共查询到20条相似文献，搜索用时 156 毫秒
1.
为了延长传感器网络生存时间,多跳路由协议一直是无线传感器领域的研究热点。其中多跳分簇的路由协议（MHLEACH） 不仅能扩展通信范围,还可以均衡分配节点能耗,从而有效提高了能量利用率。但该方法存在的问题是若选中的簇首距离基站太远,则会耗费较多能量。同时,簇群链路分布的不均匀也可能使一些靠近基站的簇首更频繁地转发数据。为解决该问题,提出一种改进算法RSSI-Mean-Filter-MHLEACH（简称RMF-MHLEACH）,该算法能对接收路由消息时获得的邻居节点信号强度与邻居表内节点剩余能量信息进行比较分析,最后找出最优的上层转发节点,从而使各节点在保证通信质量的同时,也能合理分担簇首的能量消耗。 相似文献
2.
无线传感器网络拓扑控制算法对于延长网络的生存时间、减小通信干扰、提高路由协议和MAC协议的效率等具有重要的意义。根据无线传感器网络的分簇机制,有效地利用成簇算法均衡网络节点负载,降低能耗,从簇首的选择、簇组织和簇的路由三个方面系统地分析当前典型的成簇算法,对算法的特点和适用情况进行比较分析,并指出目前算法存在问题和改进措施。 相似文献
3.
邓芳 《湖北第二师范学院学报》2010,(2):62-65
无线传感器网络拓扑控制算法对于延长网络的生存时间、减小通信干扰、提高路由协议和MAC协议的效率等具有重要的意义。根据无线传感器网络的分簇机制,有效地利用成簇算法均衡网络节点负载,降低能耗,从簇首的选择、簇组织和簇的路由三个方面系统地分析当前典型的成簇算法,对算法的特点和适用情况进行比较分析,并指出目前算法存在问题和改进措施。 相似文献
4.
针对无线传感器网络路由协议LEACH(Low Energy Adaptive Clustering Hierarchy)存在能耗不均衡的问题,提出一种改进的路由协议LEACH EM(LEACH Energy and Multi hop routing)。该算法修改了选取簇首的阈值,使节点能根据自身剩余能量动态调整其轮转周期,同时在簇间引入多跳路由机制,使距离基站较远的簇首能耗得到均衡,由此平衡整个网络负载。仿真实验表明,LEACH EM算法在能耗均衡上得到了改善,在网络生命周期中,LEACH EM算法比LEACH延长了38.8%。 相似文献
5.
根据无线传感网络能量受限的特点,提出一种低能耗路由算法SOC-IACO,算法由自组织聚类算法SOC和改进蚁群算法WAC组成.先通过SOC将节点分簇,选取簇头构造簇头数据链,再通过WAC构造簇内节点数据链.簇内数据沿节点数据链汇聚至簇头、簇头数据沿簇头数据链汇聚至总簇头,由总簇头发送数据至基站.实验表明,由于聚类过程中考虑了节点分布和簇负载均衡并采用双层链路由,SOC-IACO算法能大幅降低节点能耗提高网络寿命. 相似文献
6.
本文研究了一种基于节点位置信息的改进型LEACH无线传感器网络分簇算法,通过决策支持机制,利用传感器节点的位置信息进行分簇.该算法有效地减少了路由消耗,同时平衡节点间的能量使用,控制节点能耗,延长网络生存时间. 相似文献
7.
基于形式化建模的思想,分别建立簇首节点和簇中成员节点的有限状态机模型,描述LEACH协议的路由行为及算法思想,分析影响LEACH协议性能的可能性因素,利用NS2对LEACH协议进行仿真,仿真结果表明,改进后的LEACH协议在节省了整个网络的能量消耗并很好的均衡了网络内节点的能耗,延长了节点的生存时间,改善了网络的性能. 相似文献
8.
基于对LEACH算法和PEGASIS算法的研究,提出助理簇头改进ASCH算法.该算法能够在无线传感器网络中,根据簇头节点所处的地理位置、剩余能量及簇内成员节点数目,动态决定是否需要在簇内产生助理簇头,并在需要产生助理簇头的簇内选择合适的节点来减少簇头通信的能耗.在PEGASIS中加入助理簇头后,改进后的助理簇头改进算法的性能指标与已有算法相比均有提高,在均衡及节能、延长网络生命周期方面起到了积极的作用. 相似文献
9.
ZigBee网络的传统算法(簇树路由算法和AODVjr路由算法)在发现路由过程中节点能耗较大。为此,结合节点能量、簇树路由算法和AODVjr路由算法,提出一种改进的ZigBee网络路由算法。该路由算法选择路由时尽量避免能量较低的节点,选择最佳路径,维持网络稳定性。仿真结果表明,改进后的算法能有效降低整个网络总体能耗,合理分配网络负载,大大降低了死亡节点数量,从而延长整个网络的使用寿命。 相似文献
10.
针对LEACH（Low Energy Adaptive Clustering Hierarchy）算法中的随机分簇和簇头能耗不均问题,提出一种基于最低能耗的改进LEACH分簇算法MEC-LEACH（Minimum Energy Consumption based LEACH）。MEC-LEACH分簇算法通过最小化网络能耗得出最优簇头数,同时引入簇头的剩余能量和簇头距离sink节点的远近等因素综合选举簇头节点,使得剩余能量较大且距离sink较近的节点优先成为簇头节点,进而均衡簇头节点和网络总的能耗。仿真实验表明,MEC-LEACH算法相比其它改进算法可以有效降低网络能耗,延长网络生存时间。 相似文献
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12.
本文提出了适用于物联网视频多跳中继无线通信的实现能量预估的网络层叠协同路由交互寻访技术。该技术的前提是采用遗传算法设计轮询步进优化估值模型,依据估值模型计算节点感知距离和节点能量,结合无线大容量信号编码解调码过程建立层叠协同交互寻访体系,优化簇内、簇头节点的传输效能,实现用户层、网络通信层和感知层层叠路由的交互协同。经软件仿真和数学矩阵对比,该技术可较好地满足物联网视频等大容量感知数据的传输与处理,而且可以充分利用物联网层叠资源特别是感知层与链路层受限的运算、存储和能量等资源。 相似文献
13.
周伟 《上海大学学报(英文版)》2011,15(2):150-153
In this paper, an energy efficient clustering algorithm based on neighbors (EECABN) for wireless sensor networks is proposed.
In the algorithm, an optimized weight of nodes is introduced to determine the priority of clustering procedure. As improvement,
the weight is a measurement of energy and degree as usual, and even associates with distance from neighbors, distance to the
sink node, and other factors. To prevent the low energy nodes being exhausted with energy, the strong nodes should have more
opportunities to act as cluster heads during the clustering procedure. The simulation results show that the algorithm can
effectively prolong whole the network lifetime. Especially at the early stage that some nodes in the network begin to die,
the process can be postponed by using the algorithm. 相似文献
14.
A load-balanced minimum energy routing algorithm for Wireless Ad Hoc Sensor Networks 总被引：3，自引：0，他引：3
CAI Wen-yu JIN Xin-yu ZHANG Yu CHEN Kang-sheng 《浙江大学学报(A卷英文版)》2006,7(4):502-506
INTRODUCTION Wireless Sensor Network is one special type of wireless ad hoc networks without fixed infrastructure consisting of a collection of sensor nodes, and oper- ating on limited amount of battery energy consumed mostly in transmission and reception. In the WSNs described in Fig.1, every sensor node can sense, process data and communicate to base station (BS). WSNs have attracted much attention during the recent two years and some commercial implementations such as environmental … 相似文献
15.
Cross-layer design of energy-saving AODV routing protocol 总被引：1，自引：0，他引：1
Since most ad hoc mobile devices today operate on batteries, the power consumption becomes an important issue. This paper proposes a cross-layer
design of energy-aware ad hoc on-demand distance vector (CEAODV) routing protocol which adopts cross-layer mechanism and energy-aware metric to improve
AODV routing protocol to reduce the energy consumption and then prolong the life of the whole network. In CEAODV, the link
layer and the routing layer work together to choose the optimized transmission power for nodes and the route for packets.
The link layer provides the energy consumption information for the routing layer and the routing layer chooses route accordingly
and conversely controls the link layer to adjust the transmission power. The simulation result shows that CEAODV can outperform
AODV to save more energy. It can reduce the consumed energy by about 8% over traditional energy-aware algorithm. And the performance
is better when the traffic load is higher in the network. 相似文献
16.
Wireless sensor networks consist of hundreds or thousands of sensor nodes that involve numerous restrictions including computation capability and battery capacity. Topology control is an important issue for achieving a balanced placement of sensor nodes. The clustering scheme is a widely known and efficient means of topology control for transmitting information to the base station in two hops. The automatic routing scheme of the self-organizing technique is another critical element of wireless sensor networks. In this paper we propose an optimal algorithm with cluster balance taken into consideration, and compare it with three well known and widely used approaches, i.e., LEACH, MEER, and VAP-E, in performance evaluation. Experimental results show that the proposed approach increases the overall network lifetime, indicating that the amount of energy required for communication to the base station will be reduced for locating an optimal cluster. 相似文献
17.
数据汇聚是降低传感器网络传输能耗的重要手段.分簇传感网数据汇聚通常包括簇内汇聚及传递汇聚结果到基站两个阶段,现有方案大多关注第二阶段数据汇聚结果传递到基站的效率.现提出一种基于位置信息的分簇传感网数据汇聚方案,通过利用位置信息选择代理点,仅与代理点有不同测量值的节点进行数据发送,有效减少了第一阶段中的数据传输.理论分析与模拟试验表明,方案簇内消息发送数优于相关方案,减少了通信开销,延长了网络生命期. 相似文献
18.
采用一种神经网络算法——径向基函数来选择无线传感器网络的节点簇首,它具有并行处理能力、分布式存储以及快速学习等优点.通过分析得出与节点作为簇首相关的4个因素:节点的剩余能量,周围分布的节点的数目,中心度和距离基站的位置.把这4个因素作为神经网络的输入变量,输出变量就是该节点作为簇首的适应度值.根据网络规模的大小,基站选出一组作为簇首的节点,然后广播作为簇首的节点号的消息.如果一个节点被选为簇首,就向周围广播自己的身份并成立一个新簇,周围的非簇首节点要求加入该簇并成为它的成员.每簇中由簇首负责管理它的成员并执行数据融合等功能.实验结果表明,与其他算法相比,该算法能显著地延长传感器网络的生命. 相似文献
19.
There were two strategies for the data forwarding in the content-centric networking(CCN): forwarding strategy and routing strategy. Forwarding strategy only considered a separated node rather than the whole network performance, and Interest flooding led to the network overhead and redundancy as well. As for routing strategy in CCN, each node was required to run the protocol. It was a waste of routing cost and unfit for large-scale deployment.This paper presents the super node routing strategy in CCN. Some super nodes selected from the peer nodes in CCN were used to receive the routing information from their slave nodes and compute the face-to-path to establish forwarding information base(FIB). Then FIB was sent to slave nodes to control and manage the slave nodes. The theoretical analysis showed that the super node routing strategy possessed robustness and scalability, achieved load balancing,reduced the redundancy and improved the network performance. In three topologies, three experiments were carried out to test the super node routing strategy. Network performance results showed that the proposed strategy had a shorter delay, lower CPU utilization and less redundancy compared with CCN. 相似文献
20.
To find the optimal routing is always an important topic in wireless sensor networks （WSNs）. Considering a WSN where the nodes have limited energy, we propose a novel Energy^＊Delay model based on ant algorithms （＂E＆D ANTS＂ for short） to minimize the time delay in transferring a fixed number of data packets in an energy-constrained manner in one round. Our goal is not only to maximize the lifetime of the network but also to provide real-time data transmission services. However, because of the tradeoff of energy and delay in wireless network systems, the reinforcement learning （RL） algorithm is introduced to train the model. In this survey, the paradigm of E＆D ANTS is explicated and compared to other ant-based routing algorithms like AntNet and AntChain about the issues of routing information, routing overhead and adaptation. Simulation results show that our method performs about seven times better than AntNet and also outperforms AntChain by more than 150% in terms of energy cost and delay per round. 相似文献