基于业务区分的无线多媒体传感器网络QoS体系结构

无线多媒体传感器网络（WMSNs）的网络服务质量（QoS）一直是人们关心的核心问题,然而目前WMSNs的QoS保障研究主要针对单个协议层或特定应用场景,缺少系统性的QoS体系框架研究。结合无线传感器网络自身特点,利用图论对网络进行建模。在此基础上,提出一种三层可计算QoS指标体系,并根据各种应用不同QoS需求将应用分为四类,设计出一种基于业务区分的无线多媒体传感器网络QoS体系结构（DQoSAW）。以传输MPEG视频流为例对DQoSAW进行验证,实验结果表明DQoSAW能够显著改进WMSNs的整体性能。     

基于相关性感知的无线视频传感器网络路由协议

无线视频传感器网络（ WVSNs）节点的能量十分有限,为了降低传感器节点的能耗,延长网络生存时间,提出了一种基于相关性感知的视频传感器网络通信协议。首先对当前经典无线视频传感器网络路由协议的不足进行分析;然后从簇首节点的选择、簇的形成、节点感知方向的调整、簇内通信以及簇间通信等几个方面进行改进和优化;最后在Matlab 2012平台进行了仿真对比测试。仿真结果表明：该协议不仅能够延长无线视频传感器网络生命周期,而且提高了监测区域覆盖率。     

一种时延保证的QoS路由协议

针对无线传感器网络中多跳视频传输实时性难以保证以及节点失效造成的传输中断问题,本文在比较分析了考虑时延的路由协议基础上,提出并设计了一种保证时延QoS要求可自我修复的路由协议(Self Repaired and Delay Guarantee Routing Protocol)。该协议选择时延最短的节点作为路由节点,缩短了多跳传输时间;在路由表中增加备选路由节点,当某个路由节点失效时,自动启用备选节点修复路由,节省了路由重新建立的时间,保证了视频传输持续性。仿真结果表明该路由协议能够较好地满足无线传感器网络中多跳视频传输的时延要求。     

无线传感器网络QoS仿真与研究

无线传感器网络在军事和民用领域均具有广阔的应用前景,但由于传感器节点资源的限制,网络能否满足在实际应用中的QoS要求是一个重要问题。本文对无线传感器网络的主要QoS指标进行了介绍,并分别从能量效率、丢包率、吞吐量和传输时延等主要QoS指标对三种典型拓扑结构的无线传感器网络进行了分析;实现了基于NS2的无线传感器网络通用仿真平台,借助此平台对典型拓扑结构的传感器网络主要QoS指标进行了仿真验证和分析,得到了不同拓扑结构对无线传感器网络QoS指标的影响程度。     

无线传感器网络的QoS体系结构

不同于传统互联网,作为涵盖了数据感知、处理和传输的复杂任务型网络,无线传感器网络面向应用的特点给服务质量(QoS)研究带来了许多新的挑战,需要针对QoS体系结构以及QoS指标间复杂关系的系统工作.文中首先提出了无线传感器网络中QoS指标的分层模型以及相应的规范化描述,然后分析了QoS指标的映射关系,最后提出了一个层次化的QpS体系结构,希望为无线传感器网络中QoS保障技术的系统性研究提供参考.     

基于传输的网络视频编码技术研究

视频传输是提高网络视频QoS的一个关键环节。随着视频传榆的广泛应用,基于传输的网络视频编码技术受到越来越多的关注。文章系统的讨论了传统视频编码在传输中的应用,深入研究了MPEG-4视频编码,指出了基于传输的网络视频编码技术的发展前景。     

改进的遗传算法无线视频传感器网络协作路由技术研究

提出了适用于无线视频传感器网络的基于能量感知的跨层交互多路径协作路由技术.该技术首先采用了基于视频传感器节点感知距离的遗传优化算法,预测传输视频数据的能耗和剩余能量,结合无线信道质量和视频编码算法建立一种跨层协同的工作体系,优化节点传输视频数据的能耗、时延和带宽等因素;然后建立应用层、网络层和物理层跨层协同工作体系.仿真实验和数学分析表明,该技术不仅能够较好地满足视频传感器网络应用业务的多样性QoS数据传输性能需求,而且可以充分利用视频传感器网络受限的计算、存储能力和能量等资源.     

基于蚁群优化的多媒体传感器网络实时视频流分发策略

视频流传输是无线多媒体传感器网络的研究热点.本文提出一种基于蚁群优化的实时视频流分发策略AVSD(ACO based video streaming dissemination),分路由建立,节点内部视频数据分发两个阶段.在现有视频编码技术基础上,利用蚁群优化寻找具有不同QoS保障的路径,进行区分优先级的数据分发.仿真结果表明,AVSD策略可有效降低端到端时延,合理利用全网资源,提高网络性能并能够为无线多媒体传感器网络提供较好的视频传输性能.     

嵌入式无线局域网中H. 264视频传输的QoS研究

就H. 264在无线环境中的传输问题展开研究,针对嵌入式特点对现有的视频传输策略进行了改进,在服务这样可以将网络、缓冲和实时性等加以综合考虑,既保证了视频传输的实时性又提供了一定的网络QoS。且经过实验验证,这两种方法都取得了满意的效果。     

语音WSN的QoS路由和准入控制研究

语音无线传感器网络(WSN)数据量大、处理任务复杂,针对其中的服务质量(QoS)保障问题,总结WSN中的QoS路由协议和准入控制的研究进展,认为准入控制可根据网络拓扑结构分为平面准入控制和分簇准入控制,并针对语音无线传感器网络,提出一种将准入控制和QoS路由相结合的方法,从而提高语音传输质量。     

Nonconvex resource control and lifetime optimization in wireless video sensor networks based on chaotic particle swarm optimization

Wireless video sensor networks (WVSNs) have attracted a lot of interest because of the enhancements that they offer to existing wireless sensor networks applications and their numerous potential in other research areas. However, the introduction of video raises new challenges. The transmission of video and imaging data requires both energy efficiency and quality of service (QoS) assurance in order to ensure the efficient use of sensor resources as well as the integrity of the collected information. To this end, this paper proposes a joint power, rate and lifetime management algorithm in WVSNs based on the network utility maximization framework. The optimization problem is always nonconcave, which makes the problem difficult to solve. This paper makes progress in solving this type of optimization problems using particle swarm optimization (PSO). Based on the movement and intelligence of swarms, PSO is a new evolution algorithm to look for the most fertile feeding location. It can solve discontinuous, nonconvex and nonlinear problems efficiently. First, since chaotic mapping enjoys certainty, ergodicity and the stochastic property, the paper introduces chaos mapping into PSO with adaptive inertia weight factor to avoid the disadvantage of original PSO of easily getting to the local optimal solution in the later evolution period and keep the rapid convergence performance. Second, based on the distribution characteristics of the actual network, we decompose the resource control problem into a number of sub-problems using the hierarchical thought, where each user corresponds to a subsystem which is solved using the proposed CPSO3 method. Through the cooperative coevolution theory, these sub-optimization problems interact with each other to obtain the optimum of the system. Numerical examples show that our algorithm can guarantee fast convergence and fairness within a few iterations. Besides, it is demonstrated that our algorithm can solve the nonconvex optimization problems very efficiently.     

Dynamic duty cycle and adaptive contention window based QoS-MAC protocol for wireless multimedia sensor networks

Rapid penetration of small, customized wireless devices and enormous growth of wireless communication technologies has already set the stage for large-scale deployment of wireless sensor networks. While the need to minimize the energy consumption has driven significant researches in wireless sensor networks, offering some precise quality of service (QoS) for multimedia transmission over sensor networks has not received significant attention. However, the emerging new applications like video surveillance, telemedicine and traffic monitoring needs transmission of wireless multimedia over sensor networks. Naturally, offering some better QoS for wireless multimedia over sensor networks raises significant challenges. The network needs to cope up with battery-constraints, while providing improved QoS (end-to-end delay and bandwidth requirement). This calls for a suitable sensory MAC protocol capable of achieving application-specific QoS. In this paper, we have proposed a new QoS-based sensory MAC protocol, which not only adapts to application-oriented QoS, but also attempts to conserve energy without violating QoS-constraints. Performance modeling, analysis and simulation results demonstrate that the proposed protocol is capable of providing lower delay and better throughput, at the cost of reasonable energy consumption, in comparison to other existing sensory MAC protocols.     

A comparative analysis of video codecs for multihop wireless video sensor networks

Wireless video sensor networks (WVSNs) have drawn significant attention in recent years due to the advent of low-cost miniaturized cameras, which makes it feasible to realize large-scale WVSNs for a variety of applications including security surveillance, environmental tracking, and health monitoring. However, the conventional video coding paradigms are not suitable for WVSNs due to resource constraints such as limited computation power, battery energy, and network bandwidth. In this paper, we evaluated and analyzed the performance of video codecs based on emerging video coding paradigms such as distributed video coding and distributed compressive video sensing for multihop WVSNs. The main objective of this work was to provide an insight into the computational (encoding/decoding) complexity, energy consumption, node and network lifetime, processing and memory requirements, and the quality of reconstruction of these video codecs. Based on the findings, this paper also provides some guidelines for the selection of appropriate video codecs for a given WVSN application.     

Reduction in encoding redundancy for overlapped FOVs over wireless visual sensor networks

With an increase in the capabilities of sensors, wireless visual sensor networks (WVSNs) are being researched to perform more complicated tasks as each visual sensor performs video capture, processing and sharing. Because each visual sensor operates by using its own resources including computation and communication under a limited power supply, it is necessary to develop an energy management scheme suitable for WVSNs. In particular, when multiple camera modules of visual sensors are aimed at some regions with different fields of views (FOVs), undesirable power consumption for encoding may occur among distributed visual sensors. Because some overlapped FOVs among captured images give rise to encoding redundancy, this leads to an increase in data quantity and power consumption for the encoding and communication. To resolve this problem, in this paper, we present a novel strategy for lifetime maximization of the WVSN. In order to estimate overlapped FOVs without using complicated procedures such as pattern or object recognition, we propose a geographical model to estimate overlapped FOVs based on location and visual direction. Based on this model, the power-rate-distortion (P-R-D) is determined and used to construct an optimization problem for minimizing the power consumption of each node. Through the proposed scheme, including distributed power allocation and node scheduling under simple information sharing, the network lifetime is maximized. Numerical results demonstrate the validity of the proposed algorithm.     

Ant-based routing for wireless multimedia sensor networks using multiple QoS metrics

In wireless sensor networks, most routing protocols consider energy savings as the main objective and assume data traffic with unconstrained delivery requirements to be a given. However, the introduction of video and imaging sensors unveils additional challenges. The transmission of video and imaging data requires both energy efficiency and QoS assurance (end-to-end delay and packet loss requirements), in order to ensure the efficient use of sensor resources as well as the integrity of the information collected. This paper presents a QoS routing model for Wireless Multimedia Sensor Networks (WMSN). Moreover, based on the traditional ant-based algorithm, an ant-based multi-QoS routing metric (AntSensNet) is proposed. The AntSensNet protocol builds a hierarchical structure on the network before choosing suitable paths to meet various QoS requirements from different kinds of traffic, thus maximizing network utilization, while improving its performance. In addition, AntSensNet is able to use a efficient multi-path video packet scheduling in order to get minimum video distortion transmission. Finally, extensive simulations are conducted to assess the effectiveness of this novel solution and a detailed discussion regarding the effects of different system parameters is provided. Compared to typical routing algorithms in sensor networks and the traditional ant-based algorithm, this new algorithm has better convergence and provides significantly better QoS for multiple types of services in wireless multimedia sensor networks.     

基于认知无线电技术的动态频谱分配方案研究

随着物联网的发展,人们能够更加方便快捷地利用智能终端,随时随地接入到无线网络中进行业务数据传输.然而,激增的移动用户数量和业务的带宽需求,使得无线频谱资源日益稀缺,现有固定式频谱分配方案面临巨大挑战.面向物联网发展,如何满足用户的高移动性和呈爆炸式增长的业务传输需求成为物联网研究的重点.认知无线电技术,一方面允许用户终端自适应感知所处环境的频谱资源空闲信息,为用户营造一个无缝的接入环境,保证用户的高移动性;另一方面通过动态频谱分配有效地解决了频谱资源稀缺和现有授权频谱资源利用率低的问题,为用户的海量数据传输提供保证.作者基于认知无线电技术,提出了一个用户终端和网络端共同参与决策的两级动态频谱分配框架结构,并提出了两级动态频谱分配方案.该方案设计包含:空闲频谱资源排序选择算法和集中式的联合优化匹配算法.通过用户终端和网络端的协同工作,文中所提出的两级动态频谱分配方案能够有效满足用户的高移动性和业务传输服务质量需求,实现空闲频谱资源利用率和频谱间切换概率的联合优化,为移动用户的海量数据传输提供保证.仿真实验结果表明,与传统图匹配方法相比较,该方案能够平均提高全网服务质量有效吞吐量70%,平均降低频谱间切换概率56%.     

一种基于DPSO的无线传感器网络QoS路由算法

针对无线传感器网络中不同业务对服务质量(QoS)的不同需求,提出一种基于离散粒子群优化(DPSO)的无线传感器网络QoS路由(DPSO-QR)算法。算法将路由建立过程抽象为多目标优化过程,以节点间通信的传播损耗、时延、带宽、丢包率为优化目标,利用DPSO算法实现多目标优化,为拥有不同QoS需求的网络业务提供满足其特有需求的优化路由。仿真实验表明:与SAR,EQR算法相比,DPSO-QR算法降低了网络平均端到端时延,减小了丢包率,延长了网络寿命。     

无线多媒体传感器网络图像通信性能分析

对无线视频传感器节点的图像通信活动进行研究,分析了其在资源受限的无线多媒体传感器网络中进行图像编码和传输的性能。对基于DCT和DWT的图像编码与传输的能量消耗和率失真进行建模分析。根据所建立的能量消耗与率失真模型,对有限的能量和传输带宽进行优化分配。根据监测场景的统计信息,调整编码中所使用的参数,以使得能量消耗最小化。仿真实验结果表明,所提出的方法在保证应用所需图像质量的情况,有效地降低了无线传感器节点的数据通信量和计算过程的能耗。     

基于区分服务的无线多媒体传感器网络QoS路由协议*

针对无线多媒体传感器网络数据量大且不同业务传输的QoS约束不同的特点,提出了一种数据融合的区分服务的QoS路由算法（DF-DSQR）。该算法在兴趣泛洪期间建立实时（RT）和尽力而为（BE）业务两类梯度,采用优先级排队模型对两类业务的传输进行分级处理,并采用数据融合转发机制,为RT业务和BE业务提供了保证QoS的路由路径。仿真结果表明,该算法既能保证实时业务低时延的要求,又能保证尽力而为业务的QoS要求,均衡了网络能耗,延长了网络生存期。