基于WMSNs的图像压缩技术研究

无线多媒体传感器网络(WMSNs)通过数量庞大的终端传感节点实现对外部环境的监测,并通过无线网络进行通信。随着外部环境的不断变化,对无线多媒体传感器网络的环境监测性能也提出了新的需求,如将各类多媒体资源加入到环境监测中,以获得更为细化精准的监测信息。文章综合分析了WMSNs图像压缩技术的研究发展现状,指出了现有的WMSNs图像压缩技术的不足以及应用WMSNs的图像压缩技术应满足的要求;并对图像压缩中的三种主要变换,即DCT变换、小波变换、双正交叠式变换(LBT)进行了分析比较。同时根据WMSNs的特点,提出了基于双正交重叠变换技术(LBT)的多节点协同图像压缩优化算法设计策略,有效解决了WMSNs的单节点图像处理功能受限问题。     

一种面向无线多媒体传感器网络的分布式图像压缩算法

因为多媒体数据的高带宽要求,要传输传感器节点采集到的原始数据将会消耗大量的资源。文章提出了一种分布式图像压缩算法,该算法通过把压缩任务分配给其他节点来解决在能量受限的节点上处理能力不足的问题。此外,该算法把压缩任务分配给其他空闲节点能很好的延长网络的生存时间。     

基于GA-ACO-BP的WSN数据融合算法实现

在无线传感网络中,为了提高多传感器数据融合性能,解决传感器电池频繁更换,延长网络生命周期,提出一种将遗传算法与蚁群算法相结合改进BP神经网络的多传感器数据融合算法(GA-ACO-BP)。GA-ACO-BP算法结合了遗传算法和蚁群算法的优势,传感器网络节点将信息通过LEACH协议对数据进行融合处理,降低数据发往Sink节点的传输量,减少数据传输造成的能量消耗。通过实验仿真显示,GA-ACO-BP算法和基于LEACH协议的算法、ACO-BP算法相比,该算法能减少需要传输的数据量,延长网络生存周期。     

传感器网络小波数据压缩算法的设计与实现

无线传感器网络是无线网络重点研究的内容,数据压缩是其中的一项关键技术。文章研究无线传感器网络中基于小波变换的数据压缩算法设计与实现问题。首先提出适合资源受限无线传感器网络的渐进Haar小波变换,然后基于信号量机制和游程编码提出了一种小波数据压缩算法在无线传感器网络中的实现方案。原型系统实验表明,算法具有低的压缩压缩误差和较高的压缩比。     

基于压缩感知的图像压缩抗干扰重构算法

针对传统图像变换压缩方法压缩的图像经无线信道传输时受高斯随机干扰导致重要变换系数失真出现重构图像局部内容缺失的现象,本文根据压缩感知(CS)信号分量具有同等重要性的特性,理论分析了去除失真CS信号分量以抵御干扰的可行性,提出一种基于CS的图像压缩抗干扰重构算法。算法首先假定已知受高斯随机干扰的比特所对应的CS信号分量的位置,然后根据这些位置确定新的CS信号和重构矩阵,再进行阈值迭代重构。仿真结果表明,本文算法在低误码率(BER)下得到精确重构的图像,在高BER下得到图像内容无缺失仅全局质量小幅下降的重构图像。因此,基于CS的图像压缩抗干扰重构算法能够较好地克服变换压缩方法以及阈值迭代重构算法抗干扰能力低的不足,从而为图像无线传输抗高斯随机干扰问题提供一种可行的解决方案。     

基于 RSSI 的无线传感器网络节点定位算法研究

节点位置信息是无线传感器网络应用的基础。基于RSSI（Receive Signal Strength Indicator）的测距技术因其低成本和低复杂度的优点而被广泛用于无线传感器网络的定位技术中。介绍了RSSI信号传输模型,在介绍无线传感器网络定位基本原理的基础上,分析了影响定位精度的因素。综述了近几年提出的无线传感器网络中基于RSSI的节点定位算法及其改进算法,现有基于RSSI定位算法的改进算法主要从测距精度改进、定位精度改进或误差修正改进等方面进行。最后,指出了基于RSSI的无线传感器网络节点定位算法的不足,并进行展望。     

无线传感器网络中基于序列相关性的数据压缩算法

无线传感器网络(WSN)中传输的数据具有相关性和冗余性。如何有效降低网络中的数据量,延长网络生命周期,始终是WSN的研究热点之一。该文基于WSN中数据序列的相关性,提出一种两步数据压缩算法(TSC-SC)。网络中的簇首和簇内节点执行各自的压缩算法:簇首首先执行相关性分组算法,将数据分组,减少簇内节点的计算量以及消除簇内数据的空间相关性;簇内节点对多属性数据分类压缩,并将压缩参数传至簇首,簇首解压后再次进行分类压缩,进一步消除数据相关性,减少节点数据冗余度,降低通信能耗。为实现对压缩算法的综合性能评价,考虑基本的压缩要求和算法的计算能耗,提出了基于能量判别的算法评估模型(NCER)。仿真结果表明TSC-SC算法可以有效降低压缩比和压缩误差,充分减少数据传输量和网络的通信能耗,利用NCER指标能够直观地评价算法的性能。     

无线传感器网络数据自适应稀疏变换

针对无线传感器网络节点位置移动及传输干扰等因素可导致数据稀疏结构改变的问题,提出一种基于字典学习的无线传感器网络自适应稀疏变换方法。根据网络数据稀疏结构变化,自适应构建最优稀疏变换基,同时在字典学习问题中引入无线传感器网络数据稀疏基的可压缩约束,以满足无线传感器网络中大规模数据处理特点及稀疏变换的高实时性要求。理论分析和仿真结果表明,所提算法可有效提高无线传感器网络数据稀疏变换算法的顽健性,同时具有良好的实时性。     

视觉传感器网络中基于散度模型的协作式图像压缩机制

结合视觉传感器网络的协同工作特性,提出一种基于散度模型的图像压缩机制.理论分析和实验结果表明,该压缩机制不仅可以减少图像数据量,而且由于压缩后每字节数据所含信息量由各簇内节点的二值量化像素均分,不会引起传输错误在图像中大面积扩散.相比于采用传统的图像压缩算法,随着平均分组丢失率的增高,接收图像峰值信噪比较高.     

基于语义通信的低比特率图像语义编码方法

近年来森林火灾给环境与人类带来巨大的损失,传统基于卫星、无人机技术的探测手段效率低且成本高,而布置在山区等偏远地区的大规模传感器网络因性能受限,难以负载大数据量业务,尤其是图片等可以清楚提供现场周围环境变化的有效信息。针对以上问题,本文将基于深度学习与语义通信技术,提出一种图像语义编码方法,对火灾中传感器拍摄到的图片所包含的语义进行提取、编码、传输,在接收端利用对抗生成网络完成从语义到图片的重建,进而实现比传统图像压缩编码方法更加稳定且具有更高压缩比率,从而减轻了传感器网络的负载,其中,为了避免对复杂无线信道的学习,该方法采用成熟的LDPC码进行信道编码,以保证语义传输的可靠性。仿真结果表明,该方法能够实现比传统BPG图片压缩方法具有更低的压缩比特率和更高的清晰度。     

Perceptual quality‐based image communication service framework for wireless sensor networks

Wireless multimedia sensor networks (WMSNs) have an increasing variety of multimedia‐based applications including image and video transmission. In these types of applications, multimedia sensor nodes should ideally maximize perceptual quality and minimize energy expenditures in communication. For the required perceptual quality to be obtained, quality‐aware routing is a key research area in WMSNs. However, mapping the system parameters to the end user's perceptual quality‐of‐service measures is a challenging task because of incomplete identification metrics. Unfortunately, unless disputable assumptions and simplifications are made, optimal routing algorithm is not tractable. In this paper, we propose a novel image transmission framework to optimize both perceptual quality and energy expenditure in WMSNs. Our framework aims to provide acceptable perceptual quality at the end user by using an analytical distortion prediction model that is able to predict the image distortion resulting from any given error pattern. The innovation of the proposed scheme lies in the combined use of a content‐aware packet prioritization with an energy‐aware and quality‐aware routing protocol, named as image quality‐aware routing. Additionally, it does not only propose an energy‐efficient route selection policy but also manages the network load according to the energy residues of nodes, thus leading to a great energy economy. The results reveal that the framework is capable of identifying true metrics for mapping required image quality to network parameters. Copyright © 2011 John Wiley & Sons, Ltd.     

Image coding using lapped biorthogonal transform

The wireless sensor network utilizes image compression algorithms like JPEG, JPEG2000, and SPIHT for image transmission with high coding efficiency. During compression, discrete cosine transform (DCT)–based JPEG has blocking artifacts at low bit-rates. But this effect is reduced by discrete wavelet transform (DWT)–based JPEG2000 and SPIHT algorithm but it possess high computational complexity. This paper proposes an efficient lapped biorthogonal transform (LBT)–based low-complexity zerotree codec (LZC), an entropy coder for image coding algorithm to achieve high compression. The LBT-LZC algorithm yields high compression, better visual quality with low computational complexity. The performance of the proposed method is compared with other popular coding schemes based on LBT, DCT and wavelet transforms. The simulation results reveal that the proposed algorithm reduces the blocking artifacts and achieves high compression. Besides, it is analyzed for noise resilience.     

基于改进PSO的WMSNs覆盖增强算法

对无线多媒体传感器网络(WMSNs)的覆盖增强问题进行了研究.在WMSNs网络中,视频、图像节点的视角范围有限,只能监控周围的部分区域.由于节点数量众多、部署方式受限等原因,网络中往往存在大量的监测重叠与监控盲区,需要对各节点的感知方向进行优化,以提高网络的监控质量.文中基于有向感知模型,提出了一种覆盖增强算法MCE.MCE对各节点的感知方向进行调整,并使用了改进的PSO算法来计算求解.仿真实验表明,MCE算法能够有效地提高网络的覆盖率.     

Energy efficient distributed steganography for secure communication in wireless multimedia sensor networks

A secure communication mechanism is necessary in the applications of Wireless Multimedia Sensor Networks (WMSNs), which is more vulnerable to security attacks due to the presence of multimedia data. Additionally, given the limited technological resources (in term of energy, computation, bandwidth, and storage) of sensor nodes, security and privacy policies have to be combined with energy-aware algorithms and distributed processing of multimedia contents in WMSNs. To solve these problems in this paper, an energy efficient distributed steganography scheme, which combines steganography technique with the concept of distributed computing, is proposed for secure communication in WMSNs. The simulation results show that the proposed method can achieve considerable energy efficiency while assuring the communication security simultaneously.     

Efficient Hardware-Based Image Compression Schemes for Wireless Sensor Networks: A Survey

Multidimensional sensors, such as digital camera sensors in the visual sensor networks VSNs generate a huge amount of information compared with the scalar sensors in the wireless sensor networks WSNs. Processing and transmitting such data from low power sensor nodes is a challenging issue through their limited computational and restricted bandwidth requirements in a hardware constrained environment. Source coding can be used to reduce the size of vision data collected by the sensor nodes before sending it to its destination. With image compression, a more efficient method of processing and transmission can be obtained by removing the redundant information from the captured image raw data. In this paper, a survey of the main types of the conventional state of the art image compression standards such as JPEG and JPEG2000 is provided. A literature review of their advantages and shortcomings of the application of these algorithms in the VSN hardware environment is specified. Moreover, the main factors influencing the design of compression algorithms in the context of VSN are presented. The selected compression algorithm may have some hardware-oriented properties such as; simplicity in coding, low memory need, low computational load, and high-compression rate. In this survey paper, an energy efficient hardware based image compression is highly requested to counter the severe hardware constraints in the WSNs.     

QoS in Wireless Multimedia Sensor Networks: A Layered and Cross-Layered Approach

The emergence of wireless multimedia sensor networks (WMSN) has given birth to several civilian as well as defense applications. Some of the interesting applications employing low cost sensor nodes to manipulate rich multimedia content include traffic monitoring, border surveillance, smart homes, environment and habitat monitoring. Unlike the traditional sensor networks which are aimed at maximizing network lifetime by decreasing energy utilization, the main objective of WMSNs is optimized delivery of multimedia content along with energy efficiency. Multimedia communications in WMSNs, has stringent delay and high bandwidth requirement as compared to scalar data transfer in WSNs. Fulfilling these constraints in resource and energy constrained WMSNs is a huge challenge. In WMSNs, each layer of the protocol stack is responsible and fully involved in providing QoS guarantees. There is a need for new schemes at each layer of the protocol stack- from advanced coding techniques that reduce encoder complexity and achieve maximum compression to dynamic routing and MAC protocols that provide service differentiation and reduce end-to-end latency. In wireless sensor networks, where all layers have dependency on each other, QoS guarantees are possible through the cross layer interaction of different layers. This paper gives an overview of the different existing layered schemes in WMSNs, followed by a discussion on the significance and efficiency gains that can be achieved from cross layer interactions in WMSNs along with the review of the existing cross layer approaches. Finally, we identify the open research issues which have not been adequately addressed so far.     

QMOR: QoS-Aware Multi-sink Opportunistic Routing for Wireless Multimedia Sensor Networks

The energy efficiency and quality of service (QoS) provisioning of wireless multimedia sensor networks (WMSNs) are two major issues that impact the application of such networks. Recent studies demonstrate that network performance can be greatly improved by involving multiple sinks. However, mainstream WMSN routing protocols are generally designed to account for a single sink. This paper proposes a QoS-aware multi-sink opportunistic routing (QMOR) to efficiently deliver multimedia information under QoS constraints for WMSNs. We begin with an optimal nodes selection problem to reduce redundant multimedia data. Then, we focus on selecting and prioritizing forwarder list to enhance transmission efficiency. Finally, the multi-sink-aware operations are integrated into an optimization opportunistic routing framework, with an objective to minimize energy consumption subject to delay and reliability constraints. Our simulation results demonstrate that the QMOR performs better than typical WMSN QoS routing algorithm, in terms of the video transmission quality and energy utilization efficiency.     

Hardware compression scheme based on low complexity arithmetic encoding for low power image transmission over WSNs

Software implementation costs of most algorithms, designed for image compression in wireless sensor networks, do not justify their use to reduce the energy consumption and delay transmission of images. Even though the hardware solution looks to be very attractive for this problem, a specific care should be paid when designing a low power algorithm for image compression and transmission over these systems. The aim of this paper is to present and evaluate a hardware implementation for user-driven image compression scheme designed to respect the energy constraints of image transmission over wireless sensor networks (WSNs). The proposed encoder will be considered as a co-processor for tasks related with image compression and data packetization. In this paper, we discuss both of the hardware architecture and the features of this encoder circuit when prototyped on FPGA (field-programmable gate array) and ASIC (application-specific integrated circuit) circuits.     

Improving resource-constrained IoT device lifetimes by mitigating redundant transmissions across heterogeneous wireless multimedia of things

In Wireless Multimedia Sensor Networks (WMSNs), nodes capable of retrieving video, audio, images, and small scale sensor data, tend to generate immense traffic of various types. The energy-efficient transmission of such a vast amount of heterogeneous multimedia content while simultaneously ensuring the quality of service and optimal energy consumption is indispensable. Therefore, we propose a Power-Efficient Wireless Multimedia of Things (PE-WMoT), a robust and energy-efficient cluster-based mechanism to improve the overall lifetime of WMSNs. In a PE-WMoT, nodes declare themselves Cluster Heads (CHs) based on available resources. Once cluster formation and CH declaration processes are completed, the Sub-Cluster (SC) formation process triggers, in which application base nodes within close vicinity of each other organize themselves under the administration of a Sub-Cluster Head (SCH). The SCH gathers data from member nodes, removes redundancies, and forwards miniaturized data to its respective CH. PE-WMoT adopts a fuzzy-based technique named the analytical hierarchical process, which enables CHs to select an optimal SCH among available SCs. A PE-WMoT also devises a robust scheduling mechanism between CH, SCH, and child nodes to enable collision-free data transmission. Simulation results revealed that a PE-WMoT significantly reduces the number of redundant packet transmissions, improves energy consumption of the network, and effectively increases network throughput.     

Joint power control and rate adaptation in wireless sensor networks

Wireless sensor networks (WSNs) are energy-constrained, as a result, energy allocation and data transmission on sensor nodes are always considered together. However, current approaches ignore the multiple-hop nature of sensor networks, which results in the lack of modeling energy consumption in data relaying process. In this paper, we illustrate the importance of this issue and formulate the data sensing and transmission in WSNs as a network utility maximization (NUM) problem. A price-based distributed algorithm is proposed to solve this NUM problem, and it can stimulate the cooperation of power control and rate adaptation among the nodes along the data relaying path. Considering the time-varying wireless environment in WSNs, the stability of the proposed algorithm is studied by convergence analysis under stochastic perturbations. Numerical results show that the proposed algorithm converges to the optimal energy allocation and data transmission.