无线传感器网络数据融合技术的研究与仿真

数据融合技术是无线传感器网络中的关键技术.提出了一种动态自适应制数据融合机制(wADA),该机制主要思想是根据接收到的数据应答包数量,动态调整最大延迟时间,并最大延迟时间按照递减规则分配至各层节点,以平衡数据的准确性和实效性.OPNET仿真结果表明,WADA数据融合机制可以有效地收敛到最佳的最大延迟时间.     

Robust and dynamic data aggregation in wireless sensor networks: A cross-layer approach

In-network data aggregation is an effective technique to reduce communication cost in wireless sensor networks. Recent studies have focused on two issues respectively: dynamic aggregation to handle event triggered irregular traffic and robust aggregation to handle packet losses. However, how to achieve both the objectives simultaneously, i.e. dynamic and robust aggregation is still not considered. In this paper, by making use of direct support from MAC layer, we propose a cross-layer approach to realize robust and dynamic data aggregation. A new MAC protocol, DA-MAC is delicately designed to serve such purpose. With channel contention information obtained from DA-MAC, a node can dynamically determine where and when to do aggregation. To cope with packet losses, a virtual overlay, Rings is adopted to forward one packet to multiple nodes. We have conducted numerical analysis to optimize the key parameters and implemented our design in TinyOS based sensor networks. Performance evaluation though simulations and experiments shows that our approach can handle both traffic dynamics and packet losses, with less cost than similar solutions.     

无线传感器网络基于定向扩散与分批估计的数据融合算法

无线传感器网络中采集的数据存在着较大的冗余与误差,造成能量消耗过多,并且影响数据的可靠性。针对这个问题提出一种基于定向扩散与分批估计的数据融合算法,对监测同一对象的多个传感器所采集的数据进行综合,提高数据精度和可信度,并减少数据传输量,从而降低了功耗。通过对室内环境参数(温度)的监测验证了这种算法的可行性。     

DyDAP: A dynamic data aggregation scheme for privacy aware wireless sensor networks

End-to-end data aggregation, without degrading sensing accuracy, is a very relevant issue in wireless sensor networks (WSN) that can prevent network congestion to occur. Moreover, privacy management requires that anonymity and data integrity are preserved in such networks. Unfortunately, no integrated solutions have been proposed so far, able to tackle both issues in a unified and general environment. To bridge this gap, in this paper we present an approach for dynamic secure end-to-end data aggregation with privacy function, named DyDAP. It has been designed starting from a UML model that encompasses the most important building blocks of a privacy-aware WSN, including aggregation policies. Furthermore, it introduces an original aggregation algorithm that, using a discrete-time control loop, is able to dynamically handle in-network data fusion to reduce the communication load. The performance of the proposed scheme has been verified using computer simulations, showing that DyDAP avoids network congestion and therefore improves WSN estimation accuracy while, at the same time, guaranteeing anonymity and data integrity.     

无线传感器安全聚集协议

传统网络的安全机制不能直接应用于无线传感器网络,因此对无线传感器网络的数据聚集安全进行了研究,提出了一种新的安全机制.该安全机制使用消息认证码(MAC)的形式和概率性验证来保证数据的安全聚集,可以应用于网络各层,而不仅限于路由层.分析了新的安全数据聚集协议的性能,并与已有的安全数据聚集协议进行了对比.从分析结果可以看出,新的安全数据聚集协议不但安全性更高,而且传输的通信量也大大减少.     

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.     

无线传感器网络的差错控制技术研究

在分析传统无线网络差错控制方案的基础上,研究差错控制引起的能量消耗因素,通过介绍无线传感器网络能量消耗模型,借助Synopsys power comp lier分析了采用前项差错控制以及常用纠错码所引起的能量消耗。最后,讨论了无线传感器网络差错控制技术今后的研究重点。     

基于虚拟网格的无线传感器网络数据融合算法

无线传感器网络的能量供应和通信带宽等资源相对有限,难以适应大量数据的传输,需要在网络内部对原始监测数据进行压缩或聚合处理.为了充分利用其空间和时间相关性来进行数据压缩,提出了一种基于虚拟网格的数据融合算法.该算法基于虚拟网格来构建采集数据矩阵,并分别利用时域差分和二维离散余弦变换来去除时间和空间冗余.仿真实验和理论分析表明:该算法具有良好的压缩性能,有效地降低了节点能耗和提高了网络生命周期.     

Secure data aggregation in wireless sensor networks: A comprehensive overview

Wireless sensor networks often consists of a large number of low-cost sensor nodes that have strictly limited sensing, computation, and communication capabilities. Due to resource restricted sensor nodes, it is important to minimize the amount of data transmission so that the average sensor lifetime and the overall bandwidth utilization are improved. Data aggregation is the process of summarizing and combining sensor data in order to reduce the amount of data transmission in the network. As wireless sensor networks are usually deployed in remote and hostile environments to transmit sensitive information, sensor nodes are prone to node compromise attacks and security issues such as data confidentiality and integrity are extremely important. Hence, wireless sensor network protocols, e.g., data aggregation protocol, must be designed with security in mind. This paper investigates the relationship between security and data aggregation process in wireless sensor networks. A taxonomy of secure data aggregation protocols is given by surveying the current “state-of-the-art” work in this area. In addition, based on the existing research, the open research areas and future research directions in secure data aggregation concept are provided.     

无线传感器网络安全数据汇聚协议

无线传感器网络中,如何将数据汇聚技术与路由技术结合,设计高效的数据汇聚协议,以减少传输过程中的数据量,减轻数据汇聚过程中的网络拥塞,协助路由协议延长网络的生存时间是一个重要的问题。尽管数据汇聚能有效地减小通信开销,但数据汇聚技术也不可避免的带来了一系列安全问题,譬如传感数据外泄等,因而安全问题成为数据汇聚中一个重要研究方向。目前,安全数据汇聚技术及其实现协议已经成为传感器网络安全的研究中一个重要课题。详细介绍安全数据汇聚协议这个领域内的研究进展和成果,从安全角度对比分析各种现有协议,最后结合该领域内的研究现状以及作者的研究体会指出了该领域未来研究的一些重要方向。     

Energy-efficient cooperative data aggregation for wireless sensor networks

Recently, cooperative communication mechanism is shown to be a promising technology to improve the transmit diversity only by a single transceiver antenna. Using this communication paradigm, multiple source nodes are able to coordinate their transmissions so as to obtain energy savings. As data aggregation is one of the most important operations in wireless sensor networks, this paper studies the energy-efficient data aggregation problem through cooperative communication. We first define the cooperative data aggregation (CDA) problem, and formally prove that this problem is NP-Hard. Due to the difficult nature of this problem, we propose a heuristic algorithm MCT for cooperative data aggregation. The theoretical analysis shows that this algorithm can reach the approximate performance ratio of 2. Moreover, the distributed implementation DMCT of the algorithm is also described. We prove that both centralized and distributed algorithms can construct the same topology for cooperative data aggregation. The experimental simulations show that the proposed algorithms will decrease the power consumption by about 12.5% and 66.3% compared with PEDAP and PEGASIS algorithms respectively.     

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.     

Energy-efficient and high-accuracy secure data aggregation in wireless sensor networks

Due to the inherent characteristics of resource-constrained sensors, communication overhead is always a major concern in wireless sensor networks (WSNs). Data aggregation is an essential technique to reduce the communication overhead and prolong network lifetime. Since data aggregation results are usually used to make critical decisions, the accuracy of final aggregation results is very important. Furthermore, as wireless sensor networks are increasing being deployed in security-critical applications, we should take security into consideration as well. Therefore, for such applications, data aggregation protocols must be highly energy efficient and highly accurate while being able to prevent an adversary from stealing private data held by each sensor node. In this paper, we propose an energy-efficient and high-accuracy (EEHA) scheme for secure data aggregation. The main idea of our scheme is that accurate data aggregation is achieved without releasing private sensor readings and without introducing significant overhead on the battery-limited sensors. We conduct extensive simulations to evaluate the performance of EEHA. Our analysis and simulations show that EEHA is more efficient and accurate than the existing scheme.     

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。     

无线传感器网络动态电压调度算法

针对无线传感器网络的节点在运行状态提出了动态电压调度(DVS)算法。DVS是通过改变处理器的工作电压和工作频率来减少处理器的消耗能量。该方法首先必须对节点各部分发出的信号进行分析和预测,并根据预测后的信号对处理器设定处理速率,最后,设定合适的工作电压和工作频率。     

无线传感器网络数据融合体系结构综述

从无线传感器网络数据融合的特点和研究现状出发,分析了数据融合与网络协议层之间的联系,并阐述了数据融合在各层中发挥的作用。对数据融合的分类模型进行了较为系统的讨论,并对分层模型的具体细节进行了分析,指明了数据融合在该框架中的层次定位、功能分配及传输形式,为无线传感器网络高效的管理方法和有效的能源利用率提供参考。     

低时延的无线传感器网络数据融合算法

由于网内数据融合过程中融合节点在等待其孩子结点传输数据的时间对数据融合过程有很大影响,为减少此等待时间,降低整体的融合时间,提出一种改进的数据融合算法.该算法根据节点的传榆范围,一个簇被分为多个区域,每个节点根据自己所处的区域选择多跳或单跳通信方式向簇头传输数据,减少了等待时间.仿真结果表明,该算法可以降低数据融合时间,减少网络时延.