Post-order based routing & transport protocol for wireless sensor networks

In this paper, we propose a lightweight, application independent transport protocol for communication of the nodes belonging to a wireless sensor network (WSN) with the nodes belonging to a local area network. The framework consists of a novel downstream routing scheme and a well-known tree based upstream routing protocol for WSNs. The downstream routing protocol leverages Post-order Numbering (PN) of sensor nodes in the collection tree network formed and maintained by the upstream routing protocol. Through the proposed transport framework, using a technique similar to NATing, we achieve a seamless integration of WSNs and IP networks. The proposed protocol was not only evaluated by extensive simulations, but also implemented on a real test bed to show its practical deployability. We built our test bed around a small Wireless Distribution System (WDS) consisting of two laptop computers and eight Micaz motes attached with MTS300 sensor boards. We connected one of the computers in WDS via Ethernet to the LAN while the other operated as a server with a serial forwarder. A gateway board was attached to the second computer via a USB port which enabled it to function also as a base station for the WSN. A distinct advantage of the proposed framework is that an IP client can directly communicate with a sensor node through its base station.     

基于改进CPSO算法的无线传感器网络路由协议

为了降低节点能量消耗,延长网络生存周期,提出一种基于混沌粒子群算法（Chaotic Particle Swarm Optimization,CPSO）的无线传感器网路由协议。该协议改进了LEACH（Low Energy Adaptive Clustering Hierarchy）协议的簇头选择机制,考虑节点剩余能量、簇头到基站（Based Station）的距离等因素,通过混沌粒子群算法对簇头选举进行优化。簇头选举后,通过多跳算法对簇头到基站的通信方式进行优化。仿真结果表明,与传统的LEACH协议比较,新协议能减少能量消耗,延长网络寿命。     

Energy-aware node placement,topology control and MAC scheduling for wireless sensor networks

In the WSNs, the nodes closer to the sink node have heavier traffic load for packet forwarding because they do not only collect data within their sensing range but also relay data for nodes further away. The unbalanced power consumption among sensor nodes may cause network partition. This paper proposes efficient node placement, topology control, and MAC scheduling protocols to prolong the sensor network lifetime, balance the power consumption of sensor nodes, and avoid collision. Firstly, a virtual tree topology is constructed based on Grid-based WSNs. Then two node-placement techniques, namely Distance-based and Density-based deployment schemes, are proposed to balance the power consumption of sensor nodes. Finally, a collision-free MAC scheduling protocol is proposed to prevent the packet transmissions from collision. In addition, extension of the proposed protocols are made from a Grid-based WSN to a randomly deployed WSN, enabling the developed energy-balanced schemes to be generally applied to randomly deployed WSNs. Simulation results reveal that the developed protocols can efficiently balance each sensor node’s power consumption and prolong the network lifetime in both Grid-based and randomly deployed WSNs.     

基站选择Sink的无线传感器网络路由协议

节点的能量标志着无线传感器网络(WSN)的生命周期,但是当前一些路由协议不能够很好地平衡、延长网络的生命周期.基于此,提出了一种基站选择Sink的无线传感器网络的路由协议.该协议利用环和边构成扇形区域,基站选择几个能量较大的节点作为扇环内的Sink,这些Sink采用TDMA的原理轮流成为当前的Sink,从而平衡整个网络的能量开销.仿真结果表明,该基站选择Sink的路由协议要比CWR协议更能节约能量、延长网络的生命周期.     

无线传感器网络分簇路由节能研究

在大规模传感和环境监测中,节约能源延长传感器节点生命已成为无线传感器网络最重要的研究课题之一。提供合理的能源消耗和改善无线网络生命周期的传感器网络系统,必须设计一种新的有效的节能方案和节能路由体系。方案采用一种聚类算法减少无线传感器网络的能量消耗,创建一种cluster-tree分簇路由结构的传感器网络。该方案主要目标是做一个理想的分簇分配,减少传感器节点之间的数据传输距离,降低传感器节点能源消耗,延长寿命。实验结果表明,该方案有效地降低了能源消耗从而延长无线传感器网络生命。     

基于蚁群优化的无线传感器网络路由算法

如何在资源受限的无线传感器网络中进行高效的数据路由是无线传感器网络研究的热点之一。基于群智能优化技术的蚁群优化算法被广泛应用于网络路由算法。提出一种无线传感器网络蚁群优化路由算法,能够保持网络的生存时间最长,同时能找到从源节点到基站节点的最短路径;采用的多路数据传输也可提供高效可靠的数据传输,同时考虑节点的能量水平。仿真结果表明:提出的算法延长了无线传感器网络的寿命,实现无线传感器网络在通信过程中快速、节能的路由。     

线型无线传感器网络的节点部署策略

尽可能延长无线传感器网络的生命周期是设计和部署网络所面临的最大挑战之一。由于节点配备的能量有限,节点通常采用多跳方式向基站传输数据。分析了节点在多跳通信时的能耗,提出一种非均匀的节点部署策略,得出一个部署传感器节点的密度函数,在靠近基站的区域部署较多的节点。仿真实验表明,非均匀的节点部署策略能有效延长网络的生命周期。     

基于梯度的无线传感器网络能耗分析及能量空洞避免机制

在基于"梯度汇聚"模型的无线传感器网络 (Wireless sensor networks, WSNs)中, 因节点间能量消耗不平衡而引发的能量空洞一直是影响网络生存周期的重要原因. 本文分别分析了无通信干扰的自由空间环境和瑞利衰落环境下网络中节点的能量消耗,提出了一种基于节点能量非均匀分布的能量空洞避免机制,即根据节点的能耗水平为每个节点储备不同的初始能量.并结合通信干扰、休眠机制等因素,研究了基于"梯度汇聚"模型的无线传感器网络生存周期的上界和下界. 模拟结果表明,该机制提高了能量的利用效率,延长了网络的生存周期.     

一种基于簇的无线传感器网络能量有效路由协议

由于传感器节点的电源能量、通信能力和计算能力都十分有限。为了提高无线传感器网络(W SNs)的生命周期,提出了一种基于簇的高效节能的传感器网络路由协议。该协议提出了基于最小成本路径的数据转发法并运用于簇内路由中。同时,为了减小簇头节点的能量开销,簇头之间采用了多跳中继的方式将采集的数据发送到基站。仿真证明:该协议与LEACH协议相比,其网络寿命提高了500%,此外,该协议还提高了传感器节点的能耗均衡性、网络扩展性和可靠性。     

基于能量优化的无线传感器网络分簇路由算法研究

无线传感器网络的路由协议设计要同时关注单个节点的能耗及整个网络能量的均衡消耗.分簇算法能有效解决节点能耗受限与不同节点能量开销不平衡问题.在分析了传统分簇路由LEACH(low energy adaptive clustering hierarchy)协议中选择簇头算法不足和当前一些典型基于LEACH思想的路由改进算法...     

路由深度对Sink轨迹固定传感器网络的影响

无线传感器网络中,使用移动Sink进行数据采集能够减少网络节点死亡速度,延长网络时间,是最有效均衡网络负载的方法之一。在实际应用中,移动Sink通常采用固定路径策略,同时路由深度的改变直接影响网络拓扑和路由选择结果。比较了在不同路由深度下,采用4种典型固定策略的移动Sink网络的网络能耗、网络寿命和包延时。仿真结果表明:在较小的路由深度下,外边界策略能更好地降低节点能耗,延长网络寿命;内边界策略能取得更好的覆盖和较低的时延。     

Energy-Efficient Routing Using Novel Optimization with Tabu Techniques for Wireless Sensor Network

Wireless Sensor Network (WSN) consists of a group of limited energy source sensors that are installed in a particular region to collect data from the environment. Designing the energy-efficient data collection methods in large-scale wireless sensor networks is considered to be a difficult area in the research. Sensor node clustering is a popular approach for WSN. Moreover, the sensor nodes are grouped to form clusters in a cluster-based WSN environment. The battery performance of the sensor nodes is likewise constrained. As a result, the energy efficiency of WSNs is critical. In specific, the energy usage is influenced by the loads on the sensor node as well as it ranges from the Base Station (BS). Therefore, energy efficiency and load balancing are very essential in WSN. In the proposed method, a novel Grey Wolf Improved Particle Swarm Optimization with Tabu Search Techniques (GW-IPSO-TS) was used. The selection of Cluster Heads (CHs) and routing path of every CH from the base station is enhanced by the proposed method. It provides the best routing path and increases the lifetime and energy efficiency of the network. End-to-end delay and packet loss rate have also been improved. The proposed GW-IPSO-TS method enhances the evaluation of alive nodes, dead nodes, network survival index, convergence rate, and standard deviation of sensor nodes. Compared to the existing algorithms, the proposed method outperforms better and improves the lifetime of the network.     

A dynamic password-based user authentication scheme for hierarchical wireless sensor networks

Most queries in wireless sensor network (WSN) applications are issued at the point of the base station or gateway node of the network. However, for critical applications of WSNs there is a great need to access the real-time data inside the WSN from the nodes, because the real-time data may no longer be accessed through the base station only. So, the real-time data can be given access directly to the external users (parties) those who are authorized to access data as and when they demand. The user authentication plays a vital role for this purpose. In this paper, we propose a new password-based user authentication scheme in hierarchical wireless sensor networks. Our proposed scheme achieves better security and efficiency as compared to those for other existing password-based approaches. In addition, our scheme has merit to change dynamically the user's password locally without the help of the base station or gateway node. Furthermore, our scheme supports dynamic nodes addition after the initial deployment of nodes in the existing sensor network.     

HDEEC：面向异构网络的一种基于簇路由协议

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.为了延长网络,现存的多数簇方案是面向同构网络.为此,面向异构网络,提出基于簇的分布式能量有效路由HDEEC(heterogeneous WSN distributed energy-efficient clustering)协议.HDEEC协议首先提出异构网络模型,考虑了普通节点、特优节点和超特优节点三级能量节点;然后,提出能量消耗模型;最后依据这两个模型,提出了簇头选择方案.HDEEC协议以平衡、有效方式动态改变节点被选为簇头的概率.仿真结果表明,提出的HDEEC协议能够有效延长网络寿命,比DEEC、DDEEC的网络寿命分别提高了72％、68％.     

无线传感器网络权衡生存时间与数据分组跳数的分流路由算法*

无线传感器网络的节点大多采用电池供电.因而节能对无线传感器网络就显得至关重要.该文提出一种能耗感知的优化网络生存时间的路由算法,称之为分流路由算法(DTRA,Diffluent Traffic Routing Algorithm).DTRA算法采用一个优化模型以优化每个节点发出的数据比例,从而达到权衡网络生存时间和数据分组跳数.此外,采用一个简单的遗传算法求解该优化问题.仿真结果表明:DTRA算法能显著地提高网络的生存时间,同时将数据分组平均跳数保持在一个较低的水平;在网络生存时间上,DTRA算法比一些已有的知名算法更优.     

大规模无线传感网络的混合LEACH协议研究

能耗问题已经成为大规模无线传感器网络中的研究热点,因此如何设计高能效的路由协议是当前面临的技术挑战。为了降低传感器节点的能耗,提出一种适用大规模网络的基于LEACH算法的混合无线传感网络节能路由算法。首先,根据距离信息,设计一种簇成员向基站直接传输或者通过簇头转发数据的路由协议。然后,推导出满足该算法的能耗条件。最后,通过MATLAB工具仿真表明与已有的LEACH协议和M-LEACH协议相比,混合路由协议能够有效降低基站周围节点的能耗,从而延长整个网路的生存期。     

WSN中基于目标决策的源位置隐私保护方案

针对现有基于幻影源的无线传感网(Wireless Sensor Network,WSN)的源位置隐私保护方案,普遍存在无法有效平衡源位置隐私安全性、网络生存周期和传输延迟之间的矛盾关系的问题,提出了一种基于目标决策的幻影源分散路由方案PSSR(Phantom Source Separate path Routing)。该方案采用分段定象随机游走来确定幻影节点的位置,在保证幻影源距离真实源可视区足够远的同时,实现了幻影源位置的多样性,增大了攻击者定位源位置的难度。除此之外,该方案通过考虑节点的能量消耗、剩余能量及其到基站的距离来选取转发节点,实现了低概率重复分散路由的构建,有效平衡了源位置隐私安全性、网络生存周期和传输延迟之间的矛盾关系。仿真实验结果表明,相比EPUSBRF方案、PRLA方案和MPRP方案,PSSR方案在增强源位置隐私安全性的同时,能够有效延长网络生存周期和降低传输延迟。     

基于学习自动机的无线传感网能量均衡分簇算法

优化簇首选择、均衡节点能量负载以延长网络存活时间,一直是无线传感器网络分簇协议研究的重点。针对无线传感器网络节点随机分布的情况,在基于学习自动机(Learning Automata, LA)的ICLA算法基础上,提出一种兼顾节点密度的能耗均衡分簇算法。在簇头选举方面,综合考虑节点剩余能量和节点密度,利用学习自动机与周围环境进行信息交互和动作奖惩,选择出相对较优的簇头;根据簇首与基站距离和其节点密度构造大小非均匀的簇,实现不同位置不同网络疏密程度下簇内和簇间能耗互补均衡;构造了基于簇首剩余能量、簇内节点密度和传输距离的评价函数,并运用贪婪算法选择出最优中转簇首进行多跳传输。仿真实验结果表明,该算法能选择出更为合理的簇头,有效地均衡网络能量负载,延长网络生存时间。     

无线传感器网络分层带宽自适应路由协议

在无线传感器网络(WSNs)中,节点能量使用严格受限,限制了网络的使用寿命。固定环带宽度的分层路由协议是一种有效的解决方法。在此基础上,提出了一种引入环带宽度自适应调整的路由机制。该机制根据节点剩余能量和传输数据能耗自动调整环带宽度,并决定节点是否参与网内数据报文的传输。采用Matlab作为仿真工具对该路由机制进行了仿真分析,结果表明:该算法通过调整环带宽度的方式能够有效延长网络使用寿命和维持网内负载均衡。     

Maximizing network lifetime in wireless sensor networks with regular topologies

Limited energy supply (battery-powered) is a crucial problem in wireless sensor networks (WSNs). Sensor node placement schemes and routing protocols are mostly proposed to address this problem. In this paper, we first present how to place sensor nodes by use of a minimal number of them to maximize the coverage area when the communication radius of the sensor node is different from the sensing radius, which results in the application of regular topology to WSNs deployment. With nodes placed at an equal distance and equipped with an equal power supply, the problem of unbalanced energy consumption in 2-D regular topologies becomes more severe and much more difficult to tackle than that in 1-D chains, though the latter is known as an already quite hard problem. We address this problem and propose an adaptive data collection scheme by employing different communication radii for nodes in different locations to balance the energy consumption in WSNs. In order to achieve the ultimate goal of maximizing network lifetime in grid-based WSNs, we give a mathematical formulation, which shows the problem of maximizing network lifetime is a nonlinear programming problem and NP-hard even in the 1-D case. We discuss several heuristic solutions and show that the halving shift data collection scheme is the best solution among them. We also generalize the maximizing network lifetime problem to the randomly-deployed WSNs, which shows the significance of our mathematical formulation for this crucial problem in WSNs.