳最优路径,以多跳接力方式将数据发送至汇聚节点。BWAS算法在路径搜寻过程中评价出最优-最差蚂蚁,引入奖惩机制,加强搜寻过程的指导性。结合动态分簇能量管理,避免网络连续过度使用某个节点,均衡了网络节点能量消耗。通过与基于蚁群算法(ACS)路由算法仿真比较,本算法减缓了网络节点的能量消耗,延长了网络寿命,在相同时间里具有较少的死亡节点,具有较强的鲁棒性。     

面向智慧园区的WSN路由优化算法

为解决智慧园区中无线传感器网络(WSN)的能耗不均衡问题,构建了路由代价函数,并提出了一种新的能耗均衡路由算法.该算法结合智慧园区中无线传感器网络的特点,综合考虑节点地理位置和剩余能量来构建路由代价函数.传感器节点通过选择其邻居节点中路由代价最小的节点进行数据转发.仿真结果表明,该算法可以有效节约网络能耗,同时延长了网络的生命周期.     

基于天牛须搜索的无线传感网分簇路由协议

针对无线传感器网络中的能耗不均衡问题,提出一种基于天牛须搜索算法的负载均衡分簇路由协议算法(LEACH-BAS)。该算法引入候选簇首选举机制,使用天牛须搜索算法对簇首分布进行搜索优化,形成合理分簇。此外,在簇间路由通信时,考虑剩余能量因子和传输能耗因子来选择中继节点。仿真结果表明,LEACH-BAS算法的网络生命周期相比LEACH、EAMMH、LEACH-GA和LEACH-PSO算法分别延长了39%、22%、15%和8%。LEACH-BAS算法应用在WSN监测场景,能有效解决WSN中能量不足的问题,优化簇首节点分布,降低节点能耗,有效地延长网络生命周期。     

带宽有效聚类结合RVBT的传感器网络容错路由算法

针对现存骨干结构算法在转换重要节点时不能形成完整骨干结构的问题,提出一种带宽有效聚类结合随机虚拟骨干树(BC-RVBT)的WSN故障容错路由算法。带宽聚类提供更好的骨干树构建条件,在构建骨干的过程中选取树节点和非树节点,每个节点至少与一个树节点密切相关,根据树节点的适合度值将非树节点随机地重新分布到所有合格的树节点中,提高虚拟骨干树的性能。在NS2仿真器上的实验结果显示,相比其他几种容错算法,该文算法在传输数据时总能耗最低;平均路由路径长度和家属节点方差均为最低,分别为3.14和37.36。存在故障节点时,恢复延迟也表现优秀,有效提高了WSN的使用寿命。     

有向双环网络G(N;h)的容错路由算法

针对有向双环网络G(N;h)的容错问题,研究了有向双环网络G(N;h)容错节点所对应的等价节点的分布规律,给出一种有向双环网络G(N;h)的容错路由算法. 给出了当有向双环网络任意两个节点之间的最短路径出现故障时,找出另一条最短路径的方法. 此算法的时间复杂度为O(d).     

基于NoC的容错路由算法

各种各样的软件和硬件上的错误都会破坏网络的数据传输,因此研究No C网络的容错算法是非常必要的。在基于XY路由算法的基础上提出了改进的容错路由算法,当链路或者传输节点之间发生错误时,可通过重新设置路由规则来获取一条有效的路由路径。在FPGA上进行路由容错算法的仿真,并和目前常用的几种路由算法在所适用拓扑、是否防止死锁等方面进行对比。仿真结果显示改进的路由容错算法性能优越,是可行的。     

WSN中能量有效分簇多跳路由算法

针对现有无线传感器网络(WSN)分簇路由算法存在的能耗不均衡问题,提出一种能量有效分簇多跳路由算法,该算法包括两个方面:一是选举簇首时引入簇内平均剩余能量因子,根据上一轮结束后簇内各节点剩余能量和簇内节点的平均剩余能量的比值更新簇首在所有节点中所占的百分比;二是要求簇首根据MTE多跳路由协议与基站通信,从而均衡WSN整...     

一种基于目标区域分层的WSN路由协议

目前WSN路由协议大多是对分簇方法或传输路径的优化,从而达到优化网络能耗的目的。文中提出一种基于非均匀分层的路由协议(ULEE),通过对监测区域进行分层赋予节点以不同的竞争半径,并根据节点剩余能量选取簇头,同时采用多跳的簇间传输。仿真结果表明,该算法可以通过计算推导获得最优参数。相对于几种经典路由协议,该协议具有节点能耗均匀、网络寿命延长的特点。     

WSN中引入移动节点的路由协议设计与仿真

对于节点部署不均或者节点死亡而导致的监测盲区,可通过在WSN中引入移动节点来修复。提出一种修复策略,可较为及时、准确地修复监测盲区,同时考虑节点的能量均衡问题。在LEACH-M分簇路由算法的基础上,给出了一种按节点能量分配工作量的能量均衡分簇路由算法LEACH-M-G,并运用MATLAB仿真工具进行了仿真分析。仿真结果表明,所提出的监测盲区修复策略、以及LEACH-M-G路由能有效地修复监测盲区,均衡网络能量、延长网络生命周期。     

Multi-objective-derived energy efficient routing in wireless sensor networks using hybrid African vultures-cuckoo search optimization

Wireless Sensor Network (WSN) plays an essential role in consumer electronics, remote monitoring, an electromagnetic signal, and so forth. The functional capacity of WSN gets enhanced everyday with different technologies. The rapid development of wireless communication, as well as digital electronics, provides automatic sensor networks with low cost and power in various functions, but the challenge faced in WSN is to forward a huge amount of data between the nodes, which is a highly complex task to provide superior delay and energy loss. To overcome these issues, the development of a routing protocol is used for the optimal selection of multipath to perform efficient routing in WSN. This paper developed an energy-efficient routing in WSNs utilizing the hybrid meta-heuristic algorithm with the help of Hybrid African Vultures-Cuckoo Search Optimization (HAV-CSO). Here, the designed method is utilized for choosing the optimal cluster heads for progressing the routing. The developed HAV-CSO method is used to enhance the network lifetime in WSN. Hence, the hybrid algorithm also helps select the cluster heads by solving the multi-objective function in terms of distance, intra-cluster distance, delay, inter-cluster distance, throughput, path loss, energy, transmission load, temperature, and fault tolerance. The developed model achieved 7.8% higher than C-SSA, 25.45% better than BSO-MTLBO, 23.21% enhanced than AVOA, and 1.29% improved than CSO. The performance of the suggested model is validated, and the efficacy of the developed work is proved over other existing works.     

基于遗传聚类的无线传感器负载均衡路由算法

通常的无线传感器分簇网络存在节点负载不均衡的问题。为均衡各节点能量消耗,延长网络生存周期,将K均值算法与遗传算法相结合,提出一种负载均衡的无线传感器网络路由算法,算法利用遗传算法的全局寻优能力以克服传统K均值算法的局部性和对初始中心的敏感性,实现了传感器网络节点自适应成簇与各节点负载均衡。仿真实验表明,该算法显著延长了网络寿命,相对于其他分簇路由算法,其网络生存时间延长了约43%。     

Statistical Multipath Queue-Wise Preemption Routing for ZigBee-Based WSN

Nowadays, wireless sensor network (WSN) is an important component in IoT environment, which enables efficient data collection and transmission. Since WSN consists of a large number of sensor nodes, network congestion can easily occur which significantly degrades the performance of entire network. In this paper a novel scheme called SMQP (Statistical Multipath Queue-wise Preemption) routing is proposed to balance the load and avoid the congestion for ZigBee-based WSN. This is achieved by employing statistical path scheduling and queue-wise preemption with multiple paths between any source and destination node. NS2 simulation reveals that the proposed scheme significantly improves the QoS in terms of delivery ratio, end-to-end delay, and packet delivery ratio compared to the representative routing schemes for WSN such as ad hoc on-demand distance vector and ad hoc on-demand multipath distance vector scheme.     

基于遗传聚类的无线传感器负载均衡路由算法

通常的无线传感器分簇网络存在节点负载不均衡的问题。为均衡各节点能量消耗,延长网络生存周期,将K均值算法与遗传算法相结合,提出一种负载均衡的无线传感器网络路由算法,算法利用遗传算法的全局寻优能力以克服传统K均值算法的局部性和对初始中心的敏感性,实现了传感器网络节点自适应成簇与各节点负载均衡。仿真实验表明,该算法显著延长了网络寿命,相对于其他分簇路由算法,其网络生存时间延长了约43%。     

Secured routing in wireless sensor networks using fault‐free and trusted nodes

Wireless sensor network (WSN) should be designed such that it is able to identify the faulty nodes, rectify the faults, identify compromised nodes from various security threats, and transmit the sensed data securely to the sink node under faulty conditions. In this paper, we propose an idea of integrating fault tolerance and secured routing mechanism in WSN named as fault tolerant secured routing: an integrated approach (FASRI) that establishes secured routes from source to sink node even under faulty node conditions. Faulty nodes are identified using battery power and interference models. Trustworthy nodes (non‐compromised) among fault‐free nodes are identified by using agent‐based trust model. Finally, the data are securely routed through fault‐free non‐compromised nodes to sink. Performance evaluation through simulation is carried out for packet delivery ratio, hit rate, computation overhead, communication overhead, compromised node detection ratio, end‐to‐end delay, memory overhead, and agent overhead. We compared simulation results of FASRI with three schemes, namely multi‐version multi‐path (MVMP), intrusion/fault tolerant routing protocol (IFRP) in WSN, and active node‐based fault tolerance using battery power and interference model (AFTBI) for various measures and found that there is a performance improvement in FASRI compared with MVMP, IFRP, and AFTBI. Copyright © 2014 John Wiley & Sons, Ltd.     

A grid based clustering and routing algorithm for solving hot spot problem in wireless sensor networks

Energy conservation of the sensor nodes is the most important issue that has been studied extensively in the design of wireless sensor networks (WSNs). In many applications, the nodes closer to the sink are overburdened with huge traffic load as the data from the entire region are forwarded through them to reach the sink. As a result, their energy gets exhausted quickly and the network is partitioned. This is commonly known as hot spot problem. Moreover, sensor nodes are prone to failure due to several factors such as environmental hazards, battery exhaustion, hardware damage and so on. However, failure of cluster heads (CHs) in a two tire WSN is more perilous. Therefore, apart from energy efficiency, any clustering or routing algorithm has to cope with fault tolerance of CHs. In this paper, we address the hot spot problem and propose grid based clustering and routing algorithms, combinedly called GFTCRA (grid based fault tolerant clustering and routing algorithms) which takes care the failure of the CHs. The algorithms follow distributed approach. We also present a distributed run time management for all member sensor nodes of any cluster in case of failure of their CHs. The routing algorithm is also shown to tolerate the sudden failure of the CHs. The algorithms are tested through simulation with various scenarios of WSN and the simulation results show that the proposed method performs better than two other grid based algorithms in terms of network lifetime, energy consumption and number of dead sensor nodes.     

Q-MOHRA: QoS Assured Multi-objective Hybrid Routing Algorithm for Heterogeneous WSN

Quality of Service (QoS) assurance in Wireless Sensor Network (WSN) is a tough task, and it is more exciting due to the scarcity of resources. The requirement of different WSN applications running over has different constraints. In QoS, routing protocol the network has to balance the traffic. This paper presents a novel heuristic routing algorithm known as QoS assured Multi-objective Hybrid Routing Algorithm (Q-MOHRA) for Heterogeneous WSN. Q-MOHRA takes into account the link (energy, hop count, link quality indicator etc.) and path (jitter) metrics for optimal path selection. The performance of Q-MOHRA is evaluated through intensive simulation and equated with Simple Hybrid Routing Protocol (SHRP) and Dynamic Multi-objective Routing Algorithm (DyMORA). The metrics such as average energy consumption, residual energy, packet delivery ratio, jitter, and normalized routing load are used for comparison. The performance of Q-MOHRA has been observed to outclass SHRP and DyMORA. It improves the packet delivery ratio by 24.31% as compared to SHRP and 11.86% as compared to DyMORA. Q-MOHRA outperforms DyMORA in terms of average energy consumption by a factor of 8.27%.     

一种基于K-means的WSN移动汇聚路由算法

无线传感网络(Wireless Sensor Network,WSN)作为一种资源受限的网络,网络中节点的能耗直接影响了网络的性能。因此,均衡网络中的能耗,延长网络的生命周期,成为设计WSN路由算法的重要目标。于是,在LEACH-C协议的基础上提出了一种移动汇聚路由算法。分簇阶段由Sink节点计算最优簇首个数,通过K-means聚类将网络中的节点划分至不同的集群,选择通信成本最低的节点作为各集群的簇首。稳定传输阶段通过移动Sink进行数据采集,针对不同的延迟分别规划Sink节点的移动轨迹。MATLAB仿真结果表明,与LEACH和LEAHC-C算法相比簇首的分布更合理,结合Sink节点的移动策略能有效均衡网络能耗,延长网络的寿命。     

Energy-Efficient Routing Algorithm Based on Unequal Clustering and Connected Graph in Wireless Sensor Networks

Clustering and multi-hop routing algorithms substantially prolong the lifetime of wireless sensor networks (WSNs). However, they also result in the energy hole and network partition problems. In order to balance the load between multiple cluster heads, save the energy consumption of the inter-cluster routing, in this paper, we propose an energy-efficient routing algorithm based on Unequal Clustering Theory and Connected Graph Theory for WSN. The new algorithm optimizes and innovates in two aspects: cluster head election and clusters routing. In cluster head election, we take into consideration the vote-based measure and the transmission power of sensor nodes when to sectionalize these nodes into different unequal clusters. Then we introduce the connected graph theory for inter-cluster data communication in clusters routing. Eventually, a connected graph is constituted by the based station and all cluster heads. Simulation results show that, this new algorithm balances the energy consumption among sensor nodes, relieves the influence of energy-hole problem, improve the link quality, achieves a substantial improvement on reliability and efficiency of data transmission, and significantly prolongs the network lifetime.     

An adaptive‐aware energy and queue improvement of AOMDV

Because the node energy and network resources in the wireless sensor network (WSN) are very finite, it is necessary to distribute data traffic reasonably and achieve network load balancing. Ad hoc on‐demand multipath distance vector (AOMDV) is a widely used routing protocol in WSN, but it has some deficiencies: establishes the route by only using hop counts as the routing criterion without considering other factors such as energy consumption and network load; forwards route request in fixed delay resulting in building the nonoptimal path; and cannot update the path status after built paths. For the deficiency of AOMDV, this paper proposes a multipath routing protocol adaptive energy and queue AOMDV (AEQAOMDV) based on adaptively sensing node residual energy and buffer queue length. When sending a routing request, the forwarding delay of the routing request is adaptively adjusted by both the residual energy and the queue length of the intermediate node; when establishing routes, a fitness is defined as a routing criterion according to the link energy and the queue load, predicting the available duration of the node based on the energy consumption rate and adjusting the weight of the routing criterion by the available duration of the node; after the routes are established, the path information status are updated via periodically broadcasting Hello that carries the path information with the minimum fitness, making the source node update the path information periodically. By using NS‐2, simulations demonstrate that compared with AOMDV, AEQAOMDV has obvious improvements in increasing packet delivery ratio, reducing network routing overhead, reducing route discovery frequency, and decreasing the network delay. And AEQAOMDV is more suitable for WSN.