基于运动状态的延迟容忍移动传感器网络数据传输策略

针对延迟容忍移动传感器网络(DTMSN, delay tolerant mobile sensor networks)提出一种基于节点运动状态的数据传输(MSD, motion state-based delivery)策略.MSD使用2个通信频率,传感器节点利用基站在频率f1上的广播信号完成自身运动状态和传输概率的计算,并以此作为利用频率f2进行消息转发的依据.为了提高性能,MSD中利用消息生存时间和自身消息优先传输机制来完成消息队列的管理.仿真结果表明,与现有的几种DTMSN数据传输策略相比,MSD能够以较低的通信开销和传输延迟达到较高的数据传输成功率.     

基于网络编码的无线多播速率选择机制

在无线多播通信系统中,每个接收节点与源节点(例如基站)之间的信道状态不相同。因此,过高或者过低的多播速率都会导致较大的传输延迟。而且,信道状态随节点运动而变化,仅仅基于当前信道状态信息(CSI)和接收节点已接收数据状态信息(DSI)的多播速率选择机制无法达到最优性能。该文根据节点CSI和DSI提出了一种基于信道预测多播速率选择算法(MDCP)来最小化传输延迟,并结合网络编码提高数据重传效率。仿真结果表明,与基于最差信道状态节点的多播速率选择算法和没有信道预测的基于最大延迟节点的多播速率选择算法相比,MDCP能够获得10%-20%延迟增益。     

机会网络中基于摆渡节点与簇节点相互协作的路由机制

机会网络是一种不需要在源节点和目的节点之间存在完整路径,利用节点移动带来的相遇机会实现网络通信的延迟容忍自组织网络,它以“存储-携带-处理-转发”的模式进行.为实现互不相交簇间的信息传输,本文设计了一种带阈值的簇移动模型CMMT,并提出了一种基于摆渡（Ferry）节点与簇节点协作的路由算法（CBSW）.该算法减少了冗余的通信和存储开销,以及在Spray阶段簇节点没有遇到目的节点或摆渡节点,进入Wait阶段携带消息的节点采用直接分发方式只向目的节点传输等问题.仿真实验表明,CBSW算法能够增加传输成功率,减少网络开销和传输延迟.     

基于交易构造和转发机制的区块链网络隐蔽通信方法

针对现有存储型区块链网络隐蔽通信方案存在含密交易多副本、永久存储的问题,以及现有时间型方案隐藏容量低的问题,提出了一种基于交易构造和转发机制的区块链网络隐蔽通信方法。首先发送方借助交易构造机制创建无效交易,并将秘密信息嵌入其中,再利用交易转发机制向邻居节点发送无效交易,形成隐蔽通信信道模型,使含密交易在节点间传播且不存于区块链账本中,达到信息隐蔽安全传输的目的。实验结果表明,传输容量高于现有方案,单次通信时间减少至2.5 s。     

基于超级节点的P2P模型副本管理策略

随着计算机和网络技术的迅猛发展,对大容量分布式存储系统的研究已经成为当前热点.在分布式存储系统中,副本技术是一种最为常用的分布式数据管理机制.通过为系统中的文件增加副本,保存冗余的文件数据,可以十分有效地提高文件的可用性和可靠性.提出一种含超级节点的P2P模型,将大量分散的存储节点组织成一个逻辑存储网络.超级节点不仅用于存储"热点"文件的副本,而且还采用RAID技术进行数据备份,以进一步提高系统存储资源利用率和系统可靠性;针对一般节点的惰性,依据文件被查询到的概率,采用方根复制策略进行数据备份,在保证资源下载成功率的同时,进一步提高系统空间利用率.     

态势标绘系统设计分析

通过对态势标绘系统需求的分析,针对矢量符号在标绘系统容易出现延迟、闪烁和态势文件过大不易保存传输2个关键问题进行了深入研究分析,提出了多缓冲绘图机制和序列化存储方法,并设计实现了态势标绘系统。经过试验证明:多缓冲绘图机制能有效地避免海量矢量符号在显示过程中的闪烁和延迟;态势演播中的序列化存储方法,能有效压缩态势文件的大小,方便了态势文件的保存和传输。     

测控通信系统中低延迟视频编码传输方法研究

为降低测控通信系统延迟对无人飞行器性能影响,在深入分析影响测控通信视频编码传输延迟基础上,提出了一种适合于测控通信传输的低时延视频编码传输帧结构。算法引入帧内刷新编码方式将I帧码流平均到其他P帧中,使得压缩后各帧编码码流尽可能得到平均,从而减少编码发送缓冲区延迟;根据slice编码方式的独立性将一帧图像分成多个slice并行编码模式以减少编码处理延迟;同时去除双向预测编码B帧模式以减少帧排序延迟。实验采用新一代HEVC标准进行仿真分析,结果表明算法在不明显降低视频编码质量前提下,使得压缩后各帧码流大小尽可能平均,有效地减少了测控通信系统中视频压缩传输延迟。     

机动通信网智能通信保持技术应用研究

机动通信网具有灵活性高、组网速度快、环境场景多等优势,但是在频繁的移动过程中,其通信状态容易受到地形因素的影响,如节点距离过远、有障碍物阻隔等.针对此问题,提出一种智能通信保持技术,尽可能地使机动通信网中的各个节点保持在视距链路通信中.该技术需要通过大数据采集并存储节点、地形、行进路线等数据,并需要通过机器学习,对采集到的大数据进行算法分析,以得出最佳的机动通信网行进方案.     

一种基于LBT的分布式图像压缩算法

无线多媒体传感器网络(WMSNs)中传感器节点采集的数据量非常大,在传输前需对大数据量的多媒体信息进行压缩处理,但是单节点能源受限,存储、处理能力相对较弱。针对无线多媒体传感器网络应用的高效、低耗能的需求这些问题,在图像压缩双正交重叠变换(LBT)的基础上,文中提出了一种基于此变换的分布式无线多媒体传感器网络图像压缩算法。即基于簇结构,把压缩任务分配给其他节点,通过多个节点相互协作,共同完成图像的压缩编码和传输。实验结果表明,在传感器节点散布不均且较为密集的情况下,该算法在高质量、低复杂度和低功耗等方面都有了很大的性能提高。     

无线传感器网络高精度时间同步机制

无线传感器网络中,发送节点和接收节点间的延时包括发送延迟、访问延迟、传输延迟、传播延迟、接收延迟和接收处理延迟。传统的泛洪式时间同步算法在传感器节点上实现时一般选择在MAC层打时标来避免发送延迟和接收处理延迟。但是由于CC2530节点在发送消息前会进行空闲信道评估,那么信道的访问延迟是不能忽略的。文中提出了一种基于SFD硬件捕获机制的泛洪式时间同步机制,该同步机制避免了访问延迟对时间同步精度的影响,使同步精度保持在微秒级。     

大规模输电线路状态监测传感器网络的周期性低功耗通信技术方案

为了实现输电线路监测的功耗低、寿命长、绿色发展的目的，提出大规模输电线路状态监测传感器网络周期性低功耗通信技术方案。依据网络中传感器网络组网特征以及节点运行状态转换特点，设置睡眠定时器，以周期性运行方式使传感器网络通信节点在初始化、睡眠、激活状态间转换，通信节点在输电线路状态监测数据无传递需求时进入睡眠状态，节省通信功耗；传感器网络汇聚（sink）节点利用梯度创建上行路由，通过源路由的方式创建下行路由，以跳数和剩余能量为依据进行上、下行路由数据分组传递，降低节点功耗，延长通信运行时间。实验显示，大规模输电线路状态监测传感器网络应用该技术方案后，通信功耗明显降低，运行时间明显延长，且不会影响监测传感器网络的数据传输性能，延长了监测传感器网络的使用寿命。     

RESIDENT: a reliable residue number system-based data transmission mechanism for wireless sensor networks

Retransmission is the most common data transmission mechanism in wireless sensor networks, and can improve data transmission reliability via the acknowledgement mechanism. However, the simple acknowledgement retransmission is associated with some negative factors such as data delay, low throughput among others. To overcome the shortcomings of the retransmission mechanism, redundancy coding is introduced to wireless communications, which has been widely applied in 4G communication. Unfortunately, not all redundant erasure codes are suitable for wireless sensor networks, as nodes’ energy, processing power, and storage capacity are all limited. Moreover, we also need to consider data transmission delay. Therefore, to improve data transmission reliability, we must take into account the complexity of algorithm, data transmission delay, node energy consumption, and other factors. In this article, we propose a REliable reSIDuE number system-based data transmission mechanism (RESIDENT) for WSNs, which can improve data transmission reliability via hybrid automatic repeat requests in hop-by-hop scenarios. In order to decrease the complexity of decoding, we present our algorithm and the proof of correctness, and report the performance using extensive set of simulation experiments. Our simulation results show that RESIDENT exhibits a good performance when compared to the previous studies, not only in terms of reliable data transmission, but also in end-to-end delay and energy consumption.     

交通路灯监控系统的无线传感网链状路由算法

在交通路灯监控系统中为节省网络节点能耗和降低数据传输时延,提出一种无线传感网链状路由算法（CRASMS）。该算法根据节点和监控区域的信息将监控区域分成若干个簇区域,在每一个簇区域中依次循环选择某个节点为簇头节点,通过簇头节点和传感节点的通信建立簇内星型网络,最终簇头节点接收传感节点数据,采用数据融合算法降低数据冗余,通过簇头节点间的多跳路由将数据传输到Sink节点并将用户端的指令传输到被控节点。仿真结果表明：CRASMS算法保持了PEGASIS算法在节点能耗方面和LEACH算法在传输时延方面的优点,克服了PEGASIS 算法在传输时延方面和LEACH算法在节点能耗方面的不足,将网络平均节点能耗和平均数据传输时延保持在较低水平。在一定的条件下,CRASMS算法比LEACH和PEGASIS算法更优。     

面向混合业务的无线传感器网络能量有效接入策略

研究了在实时业务和非实时业务同时存在的混合背景下,非实时业务的无线传感器节点自适应侦听和睡眠的动态接入机制。网络节点处于睡眠状态时所需的能量很低,节约了无线传感器网络节点的平均能量消耗;但是,过长的睡眠时间可能使得网络节点错失传输机会。因此,根据信道的使用情况,合理地设定无线传感器网络节点的睡眠时间,能够在网络能量消耗和传输效率之间进行调整,从而最大化无线传感器网络的能量传输效率。首先,利用连续时间 Markov 方法对问题进行建模,并利用基于摄动分析理论对系统模型进行分析,获得求解无线传感器网络能量效率最大化的最优睡眠时间梯度算法。最后通过理论结果和计算机仿真模拟的对比,验证了推荐方法的可行性。     

物联网感知层多路径传输策略研究

多路径数据传输是无线传感器网络亟需解决的一个关键问题.本文针对节点故障、链路失效和外界干扰影响网络稳定性和可靠性,提出一种基于混合蛙跳算法的无线传感器网络多路径传输策略.首先我们详细介绍了蛙跳算法及其原理,之后我们将其应用到无线传感器网络多路径传输策略之中,接着运用混合蛙跳算法对传感网络节点其进行更新、划分、重组以便选择出最优节点建立传输最优路径,提高网络的稳定性和可靠性.通过算法仿真与结果对比提出的算法与AODV、粒子群PSO算法相比,在网络能耗、传输时延、丢包率、连通率和可靠度等方面都具有较好的性能.其中网络能耗比AODV、PSO算法降低了62.5％和35.8％.     

Energy Attentive and Pre-fault Recognize Mechanism for Distributed Wireless Sensor Network Using Fuzzy Logic Approach

Wireless sensor networks (WSNs) have been transforming over recent years with development in the design of smart real-time applications. However, it presents numerous challenges in terms of fault-tolerant communication, low latency, scalability, and transmission efficiency. It is extremely difficult for WSNs to detect runtime faults since they're unaware of the internal processes at work within the sensor node. As a result, valuable sensed information cannot reach its destination and performance starts degrading. Towards this objective, the proposed mechanism applies a novel pre-fault detection mechanism based on a fuzzy rule-based method for multilevel transmission in distributed sensor networks. The proposed mechanism uses a fuzzy rule set to make routing decisions. A fuzzy decision rule set is proposed to perform routing based on the fuzzy fault count status of a node. The proposed mechanism assists in identifying the fault in advance and determining the optimal routing path to save energy and improve network performance. In accordance with the node fault status, the data transmission rate is finalized to prevent further energy consumption. The results demonstrated that the proposed mechanism performed well on judgment evaluation metrics like the energy dissipation ratio, throughput, packet loss rate and communication delay.

     

An energy efficient and QoS aware routing protocol for wireless sensor and actuator networks

Wireless sensor and actuator networks are composed of sensor and actuator nodes interconnected via wireless links. The actuators are responsible for taking prompt decisions and react accordingly to the data gathered by sensor nodes. In order to ensure efficient actions in such networks, we propose a new routing protocol that provides QoS in terms of delay and energy consumption. The network is organized in clusters supervised by CHs (Cluster-Heads), elected according to important metrics, namely the energy capability, the riches of connectivity, which is used to select the CH with high node density, and the accessibility degree regarding all the actuators. The latter metric is the distance in number of hops of sensor nodes relative to the actuator nodes. This metric enhances more the network reliability by reducing the communication delay when alerting the actuator nodes, and hence, reducing the energy consumption. To reach efficiently the actuator nodes, we design a delay and energy sensitive routing protocol based on-demand routing approach. Our protocol incurs less delay and is energy efficient. We perform an evaluation of our approach through simulations. The obtained results show out performance of our approach while providing effective gain in terms of communication delay and energy consumption.     

LSAPSP: Load distribution‐based slot allocation and path establishment using optimized substance particle selection in sensor networks

Sensor node energy conservation is the primary design parameters in wireless sensor networks (WSNs). Energy efficiency in sensor networks directly prolongs the network lifetime. In the process of route discovery, each node cooperates to forward the data to the base station using multi‐hop routing. But, the nodes nearer to the base station are loaded more than the other nodes that lead to network portioning, packet loss and delay as a result nodes may completely loss its energy during the routing process. To rectify these issues, path establishment considers optimized substance particle selection, load distribution, and an efficient slot allocation scheme for data transmission between the sensor nodes in this paper. The selection of forwarders and conscious multi‐hop path is selected based on the route cost value that is derived directly by taking energy, node degree and distance as crucial metrics. Load distribution based slot allocation method ensures the balance of data traffic and residual energy of the node in areal‐time environment. The proposed LSAPSP simulation results show that our algorithm not only can balance the real‐time environment load and increase the network lifetime but also meet the needs of packet loss and delay.     

Energy-Efficient Routing Protocol for Wireless Sensor Networks with Static Clustering and Dynamic Structure

Data gathering is an essential operation in wireless sensor networks. For periodic data gathering applications, each sensor node has data that must be sent to a distant base station in a round of communication. Due to the limited battery power of sensor nodes, each sensor node transmitting its sensed data to the base station directly significantly consumes its energy. This work presents a hierarchical ring-based data gathering (HRDG) scheme for dense wireless sensor networks. A hierarchical grid structure is constructed, and only some sensor nodes are elected as grid heads for gathering data, subsequently reducing the total energy consumption per round. Grid heads are then organized into hierarchical rings to decrease the transmission delay of a round. The proposed HRDG scheme focuses on reducing the energy × delay cost in a round of data gathering. Moreover, the energy × delay cost of HRDG is analyzed. Simulation results indicate that the proposed HRDG scheme outperforms other data gathering schemes in terms of the number of rounds, the energy × delay cost and coverage ratio.     

多簇无线传感网的优化生存时间近邻功率控制算法

针对非均匀分布的无线传感网的生存时间问题,提出多簇无线传感网的优化生存时间近邻功率控制(NPCAOL_MC)算法。该算法采用K-means算法确定网络的簇个数和对应每个簇的节点,利用近邻算法评估每个簇的节点密度,确定簇的最优通信距离。结合Friss自由空间模型计算当前簇的最优发送功率。Sink节点广播通知其他节点,如果是同一簇内的节点相互通信,则采用簇最优功率发送数据,否则采用默认最大发送功率发送数据。仿真结果表明,利用NPCAOL_MC算法可以分析整个网络节点的位置信息,采用簇最优发送功率发送数据,从而提高生存时间,并使能耗经济有效。在密度分布不均的无线传感网中,NPCAOL_MC比采用固定发送功率的Ratio_w算法更优。