基于图着色的无线自组网极小连通支配集算法

基于连通支配集算法的虚拟主干网技术对于无线自组网的路由优化、能量保护和资源分配都具有重要的作用。通过引入极大独立集和极小支配集概念,基于图着色思想提出一种新的适合于无线自组网的极小连通支配集算法,从理论上证明了该算法的正确性和高效性,也通过仿真实验分析了该算法在多种情况下的实际性能,仿真结果表明新算法在簇头和主干节点数目方面具有较好的性能,特别在节点密集的网络环境中更加突出。     

一种等级化分布式时间同步算法

为了满足无线自组网中采用分布式TDMA组网所需的时间同步要求,提出了一种等级化分布式时间同步算法。该方法采用时间参考节点推选制度,实时更新参考节点,同时采用分层的时间等级和时间质量相结合使得在网的每个节点都能和自己周围最靠近时间参考点的节点进行对时同步,仿真实验结果表明,该方法能够提高同步精度,完全满足分布式TDMA无线自组网的时间同步要求。     

基于精简IPv6的自组网络

本文介绍了一种简单易实现的基于精简IPV6的自组网络,设计了微型无线传感器节点,选用了低功耗、低价格的ATMEGA16L单片机和数据无线收发芯片nRF905,实现了一种低功耗无线网络,分析了自组网络的体系结构,为进一步研究基于IPv6的无线传感器网络的其它算法提供了一个非常有价值的参考平台。     

信号强度和运动向量结合的无线传感器网络移动节点定位

无线传感器网络的定位是近年来无线传感器网络研究的重要课题.本文首先介绍了无线传感器网络的来源、重要性以及无线传感器网络定位的分类.然后提出了一种全新定位算法,信号强度和运动向量结合的无线传感器网络移动节点定位,简称SSMV算法,在外围布置四个锚节点,得用信号强度和未知节点在运动中向量的变化,对锚节点在内的未知节点进行定位,并对该算法进行了仿真和总结.通过与凸规划法进行比较,仿真结果表明,该算法有更高的定位精度.     

Ad Hoc网络移动节点的自身定位技术改进

网络节点的定位技术已成为无线自组网的关键技术之一,为了改善DV-Hop算法因多路径干扰和噪声干扰带来的误差,结合Convex-PIT算法,提出采用多次利用质心的思想,即利用未知节点可收到多组锚节点的信息,形成多个重叠的区域,并利用区域的质心得到初始解,最后采用卡尔曼滤波器对初始解进行优化,得到最终结果。实验表明,该技术提高了性能。     

模拟退火算法在无线传感器网络定位中的应用

近年来,随着对无线传感器网络研究的不断深入,节点定位问题受到了国内外研究者的极大关注。在深入研究无线传感器网络节点定位和模拟退火算法的基础上,提出了一种新颖的无线传感器网络节点定位算法,着重介绍了算法的基本原理和实现方法。仿真实验结果表明,该算法取得了良好的定位效果。该算法设计简单,计算量小,比较适合于无线传感器网络的节点定位。     

基于DV-Hop的RSSI-Hop算法

在无线传感器网络中,监测到时间之后关心的一个重要问题就是该事件发生的位置。传感器节点能量有限、可靠性差、节点规模大且随机布放、无线模块通信距离有限,对定位算法和定位技术提出了很高的要求。针对随机布放、节点配置低的无线传感器网络,提出一种新的RSSI-Hop定位方法,该方法可以在不增加硬件开销的基础上,有效降低节点能量消耗,较准确地估算未知节点到参考节点之间的距离,减少累积误差,提高定位的准确性。其主要思想是,节点信息根据RSSI强弱,估算各节点到信标节点之间的距离。实验表明,新算法比以前的算法定位更准确。     

温室环境中的一种自组网路由算法研究

针对无线传感器网络中节点在温室场境中的自组网问题,文章介绍了一种自组网路由算法,每个节点都运行相同的程序。首先,上电后节点等待入网;然后,将入网信息上传至汇聚节点。节点的入网或退出,都是自动执行。在实验室环境下进行模拟实验,文章所讲述的算法可以应用于温室环境中。     

基于网络演算的无线自组网QoS性能确定上界研究

为保证无线自组网的服务质量(QoS),需精确求解其性能确定上界.对进入无线自组网节点的数据流进行漏桶管制,节点为数据流提供基于速率-延迟(rate-latency)模型的服务保障,在已有无线自组网链路吞吐量模型的基础上利用网络演算理论推导了无线自组网节点的积压数据上界、端到端数据流的延迟上界以及端到端数据流的延迟抖动上界模型.对网格形式拓扑的无线自组网,不同数据流的仿真结果都在数值计算的上界范围之内,表明基于网络演算理论的无线自组网的QoS性能上界模型具有较好的性能.     

无线自组网路由协议仿真与实现

性能良好的路由算法可以降低传输延时、提高包到达率、合理处理网络拥塞,总而言之,有效提高网络的传输性能。然而在无线自组网中,没有最优的算法,网络规模、节点特性的不同,都会使路由算法的表现千差万别。着力研究了无线自组网中常用的几种路由算法,建立不同的网络场景,使用NS2进行仿真,分析数据包的行为,比较两类路由协议的性能差异和优缺点,以仿真结果给架设无线自组网时路由协议的选择给出了指导性的意见,并在嵌入式路由器上实现了路由算法行为,     

Computational intelligence based localization of moving target nodes using single anchor node in wireless sensor networks

Wireless Sensor Networks (WSNs) have tremendous ability to interact and collect data from the physical world. The main challenges for WSNs regarding performance are data computation, prolong lifetime, routing, task scheduling, security, deployment and localization. In recent years, many Computational Intelligence (CI) based solutions for above mentioned challenges have been proposed to accomplish the desired level of performance in WSNs. Application of CI provides independent and robust solutions to ascertain accurate node position (2D/3D) with minimum hardware requirement (position finding device, i.e., GPS enabled device). The localization of static target nodes can be determined more accurately. However, in the case of moving target nodes, accurate position of each node in network is a challenging problem. In this paper, a novel concept of projecting virtual anchor nodes for localizing the moving target node is proposed using applications of Particle Swarm Intelligence, H-Best Particle Swarm Optimization, Biogeography Based Optimization and Firefly Algorithm separately. The proposed algorithms are implemented for range-based, distributed, non-collaborative and isotropic WSNs. Only single anchor node is used as a reference node to localize the moving target node in the network. Once a moving target node comes under the range of a anchor node, six virtual anchor nodes with same range are projected in a circle around the anchor node and two virtual anchor nodes (minimum three anchor nodes are required for 2D position) in surrounding (anchor and respective moving target node) are selected to find the 2D position. The performance based results on experimental mobile sensor network data demonstrate the effectiveness of the proposed algorithms by comparing the performance in terms of the number of nodes localized, localization accuracy and scalability. In proposed algorithms, problem of Line of Sight is minimized due to projection of virtual anchor nodes.     

移动无线传感器网络中节点自定位算法研究

移动无线传感器网络(MWSN)是一种全新的信息获取和处理技术,可以在广泛的应用领域内实现复杂的大规模监测和追踪任务,而移动节点的位置信息则是其应用的基础。针对这一特征,文章深入探讨了移动节点自定位算法的研究现状,介绍了移动无线传感器网络节点定位的基本方法,讨论了定位算法的性能评价指标,并对各种算法性能进行了比较,最后指出了算法存在的问题和解决办法。文章认为三维全节点移动的定位算法将成为以后的研究趋势。     

Rate allocation strategies for energy-efficient multipath routing in Ad-hoc networks towards B3G

Wireless mobile Ad-hoc network is a special network that all nodes can self-organize and work together. It is flexible to form a network and extend the coverage area dynamically without infrastructure, so Ad-hoc network is envisioned as cornerstones of future generation networking technologies (B3G or 4G). However, the dynamic network topology makes the communication cost not only the energy of source/destination nodes, but also the relay nodes. Another problem of the Ad-hoc network is it is hard to provide a stable and persistent quality of service (QoS), which is strongly required by the beyond 3rd generation (B3G) system. In this article, the authors establish a scenario that contains B3G cellular base station and Ad-hoc mobile nodes, and propose two algorithms minimum incremental rate algorithm and power feed-back rate allocation algorithm in multipath routing. The algorithms can maintain a constant total transmission rate and bit error ratio (BER) to provide the QoS guarantee and reach the minimum power consumption of the relay nodes by adjusting the rate of each path in the multipath routing.     

On localization in sensor network with inaccurate and incomplete distance measurements

The sensor network localization problem has received a lot of attention in recent years because many important applications resort to node position information. In contrast to the many interesting algorithms proposed in the literature, this paper provides a relatively straightforward procedure that can tackle localization problem for sensor network in a Least Squares Euclidean Distance Matrix Approximation （LS-EDMA） framework. Simulation results reveal that our proposed algorithm is more robust than another popular Multi-Dimensional Scaling （MDS） and Semi-Definite Programming （SDP） based localization techniques, especially with inaccurate and incomplete distance measurements.     

Neural-based approach for localization of sensors in indoor environment

Location of wireless sensor nodes is an important piece of information for many applications. There are many algorithms present in literature based on Received Signal Strength (RSSI) to estimate the location. However the radio signal propagation is easily influenced by diffraction, reflection and scattering. Therefore algorithms purely based on RSSI may not accurately predict the position of the node. In the present work, an algorithm for estimating the position of mobile nodes is proposed which is based on a combination of Received Signal Strength (RSSI) and Link Quality Indicator (LQI). Artificial Neural Networks are used to establish the relationship between the location of the mobile node and the experimentally obtained values of RSSI and LQI. Two different algorithms namely, Bayesian Regularization and Gradient Descent are used to develop the neural network model. Proposed algorithms improve the localization accuracy and perform better than other state-of-the-art algorithms.     

Analyzing localization errors in one-dimensional sensor networks

One-dimensional sensor networks can be found in many fields and demand node location information for various applications. Developing localization algorithms in one-dimensional sensor networks is trivial, due to the fact that existing localization algorithms developed for two- and three-dimensional sensor networks are applicable; nevertheless, analyzing the corresponding localization errors is non-trivial at all, because it is helpful to improving localization accuracy and designing sensor network applications. This paper deals with localization errors in distance-based multi-hop localization procedures of one-dimensional sensor networks through the Cramér-Rao lower bound (CRLB). We analyze the fundamental behaviors of localization errors and show that the localization error for a sensor is locally determined by network elements within a certain range of this sensor. Moreover, we break down the analysis of localization errors in a large-scale sensor network into the analysis in small-scale sensor networks, termed unit networks, in which tight upper and lower bounds on the CRLB can be established. Finally, we investigate two practical issues: the applicability of the analysis based on the CRLB and the optimal anchor placement.     

RPSF: A Routing Protocol with Selective Forwarding for Mobile Ad-Hoc Networks

Many existing reactive routing algorithms for mobile ad-hoc networks use a simple broadcasting mechanism for route discovery which can lead to a high redundancy of route-request messages, contention, and collision. Position-based routing algorithms address this problem but require every node to know the position and velocity of every other node at some point in time so that route requests can be propagated towards the destination without flooding the entire network. In a general ad-hoc network, each node maintaining the position information of every other node is expensive or impossible. In this paper, we propose a routing algorithm that addresses these drawbacks. Our algorithm, based on one-hop neighborhood information, allows each node to select a subset of its neighbors to forward route requests. This algorithm greatly reduces the number of route-request packets transmitted in the route-discovery process. We compare the performance of our algorithm with the well known Ad-hoc On-demand Distance Vector (AODV) routing algorithm. On average, our algorithm needs less than 12.6% of the routing-control packets needed by AODV. Simulation results also show that our algorithm has a higher packet-delivery ratio and lower average end-to-end delay than AODV.     

Transmission capacity for inhomogeneous overlaid wireless Ad-hoc networks

In the analysis of overlaid wireless Ad-hoc networks, the underlying node distributions are commonly assumed to be two independent homogeneous Poisson point processes. In this paper, by using stochastic geometry tools, a new inhomogeneous overlaid wireless Ad-hoc network model is studied and the outage probability are analyzed. By assuming that primary （PR） network nodes are distributed as a Poisson point process （PPP） and secondary （SR） network nodes are distributed as a Matern cluster processes, an upper and a lower bounds for the transmission capacity of the primary network and that of the secondary network are presented. Simulation results show that the transmission capacity of the PR and SR network will both have a small increment due to the inhomogeneity of the SR network.     

Topology-aware peer-to-peer overlay network for Ad-hoc

The mismatch between the structured peer-to-peer (P2P) overlay network, which is based on Hashing, and the actual physical network, leads to query repeatedly passing through some nodes in the actual route when it is applied in Ad-hoc networks. An approach of getting an appropriate node identifier (ID) bearing its local physical information is proposed, in which the traditional theory of getting node ID through Hashing the node's Internet protocol (IP) address is abandoned, and a topology-aware overlay network suiting Ad-hoc networks is constructed. The simulation results show that the overlay network constructed in the proposed method can avoid the route being iteratively accessed. Meanwhile, it can effectively minimize the latency and improve the load balance.     

Attack containment in mobile ad-hoc networks through fair distribution of processing resources

Due to frequent joining and leaving of nodes and better performance, use of flooding algorithms is always proffered in Mobile Ad-hoc Networks (MANETs). A single query transmitted by a node can be received by hundreds of nodes at 3rd or 4th hop. But it is also fact that flooding algorithms provide an opportunity to attackers for launching query flooding attacks. On one side these query flooding attacks results in wastage of valuable processing resources and on the other side they cause in starvation and delay at legitimate user’s end. To solve this problem we proposed attack containment techniques by providing a fair share of processing resources to every node. Fair distribution is achieved by designing different query distribution techniques based on mathematical models. Results obtained through network simulator 2 prove that the proposed solution is resilient against various types of flooding attacks.