基于DF中继协作的车联网安全传输性能研究

5G时代的到来加快了以车路协同为核心的车联网技术的发展脚步。高效，可靠，安全的通信质量将是实现智能交通管理系统，完善智慧出行的基本要求。因此，针对存在信息窃取者的车联网中继协作传输场景，利用机会式中继选择策略与最大比合并技术设计了直接传输链路与多跳中继转发链路共存的安全传输方案，旨在提高信息传输的可靠性及安全性。同时，在获得信道概率密度函数及累积分布函数的基础上，利用全概率公式等方法推导出基于DF(Decode-Forward)中继协作传输的车联网系统安全中断概率的闭合表达式，其中涉及的信息传输信道均服从Nakagami-m分布，提高了理论推导的难度。最终的仿真实验证实了理论推导的准确性及本方案的可行性。      

Reliable and infrastructure-independent routing for the internet of vehicles

The Internet of Vehicles (IoV) is a new framework for intelligent transportation systems. One of its goals is to improve safety and increase the quality of service for passengers. Topology changes in IoV present significant challenges to the function of safety applications. Most routing algorithms offer their solution, independent of infrastructure or based exclusively on infrastructure. Although the lack of access to roadside units disrupts infrastructure-based algorithms, methods that do not use infrastructure will also not enjoy the benefits of high-speed data transmission. This research proposes the reliable and infrastructure-independent routing (RIIR) routing algorithm to increase the reliability of real-time routing in the IoV. The RIIR, in addition to simultaneous covering capability to use intelligent infrastructure for accelerating data transmission and flexibility in conditions of lack of access to infrastructure, by introducing three new criteria entitled “history of vehicle movement,” “conformity of vehicle speed with the harmonic speed average of nearby vehicles,” and “number of reliable neighbors,” scores vehicles and then selects the most suitable vehicles as route members. The RIIR measures the conformity of the previous presence of vehicles on the current route and the stability of their link with adjacent vehicles. Furthermore, it prevents congestion by halting the spread of route request messages at intersections not leading to the destination. The efficiency of the RIIR has been theoretically proven, and extensive simulations with multiple scenarios in SUMO and NS3 show the superiority of the RIIR in increasing the packet delivery rate and reducing route failure, average delay, and control overhead.     

Environment-Driven Opportunity Forwarding Cross-Layer Optimization for Ubiquitous Wireless Networks

In this paper, an environment-driven cross-layer optimization scheme is proposed to maximize packet forwarding efficiency. The proposed algorithm is aimed to improve the performance of location-based routing protocol in respect of greedy forwarding and avoid void regions for ubiquitous wireless networks. In greedy forwarding mode, we use a new routing metric IAPS which can estimate the forwarding distance, link quality and the difficulty of channel access during the process of the next hop node selection. When the packet forwarding comes into a local minimum, the proposed scheme uses an opportunistic forwarding method based on competitive advantage to bypass the void regions. NS2 simulation results indicate that the proposed algorithm can improve network resource utilization and the average throughput, and reduce congestion loss rate of wireless multi-hop network comparison with existing GPSR algorithm.     

基于D2D通信系统中的一种跨层中继选择算法

在D2D通信系统与蜂窝网络共存的场景下,引入中继节点可有效提高D2D链路的吞吐量和D2D用户对蜂窝用户的干扰。文中基于译码转发模式,结合跨层协作通信的思想,提出了一种基于物理层和数据链路层的跨层中继选择算法。该算法结合物理层的信道状态信息和数据链路层的队列状态信息,两个参数进行最优中继节点的选择。并最终通过仿真验证表明,基于跨层中继选择算法可提高通信系统的吞吐量,同时降低了通信系统的平均时延和数据包错误率。     

DABPR: a large-scale internet of things-based data aggregation back pressure routing for disaster management

In this paper, we propose a data aggregation back pressure routing (DABPR) scheme, which aims to simultaneously aggregate overlapping routes for efficient data transmission and prolong the lifetime of the network. The DABPR routing algorithm is structured into five phases in which event data is sent from the event areas to the sink nodes. These include cluster-head selection, maximization of event detection reliability, data aggregation, scheduling, and route selection with multi attributes decision making metrics phases. The scheme performs data aggregation on redundant data at relay nodes in order to decrease both the size and rate of message exchanges to minimize communication overhead and energy consumption. The proposed scheme is assessed in terms of packet delivery, network lifetime, ratio, energy consumption, and throughput, and compared with two other well-known protocols, namely “information-fusion-based role assignment (InFRA)” and “data routing for in-network aggregation (DRINA)”, which intrinsically are cluster and tree-based routing schemes designed to improve data aggregation efficiency by maximizing the overlapping routes. Meticulous analysis of the simulated data showed that DABPR achieved overall superior proficiency and more reliable performance in all the evaluated performance metrics, above the others. The proposed DABPR routing scheme outperformed its counterparts in the average energy consumption metric by 64.78% and 51.41%, packet delivery ratio by 28.76% and 16.89% and network lifetime by 42.72% and 20.76% compared with InFRA and DRINA, respectively.

     

一种环境感知的无线Mesh网络自适应QoS路径选择算法

本文针对如何改善无线多跳Mesh网络的服务质量,满足无线多媒体业务对数据传输的带宽、时延、抖动的要求等问题,研究了一种基于无线信道状态和链路质量统计的MAC层最大重传次数的自适应调整算法。该算法通过对无线Mesh网络的无线信道环境的动态感知,利用分层判断法区分无线分组丢失的主要原因是无线差错还是网络拥塞导致,实时调整MAC层的最佳重传次数,降低无线网络中的分组冲突概率。基于链路状态信息的统计和最大重传策略,提出了一种启发式的基于环境感知的QoS路由优化机制HEAOR。该算法通过动态感知底层链路状态信息,利用灰色关联分析法自适应选择最优路径,在不增加系统复杂度的基础上,减少链路误判概率,提高传输效率。NS2仿真结果表明,HEAOR算法能有效减少重路由次数,降低链路失效概率,提高网络的平均吞吐率。本文提出的方法不仅能够优化MAC层的重传,而且通过发现跨层设计的优化参数实现对路径的优化选择。      

基于路径分段的MANET自适应多径路由协议

采用多径路由机制能够有效保证Ad hoc网络数据包传输成功概率,提高网络可靠性。该文在路径数量分析的基础上,根据分组丢弃概率门限判决方法,提出了基于路径分段的自适应多径路由协议。节点采用预先设定的门限值判定链路状态,并且根据网络当前的拓扑状态自适应地选择中继节点,建立路径分段的多径路由。仿真结果表明,该机制在合理利用网络资源的同时能够有效保障数据包的可靠传输,更加适用于状态时变的Ad hoc网络。     

层次分析法在ZigBee网络语音通信中的应用研究

在自组织网络语音通信中,针对音频传输中存在的延时、丢包等主要问题,在ZigBee网络路由的基础上建立层次分析法评价模型,设计了一种音频传输路由算法AHP-RP。通过分析路径链路质量、音频负载值、路径存活时间和路径长度等因素对音频质量的影响,构建以网络的4个因素为因子的比较矩阵,选择最优传输路径。仿真及实际通信平台验证表明,该算法能有效地适应网络状态,明显改善了语音通话质量。     

MIMO多中继辅助通信中基于最优功率分配的路由选择算法

考虑多个多天线中继站辅助的通信网,各中继站工作于放大转发(AF)模式,本文针对两跳半双工中继信道,提出一种基于最优功率分配的多天线路由选择算法。在总功率约束条件下,首先实现基站与中继间的最优功率分配,然后基于多天线中继模式,选出接收信噪比最大的一个中继进行传输。当功率完全分配给基站时,由于未使用中继传输,等价于选择一跳路由。与不进行中继选择的全工作模式相比,该算法不仅能达到满分集度,而且具有更好的中断概率性能和更大的系统容量。仿真结果表明,本文方法以较小的计算复杂度,使系统获得了较大的性能增益,并对于存在路径损耗的实用场景,该算法的性能优势仍然存在。      

无人机短包通信中基于NOMA传输的安全性能分析

针对物联网（IoT）通信的低延时需求,为了保证数据传输的灵活性,本文构建一种基于短包传输的无人机（UAV）通信网络。由于非正交多址接入（NOMA）技术能够增加可服务的地面用户数量,故将该技术应用到无人机短包通信（UAV-SPC）系统中可以解决多用户的安全传输问题。与正交多址（OMA）技术相比,NOMA可有效提高用户接入公平性和频谱利用率,因此被广泛用于下行链路的通信传输。为解决复杂的安全传输问题,首先证明在功率和译码错误率约束的条件下,分别存在最优的功率分配,数据传输包长和系统传输比特数使目标用户的平均安全吞吐量最大。在此基础上,通过本文所提算法得到安全传输问题的优化解。实验结果验证了该算法的稳定性和可行性。此外,与基准方案相比,本文所提方案可有效降低短包传输的通信时延,提高系统中目标用户的平均安全吞吐量。     

无线网络中基于DSDV的最大化吞吐量的协作路由算法

为最大化无线自组织网络的吞吐量,提出一种自适应的协作路由算法。在算法中,协作分集技术与路由选择相结合,通过在路由的每一跳选择最佳的中继节点协作发送节点传输信息来改善网络吞吐量。首先通过目的序列距离矢量路由协议（DSDV）初步建立最短路由路径,在每条链路的发送节点和接收节点根据邻节点表选出公共邻居节点,建立候选中继集合;进一步,每一跳根据链路吞吐量,在候选中继集合中自适应选择最多两个中继来协助发送节点进行传输,并根据选出的中继节点数动态分配节点发射功率。在保证系统发射功率一定的情况下,最大化网络吞吐量。仿真结果表明,在相同的发射功率下,相对于非协作路由DSDV算法,采用固定数量中继的协作路由算法提高了整个网络的吞吐量,而自适应的协作路由算法可进一步提高吞吐量;同时仿真了网络吞吐量与网络规模和节点最大移动速度的变化关系。      

低轨卫星网络的航点分段路由及业务性能分析

提出一种基于卫星航点的分段路由（waypoint-segmentrouting,WSR）算法，WSR算法以可预测的卫星网络拓扑运动周期为基础，根据卫星节点链路状态确定卫星航点的位置；利用分段路由灵活规划分组传输路径的机制，提前响应网络拓扑变化，计算得到一条不受网络拓扑快照切换影响的传输路径。基于NS-3仿真平台进行仿真实验，设置源节点与目标节点在反向缝同侧与不同侧两种场景，选取优化链路状态路由（optimized link state routing,OLSR）算法和最短路径算法与WSR进行时延抖动与分组丢失率的对比分析。实验证明WSR与OLSR相比，两种场景下最大时延抖动分别降低46 ms与126 ms，分组丢失率分别降低30%和21%，并且能够解决拓扑快照切换导致分组传输路径中断的问题。     

一种基于AODV的链路中断预测和最短路径修复机制

在无线Ad Hoc网络中,为了提高链路质量和通信的稳定性,提出一种基于AODV路由协议的链路中断预测和最短路径修复机制(LIFSR-AODV).通过检测网络中的链接质量,预测和避免链路中断的发生,降低了本地修复过程中控制包的开销和传输延迟.同时,在修复过程中能够通过删除链路中的多余节点来缩短路径长度.通过在IEEE 802.15.4 Matlab模拟器下仿真,验证此路由机制能够提高AODV路由协议的性能和链路的稳定性.     

LRP: Link quality‐aware queue‐based spectral clustering routing protocol for underwater acoustic sensor networks

Recently, underwater acoustic sensor networks (UASNs) have been considered as a promising approach for monitoring and exploring the oceans in lieu of traditional underwater wireline instruments. As a result, a broad range of applications exists ranging from oil industry to aquaculture and includes oceanographic data collection, disaster prevention, offshore exploration, assisted navigation, tactical surveillance, and pollution monitoring. However, the unique characteristics of underwater acoustic communication channels, such as high bit error rate, limited bandwidth, and variable delay, lead to a large number of packet drops, low throughput, and significant waste of energy because of packets retransmission in these applications. Hence, designing an efficient and reliable data communication protocol between sensor nodes and the sink is crucial for successful data transmission in underwater applications. Accordingly, this paper is intended to introduce a novel nature‐inspired evolutionary link quality‐aware queue‐based spectral clustering routing protocol for UASN‐based underwater applications. Because of its distributed nature, link quality‐aware queue‐based spectral clustering routing protocol successfully distributes network data traffic load evenly in harsh underwater environments and avoids hotspot problems that occur near the sink. In addition, because of its double check mechanism for signal to noise ratio and Euclidean distance, it adopts opportunistically and provides reliable dynamic cluster‐based routing architecture in the entire network. To sum up, the proposed approach successfully finds the best forwarding relay node for data transmission and avoids path loops and packet losses in both sparse and densely deployed UASNs. Our experimental results obtained in a set of extensive simulation studies verify that the proposed protocol performs better than the existing routing protocols in terms of data delivery ratio, overall network throughput, end‐to‐end delay, and energy efficiency.     

能量收集多跳D2D无线传感网络中的中继选择算法

针对无线功率传输技术的能量收集效率有限造成信噪比下降进而引发通信中断率增加的问题,在能量收集多跳D2D(Device to Device)无线传感网络中,提出一种基于改进K-means聚类的中继选择方法。首先,推导得到能量收集下的信噪比因子,使其作为K-means聚类特征。然后,利用最小欧氏距离原则得到距离聚类中心最近的实际节点的位置。最后,根据距离重排序得到中继节点,形成从源节点到目的节点的通信链路。仿真实验结果表明,相比最短路径算法和随机中继协作方案,所提出的改进算法链路信噪比更大,能够减小通信中断率,具有更好的中继性能。     

车联网中基于动态传输距离的多跳稳定路由

数据传输是车联网(VANETs)实现交通安全的基础。然而,车辆的移动、信号传输的衰减以及彼此间的干扰对链路的可靠性均有影响。为此,提出基于动态传输距离的多跳稳定(DTMS)路由。DTMS路由在选择下一跳转发节点时,考虑到因衰减而导致的传输距离的变小,先估计车辆动态传输距离,再依据动态传输距离估计链路的连通时间以及距离因素,然后,计算邻居节点的权重,最后,基于节点权重值设置定时器,进而竞争产生下一跳转发节点。仿真结果表明,提出的DTMS路由有效地提高了数据包传输成功率。     

Stability-based routing,link scheduling and channel assignment in cognitive radio mobile ad-hoc networks

One fundamental issue in cognitive radio mobile ad hoc networks (CR-MANETs) is the selection of a stable path between any source and destination node to reduce the end-to-end delay and energy consumption arisen from route reconstruction. In this way, we analyse the link stability by calculating the link life time that is dependent on failures caused by secondary users’ (SUs) movements and primary users’ (PUs) activities. We propose a joint stability-based routing, link scheduling and channel assignment (SRLC) algorithm in CR-MANETs, which is benefited from considering the link life time, amount of interference imposed on PUs and energy consumption. The proposed algorithm selects a frequency channel/time slot in a way that channel utilization and previous behaviours of SUs and PUs, are taken into account. In the proposed SRLC, the concept of load balancing is applied by avoiding to route packets through SUs with insufficient energy. The effectiveness of the proposed algorithm is verified by evaluating the aggregate interference energy, end-to-end delay, goodput and the energy usage per packet transmission under three different scenarios. The results show our proposed scheme finds better routes compared to the recently proposed joint stable routing and channel assignment protocol.

     

一种新的GEO/LEO双层星座路由算法

针对多层卫星星座网络的复杂通信环境和特殊应用背景,提出一种新的基于优先级的星上分布式路由算法( PDRA)。 PDRA算法采用新的分层管理策略,根据信息重要程度设置优先级,在拓扑快照起始时刻进行路由计算与更新,信息传输过程中采用拥塞回避策略。理论分析和仿真验证表明,PDRA算法与现有典型卫星星座网络路由算法相比性能优越,能够很好地利用GEO/LEO双层星座特点,有较低的数据丢包率和较高的吞吐量,可有效避免链路拥塞,并能保证重要信息实时可靠传输。     

民航空地通信中的多链路数据分配算法

针对民航空地通信数据丢失率高、吞吐量低问题,提出了一种基于丢包感知负载均衡(Packet Loss-Aware Load Balancing)的分配算法。在空地多链路通信中,每条链路的数据损失率随着链路状态与传输环境等情况实时变化。该算法通过控制每次空地通信中数据流的分割比率,动态分配给每条链路不同大小的数据流,使每条链路的传输损失率趋于相近,提高了空地通信系统吞吐量并减少了数据传输损失,以应对空地通信中丢包率高与吞吐量低等问题。仿真结果表明,所提算法在数据传输损失率和吞吐量上都优于现有的多链路子流分配算法。