DFA：基于802.11的无线网络动态帧分片与聚集方案

提出了一种适用于基于IEEE 802.11的无线网络的动态帧分片与聚集方案。该方案依据实时的信噪比信息来判断链路误码率,利用分片和聚集操作动态调整发送帧的长度,从而减少误码重传的发生。模拟实验证明,该方案能够有效提高WLAN以及无线Mesh网络为代表的基于802.11的无线单跳以及多跳网络的传输性能。     

基于IEEE802.11n的长距离无线链路性能分析

IEEE802.11n-2009在传统802.11协议上添加了帧聚合和块回复功能,实现了MAC层增强,显著提高了网络吞吐量,使其更加适用于长距离无线网络。通过长距离(45km)无线链路信道利用率的理论计算和网络仿真,论证了节点采用帧聚合与块回复功能时的信道利用率明显优于不采用的情况。仿真结果进一步表明,速率越高、聚合帧越大在长距离传输时的吞吐量越高,且距离越远时帧聚合的优势越明显。     

IEEE 802.11无线局域网标准研究*

介绍了IEEE 802.11全系列标准,研究了IEEE 802.11系列各标准的发展轨迹和相互关系,建立了该系列标准的层次模型。研究并分析了IEEE 802.11、IEEE 802.11a、IEEE 802.11b、IEEE 802.11g和IEEE 802.11n这几种常见标准,并对相应物理层和媒质访问控制层的关键技术作了重点分析。     

DFA:基于 802. 11的无线网络动态帧分片与聚集方案 *

提出了一种适用于基于 IEEE 802. 11的无线网络的动态帧分片与聚集方案。该方案依据实时的信噪比信息来判断链路误码率 ,利用分片和聚集操作动态调整发送帧的长度 ,从而减少误码重传的发生。模拟实验证明 ,该方案能够有效提高 WLAN以及无线 Mesh网络为代表的基于 802. 11的无线单跳以及多跳网络的传输性能。     

Analyzing the effective throughput in multi-hop IEEE 802.11n networks

In this paper we characterize the effective throughput for multi-hop paths in IEEE 802.11n based wireless mesh networks. We derive an analytical model capturing the effects of frame aggregation and block acknowledgements, features found in the new IEEE 802.11n standard. We describe the throughput at MAC layer as a function of physical data rate, error rate, aggregation level and path length. While being mathematically tractable, the proposed model is flexible enough to account for complex and realistic error characteristics of the wireless channel, such as long-term fluctuations and burstiness. We further show how to integrate the well-known Gilbert-Elliot channel model into our model and evaluate both models in our indoor wireless testbed.     

无线传感器网络中基于预测的时域数据融合技术

数据融合是无线传感器网络中重要的研究领域之一。在无线传感器网络中,数据融合的作用主要体现在节省能量、提高数据收集效率、增强数据准确性以及获取综合性信息等几个方面。时间序列分析是一种根据动态数据揭示系统动态结构以及规律的统计方法。基于监测数据的时间序列模型以及时间序列预测,提出适用于无线传感器网络的基于预测的时域数据融合方法,以部署于故宫博物院的环境监测网络采集的温度数据作为样本,通过仿真对该方法进行有效性验证以及性能分析。结果表明,一阶自回归预测算法与其它预测算法相比,具有更好的适用性,当误差阈值为0.05 ℃-0.50 ℃时,预测成功率为21%-83%;当误差阈值为0.05 ℃时,节能收益达到68%。     

Distributed channel assignment algorithms for 802.11n WLANs with heterogeneous clients

As the latest IEEE 802.11 standard, 802.11n applies several new technologies, such as multiple input multiple output (MIMO), channel bonding, and frame aggregation to greatly improve the rate, range and reliability of wireless local area networks (WLANs). In 802.11n WLANs, access points (APs) are often densely deployed to provide satisfactory coverage. Thus nearby APs should operate at non-overlapping channels to avoid mutual interference. It is challenging to assign channels in legacy 802.11a/b/g WLANs due to the limited number of channels. Channel assignment becomes more complex in 802.11n WLANs, as the channel bonding in 802.11n allows WLAN stations (APs and clients) to combine two adjacent, non-overlapping 20MHz channels together for transmission. On the other hand, IEEE 802.11n is backward compatible, such that 802.11n clients will coexist with legacy clients in 802.11n WLANs. Legacy clients may affect the performance of nearby 802.11n clients, and reduce the effectiveness of channel bonding. Based on these observations, in this paper, we study channel assignment in 802.11n WLANs with heterogeneous clients. We first present the network model, interference model, and throughput estimation model to estimate the throughput of each client. We then formulate the channel assignment problem into an optimization problem, with the objective of maximizing overall network throughput. Since the problem is NP-hard, we give a distributed channel assignment algorithm based on the throughput estimation model. We then present another channel assignment algorithm with lower complexity, and aim at minimizing interference experienced by high-rate, 802.11n clients. We have carried out extensive simulations to evaluate the proposed algorithms. Simulation results show that our algorithms can significantly improve the network throughput of 802.11n WLANs, compared with other channel assignment algorithms.     

无线传感器网络中最大化网络寿命的数据聚合路由

针对数据聚合无线传感器网络寿命最大化问题,分析了网络流量和节点能耗,提出了数据聚合路由问题的网络流量模型,并将网络最大寿命与流量模型相结合设计了一组混合整数规划代价函数.采用对偶分解的方法,获得了近似最优的中继传输速率和路由.仿真实验表明,该算法能有效减少数据通信量,均衡各个节点的能量消耗,延长网络寿命.     

Data aggregation in wireless sensor networks using ant colony algorithm

Data aggregation is important in energy constraint wireless sensor networks which exploits correlated sensing data and aggregates at the intermediate nodes to reduce the number of messages exchanged network. This paper considers the problem of constructing data aggregation tree in a wireless sensor network for a group of source nodes to send sensory data to a single sink node. The ant colony system provides a natural and intrinsic way of exploring search space in determining data aggregation. Moreover, we propose an ant colony algorithm for data aggregation in wireless sensor networks. Every ant will explore all possible paths from the source node to the sink node. The data aggregation tree is constructed by the accumulated pheromone. Simulations have shown that our algorithm can reduce significant energy costs.     

无线传感器网络中一种高效的能量汇报融合机制

通过对telosb节点能耗规律的分析,建立能量预测模型（EFM）采用差介阈值融合汇报机制（DTARM）能够显著减少能量数据汇报次数,提高数据收集效率,降低能耗。实验表明：预测模型的预测成功率为70％-85％,采用差分-阈值融合汇报机制后能使节点的寿命延长5％-11％。     

Continuous data aggregation and capacity in probabilistic wireless sensor networks

Due to the existence of many probabilistic lossy links in Wireless Sensor Networks (WSNs) (Liu et al., 2010)  [25], it is not practical to study the network capacity issue under the Deterministic Network Model (DNM). A more realistic one is actually the Probabilistic Network Model (PNM). Therefore, we study the Snapshot Data Aggregation (SDA) problem, the Continuous Data Aggregation (CDA) problem, and their achievable capacities for probabilistic WSNs under both the independent and identically distributed (i.i.d.) node distribution model and the Poisson point distribution model in this paper. First, we partition a network into cells and use two vectors to further partition these cells into equivalent color classes. Subsequently, based on the partitioned cells and equivalent color classes, we propose a Cell-based Aggregation Scheduling (CAS) algorithm for the SDA problem in probabilistic WSNs. Theoretical analysis of CAS and the upper bound capacity of the SDA problem show that the achievable capacities of CAS are all order optimal in the worst case, the average case, and the best case. For the CDA problem in probabilistic WSNs, we propose a Level-based Aggregation Scheduling (LAS) algorithm. LAS gathers the aggregation values of continuous snapshots by forming a data aggregation/transmission pipeline on the segments and scheduling all the cell-levels in a cell-level class concurrently. By theoretical analysis of LAS and the upper bound capacity of the CDA problem, we prove that LAS also successfully achieves order optimal capacities in all the cases. The extensive simulation results further validate the effectiveness of CAS and LAS.     

无线传感器网络中的数据融合及其能效评估*

首先介绍当前无线传感器网络中具有代表性的数据融合算法;然后基于树型网络拓扑结构,结合节点休眠调度机制,建立传感器节点的能量模型;最后提出从能量的角度评价不同数据融合算法性能的方法,并通过模拟对典型数据融合算法进行分析.     

基于802.11n的多功能无线传输平台的设计与应用

针对现有煤矿井下人员定位系统存在功能单一、定位精度不高的问题,设计了一种基于802.11n的煤矿本安型多功能无线传输平台。该平台基于802.11n传输协议和采用信号强度测量模块,不仅实现了数据、语音和视频等的高速传输,还可同时通过WiFi信号实现井下人员的实时定位。煤矿井下实际测试结果表明,该平台的无线传输速率达到了120Mbit/s,信号覆盖范围为500m,实时定位精度为9.68m,满足了煤矿安全信息的传输要求。     

基于IEEE802.11n的无线网络及其在校园网的应用研究

该文对IEEE802.11n的标准及其核心技术进行了介绍,并就基于它的无线设备组建的校园网进行了分析,对它在校园网中的应用进行了研究。     

无线传感器网络中基于分簇的数据聚合机制

在无线传感器网络(WSNs)中如何有效聚合数据是当前物联网应用中的重要挑战.然而在已有的若干解决方案中,传感器的计算和通信过程消耗了较高的能量,数据的隐私性和完整性得不到有效保障.针对上述问题,提出一种基于分簇的数据聚合机制,采用代数方程计算传感器的中间数据聚合值,采用数字签名进行簇间传感器的身份认证.实验表明:该机制能有效降低传感器计算和通信的耗能,保证数据的隐私性和完整性.     

Secure and energy-efficient data aggregation with malicious aggregator identification in wireless sensor networks

Data aggregation in wireless sensor networks is employed to reduce the communication overhead and prolong the network lifetime. However, an adversary may compromise some sensor nodes, and use them to forge false values as the aggregation result. Previous secure data aggregation schemes have tackled this problem from different angles. The goal of those algorithms is to ensure that the Base Station (BS) does not accept any forged aggregation results. But none of them have tried to detect the nodes that inject into the network bogus aggregation results. Moreover, most of them usually have a communication overhead that is (at best) logarithmic per node. In this paper, we propose a secure and energy-efficient data aggregation scheme that can detect the malicious nodes with a constant per node communication overhead. In our solution, all aggregation results are signed with the private keys of the aggregators so that they cannot be altered by others. Nodes on each link additionally use their pairwise shared key for secure communications. Each node receives the aggregation results from its parent (sent by the parent of its parent) and its siblings (via its parent node), and verifies the aggregation result of the parent node. Theoretical analysis on energy consumption and communication overhead accords with our comparison based simulation study over random data aggregation trees.     

无线传感网安全数据聚合研究

如何保障数据在聚合,计算和存储以及转发等过程中的数据机密性、完整性,是无线传感网安全研究的核心环节·针对这个核心环节首先分析了无线传感网数据聚合过程中面临的安全威胁,进而提出数据安全聚合的基本要求,在自组织环结构的基础上,提出了一种新的无线传感网数据安全聚合方案,并分析了该方案的性能及其安全性.     

无线传感器网络中数据融合算法研究

在提供高效的数据融合的同时保障数据的安全是无线传感器网络的研究的一个具有挑战性的问题。本文为加法融合函数设计了一种具有隐私保护功能的数据融合算法——基于分簇的安全数据融合。该算法利用了分簇协议和多项式的代数性质。其优点为带来的通信开销较小。研究的主要目标是提高无线传感器网络中数据融合效率的同时,保证数据的安全性。     

无线传感器网络的数据聚合时机分析

数据聚合是无线传感器网络实现节能的一种重要技术。数据聚合的时机直接影响到数据聚合的准确度和延时,是数据聚合的关键问题之一。建立基于泊松过程的数据聚合模型,分析数据聚合时机的概率特征,提出满足一定概率要求和信息数要求的条件下,数据聚合时机的求解方法。仿真表明,理论分析和模拟实验结果基本相符。该结论为数据聚合时机的分析提供新的思路。     

TDMA scheduling for event-triggered data aggregation in irregular wireless sensor networks

Multi-hop wireless sensor networks often use a TDMA schedule to collect data periodically from multiple locations within a large area. If the measurements from neighboring sensors are cross-correlated, they can be aggregated and compressed as they travel to the data sink. In order for data aggregation to occur quickly, the TDMA schedule must arrange time slot assignments in a certain order. The existing scheduling protocols cannot quickly obtain a schedule with this order, high concurrency, and no collisions. We propose a distributed TDMA scheduling protocol for data aggregation called DATP. In DATP, the sensor nodes transmit dummy packets in order to determine whether they can tolerate the interference from the other nodes that are assigned the same time slot. In this way, time slot allocations are empirically verified to be collision-free. In contrast, the existing protocols obtain schedules with collisions because they use unrealistic interference models such as neglecting interference generated more than two hops away. Furthermore, our simulations reveal that DATP achieves similar concurrency and lower execution time than comparable protocols. These simulations are executed for different network sizes, node densities, and data compression models. In addition, we show that, in networks with fluctuating links, DATP’s main advantage is its execution speed.