Improved Multi-Path Routing for QoS on MANET

A Mobile Ad hoc NETwork(MANET)is a self-configuring network that is not reliant on infrastructure.This paper introduces a new multipath routing method based on the Multi-Hop Routing(MHR)technique.MHR is the consecutive selection of suitable relay nodes to send information across nodes that are not within direct range of each other.Failing to ensure good MHR leads to several negative consequences,ultimately causing unsuccessful data transmission in a MANET.This research work consists of three portions.The first to attempt to propose an efficient MHR protocol is the design of Priority Based Dynamic Routing(PBDR)to adapt to the dynamic MANET environment by reducing Node Link Failures(NLF)in the network.This is achieved by dynamically considering a node’s mobility parameters like relative velocity and link duration,which enable the next-hop selection.This method works more efficiently than the traditional protocols.Then the second stage is the Improved Multi-Path Dynamic Routing(IMPDR).The enhancement is mainly focused on further improving the Quality of Service(QoS)in MANETs by introducing a QoS timer at every node to help in the QoS routing of MANETs.Since QoS is the most vital metric that assesses a protocol,its dynamic estimation has improved network performance considerably.This method uses distance,linkability,trust,and QoS as the four parameters for the next-hop selection.IMPDR is compared against traditional routing protocols.The Network Simulator-2(NS2)is used to conduct a simulation analysis of the protocols under consideration.The proposed tests are assessed for the Packet Delivery Ratio(PDR),Packet Loss Rate(PLR),End-to-End Delay(EED),and Network Throughput(NT).

Multi-Path Attention Inverse Discrimination Network for Offline Signature Verification

Signature verification,which is a method to distinguish the authenticity of signature images,is a biometric verification technique that can effectively reduce the risk of forged signatures in financial,legal,and other business envir-onments.However,compared with ordinary images,signature images have the following characteristics:First,the strokes are slim,i.e.,there is less effective information.Second,the signature changes slightly with the time,place,and mood of the signer,i.e.,it has high intraclass differences.These challenges lead to the low accuracy of the existing methods based on convolutional neural net-works(CNN).This study proposes an end-to-end multi-path attention inverse dis-crimination network that focuses on the signature stroke parts to extract features by reversing the foreground and background of signature images,which effectively solves the problem of little effective information.To solve the problem of high intraclass variability of signature images,we add multi-path attention modules between discriminative streams and inverse streams to enhance the discriminative features of signature images.Moreover,a multi-path discrimination loss function is proposed,which does not require the feature representation of the samples with the same class label to be infinitely close,as long as the gap between inter-class distance and the intra-class distance is bigger than the set classification threshold,which radically resolves the problem of high intra-class difference of signature images.In addition,this loss can also spur the network to explore the detailed infor-mation on the stroke parts,such as the crossing,thickness,and connection of strokes.We respectively tested on CEDAR,BHSig-Bengali,BHSig-Hindi,and GPDS Synthetic datasets with accuracies of 100%,96.24%,93.86%,and 83.72%,which are more accurate than existing signature verification methods.This is more helpful to the task of signature authentication in justice and finance.

MTSS: multi-path traffic scheduling mechanism based on SDN

Large-scale and diverse businesses based on the cloud computing platform bring the heavy network traffic to cloud data centers.However,the unbalanced workload of cloud data center network easily leads to the network congestion,the low resource utilization rate,the long delay,the low reliability,and the low throughput.In order to improve the utilization efficiency and the quality of services(QoS)of cloud system,especially to solve the problem of network congestion,we propose MTSS,a multi-path traffic scheduling mechanism based on software defined networking(SDN).MTSS utilizes the data flow scheduling flexibility of SDN and the multi-path feature of the fat-tree structure to improve the traffic balance of the cloud data center network.A heuristic traffic balancing algorithm is presented for MTSS,which periodically monitors the network link and dynamically adjusts the traffic on the heavy link to achieve programmable data forwarding and load balancing.The experimental results show that MTSS outperforms equal-cost multi-path protocol(ECMP),by effectively reducing the packet loss rate and delay.In addition,MTSS improves the utilization efficiency,the reliability and the throughput rate of the cloud data center network.

MRBCH: A Multi-Path Routing Protocol Based on Credible Cluster Heads for Wireless Sensor Networks

Wireless sensor networks are widely used for its flexibility, but they also suffer from problems like limited capacity, large node number and vulnerability to security threats. In this paper, we propose a multi-path routing protocol based on the credible cluster heads. The protocol chooses nodes with more energy remained as cluster heads at the cluster head choosing phase, and then authenticates them by the neighbor cluster heads. Using trust mechanisms it creates the credit value, and based on the credit value the multi-path cluster head routing can finally be found. The credit value is created and exchanged among the cluster heads only. Theoretical analysis combined with simulation results demonstrate that this protocol can save the resource, prolong the lifetime, and ensure the security and performance of the network.

Mu-Net:Multi-Path Upsampling Convolution Network for Medical Image Segmentation

Medical image segmentation plays an important role in clinical diagnosis,quantitative analysis,and treatment process.Since 2015,U-Net-based approaches have been widely used formedical image segmentation.The purpose of the U-Net expansive path is to map low-resolution encoder feature maps to full input resolution feature maps.However,the consecutive deconvolution and convolutional operations in the expansive path lead to the loss of some high-level information.More high-level information can make the segmentationmore accurate.In this paper,we propose MU-Net,a novel,multi-path upsampling convolution network to retain more high-level information.The MU-Net mainly consists of three parts:contracting path,skip connection,and multi-expansive paths.The proposed MU-Net architecture is evaluated based on three different medical imaging datasets.Our experiments show that MU-Net improves the segmentation performance of U-Net-based methods on different datasets.At the same time,the computational efficiency is significantly improved by reducing the number of parameters by more than half.

QoS Based and Energy Aware Multi-Path Hierarchical Routing Algorithm in WSNs

In hierarchical networks, nodes are separated to play different roles such as CHs and cluster members. Each CH collects data from the cluster members within its cluster, aggregates the data and then transmits the data to the sink. Each algorithm that is used for packet routing in quality of service (QoS) based applications should be able to establish a tradeoffs between end to end delay parameter and energy consumption. Therefore, enabling QoS applications in sensor networks requires energy and QoS awareness in different layers of the protocol stack. We propose a QoS based and Energy aware Multi-path Hierarchical Routing Algorithm in wireless sensor networks namely QEMH. In this protocol, we try to satisfy the QoS requirements with the minimum energy via hierarchical methods. Our routing protocol includes two phase. In first phase, performs cluster heads election based on two parameters: node residual energy and node distance to sink. In second phase, accomplishes routes discovery using multiple criteria such as residual energy, remaining buffer size, signal-to-noise ratio and distance to sink. When each node detect an event can send data to the CH as single hop and CH to the sink along the paths. We use a weighted traffic allocation strategy to distribute the traffic amongst the available paths to improve the end to end delay and throughput. In this strategy, the CH distributes the traffic between the paths according to the end to end delay of each path. The end to end delay of each path is obtained during the paths discovery phase. QEMH maximizes the network lifetime as load balancing that causes energy consume uniformly throughout the network. Furthermore employs a queuing model to handle both real-time and non-real-time traffic. By means of simulations, we evaluate and compare the performance of our routing protocol with the MCMP and EAP protocols. Simulation results show that our proposed protocol is more efficient than those protocols in providing QoS requirements and minimizing energy consumption.

Performance Study of Multi-Path in VANETs and Their Impact on Routing Protocols

Modeling complicated vehicular traffic behavior and analyzing effects on the communication performance of routing protocols taken by environmental factors have been a challenging task for the past several years. In this paper, we study the performance of multi-path routing protocol. Then, we investigate both multi-path and single-path routing protocol and analyze characteristics such as network connectivity, vehicle-node density etc. To better understand this phenomenon, we use mobility model with different parameters and evaluate the performance of routing protocols (Ad-hoc On-Demand Distance Vector and Ad-hoc On-demand Multipath Distance Vector routing protocols) through NS2 platform. The simulation results show the significance of multi-path on the throughput, loss and average delay of VANETs. The results of this paper may be used to study designing route protocols and applications of VANET.

Emulation of Realistic Multi-Path Propagation Channels inside an Anechoic Chamber for Antenna Diversity Measurements

As antennas are inherently included recommended in Over-The-Air (OTA) testing, it is important to also consider realistic channel models for the multiple-input multiple-output (MIMO) device performance evaluation. This paper aims to emulate realistic multi-Path propagation channels in terms of angles of arrivals (AoA) and cross-polarization ratio (XPR) with Rayleigh fading, inside an anechoic chamber, for antenna diversity measurements. In this purpose, a practical multi-probe anechoic chamber measurement system (MPAC) with 24 probe antennas (SATIMO SG24) has been used. However, the actual configuration of this system is not able to reproduce realistic channels. Therefore, a new method based on the control of the SG24 probes has been developed. At first time, this method has been validated numerically through the comparison of simulated and analytical AoA probability density distributions. At the second time, the performance of an antenna diversity system inside the SG24 has been performed in terms of the correlation coefficient and diversity gain (DG) using an antenna reference system. Simulated and measurements results have shown a good agreement.

Multi-Path Routing and Resource Allocation in Active Network

An algorithm of traffic distribution called active multi\|path routing (AMR) in active network is proposed. AMR adopts multi\|path routing and applies nonlinear optimize approximate method to distribute network traffic among multiple paths. It is combined to bandwidth resource allocation and the congestion restraint mechanism to avoid congestion happening and worsen. So network performance can be improved greatly. The frame of AMR includes adaptive traffic allocation model, the conception of supply bandwidth and its’ allocation model, the principle of congestion restraint and its’ model, and the implement of AMR based on multi\|agents system in active network. Through simulations, AMR has distinct effects on network performance. The results show AMR is a valid traffic regulation algorithm.

Short Baseline Positioning with an Improved Time Reversal Technique in a Multi-path Channel

在水下面的一条多路径隧道的存在极大地减少放系统的短基线的精确性。在这份报纸，到放系统的短基线的一面时间颠倒镜子的申请被调查。时间颠倒镜子技术允许声学的信号更好集中在未知环境，它有效地减少了多路径的扩大声学的信号象一样改进了集中的信号。时间颠倒操作员的 signal-to-noise 比率(SNR ) 极大地增加了并且能被 ensonifying 获得水。这种技术被环境并且因此少些影响对复杂的浅水环境更适用。数字模拟和水池实验被用来表明这种技术的效率。

A new method to estimate DOA in CDMA system in multi-path environment

An algorithm for direction angle of arrival(DOA) estimation and array calibration of signals from multiple mobile users in the CDMA systems and multi-path environment was presented . The main idea is that the algorithm employs code-matched filter and model of the inter-symbol interference and multiple-access interference exactly. The correlation matrices of the received signals before and after code-matched filtering were employed to eliminate the effect of the additive white Gaussian noise, and a new mathematical problem was created, a new maximum likelihood method based on the strong law of large number was derived for DOA estimation and array calibration. Computer simulation results prove that the algorithm is effective.

Novel multi-path routing scheme for UWB Ad hoc network

The routing protocols play an important role for ad hoc networks performance.As some problems with DSR,SMR,and AMR protocols were analyzed,a new routing protocol suitable for UWB Ad hoc networks was proposed in this paper.The new routing protocol utilize an act of orientation of UWB and tries to get sufficient route information and decrease the network load caused by route discovery at the same time.Simulation results show that the routing load of the new protocol is lower and throughput is higher than that of DSR.While the node’s mobility increases,these advantages become more obvious.

Multi-path planning algorithm based on fitness sharing and species evolution

A new algorithm is proposed for underwater vehicles multi-path planning. This algorithm is based on fitness sharing genetic algorithm, clustering and evolution of multiple populations, which can keep the diversity of the solution path, and decrease the operating time because of the independent evolution of each subpopulation. The multi-path planning algorithm is demonstrated by a number of two-dimensional path planning problems. The results show that the multi-path planning algorithm has the following characteristics: high searching capability, rapid convergence and high reliability.

The quickly switching routing algorithm based on multi-path in mobile Ad Hoc networks

This paper proposes a new on-demand multi-alternate-path algorithm, called quickly switching routing algorithm(QSRA). It switches failure routing to an alternate path as quickly as the network can. Like a nervure shape, algorithm QSRA shapes disjoint-alternate-path structure, but is not limited to. It also contains another structure that every primary node has several links to alternate paths. This structure has two advantages, the first one is that primary nodes can select one alternate path immediately when primary routing is failure without going back to source node to re-discover a new routing or choose an alternate path; the second is that it guarantees primary nodes can select another alternate path as quickly as possible once one of alternate paths fails. Strongpoint of algorithm QSRA is reducing frequency of routing re-discovering. Besides, the structure occupies fewer resources than other routing algorithms due to its distributed structure. Simulation shows that QSRA has higher packets received ratio and lower control packet overhead and lower end-to-end delay.

SOPA:Source Routing Based Packet-Level Multi-Path Routing in Data Center Networks

Many "rich-connected" topologies with multiple parallel paths between servers have been proposed for data center networks recently to provide high bisection bandwidth, but it remains challenging to fully utilize the high network capacity by appropriate multi-path routing algorithms. As flow-level path splitting may lead to traffic imbalance between paths due to flow size difference, packet-level path splitting attracts more attention lately, which spreads packets from flows into multiple available paths and significantly improves link utilizations. However, it may cause packet reordering, confusing the TCP congestion control algorithm and lowering the throughput of flows. In this paper, we design a novel packetlevel multi-path routing scheme called SOPA, which leverages Open Flow to perform packet-level path splitting in a roundrobin fashion, and hence significantly mitigates the packet reordering problem and improves the network throughput. Moreover, SOPA leverages the topological feature of data center networks to encode a very small number of switches along the path into the packet header, resulting in very light overhead.Compared with random packet spraying(RPS), Hedera and equal-cost multi-path routing(ECMP), our simulations demonstrate that SOPA achieves 29.87%, 50.41% and 77.74% higher network throughput respectively under permutation workload, and reduces average data transfer completion time by53.65%, 343.31% and 348.25% respectively under production workload.

An Efficient CSI Feedback Scheme for Dual-Polarized MIMO Systems Using Layered Multi-Paths Information

Massive MIMO is one of the enabling technologies for beyond 4G and 5G systems due to its ability to provide beamforming gain and reduce interference Dual-polarized antenna is widely adopted to accommodate a large number of antenna elements in limited space. However,current CSI(channel state information)feedback schemes developed in LTE for conventional MIMO systems are not efficient enough for massive MIMO systems since the overhead increases almost linearly with the number of antenna. Moreover,the codebook for massive MIMO will be huge and difficult to design with the LTE methodology. This paper proposes a novel CSI feedback scheme named layered Multi-paths Information based CSI Feedback(LMPIF),which can achieve higher spectrum efficiency for dual-polarized antenna system with low feedback overhead. The MIMO channel is decomposed into long term components(multipath directions and amplitudes)and short term components(multipath phases). The relationship between the two components and the optimal precoder is derived in closed form. To reduce the overhead,different granularities in feedback time have been applied for the long term components and short term componentsLink and system level simulation results prove that LMPIF can improve performance considerably with low CSI feedback overhead.

基于路径相似表与个体迁移策略的多路径覆盖测试

将遗传算法用于多路径覆盖测试中是个研究热点,在新旧种群迭代过程中,旧种群中可能包含其他子种群的优秀个体,这部分个体未被充分利用,造成资源浪费;同时,种群中的个体数会远大于可达路径数,而每个个体都会经过某一条可达路径,这样会有多个个体经过同一条路径,导致重复计算个体与目标路径的相似度。基于此,提出结合路径相似表与个体迁移的多路径覆盖测试方法以提高测试效率。通过路径相似表存储已计算得到的路径相似度值,避免该值被重复计算,减少测试时间。在进化过程中,将个体路径与其他目标路径进行比较,若相似度达到阈值,则将此优秀个体迁移至该路径对应的子种群中,提高个体利用率并减少进化代数。由实验可知,该方法与其他六种同类经典方法在八个程序上的平均生成时间降低最高达44.64%,最低为2.64%,平均进化代数降低最高达35.08%,最低为6.13%,故该方法有效地提高了测试效率。

基于Pareto蚁群算法的双目标路径规划研究

针对复杂建筑环境人员应急疏散单一路径不能满足火灾环境变化需求的问题,基于改进蚁群算法,结合Pareto双目标解集思想,提出一种组合优化解集的双目标蚁群算法,通过排序优化的思想,实现人员多路径动态疏散规划。在构造Pareto解集的阶段协同考虑疏散路径长度以及火灾风险程度2个优化目标,计算各个解之间的支配关系。利用排序优化蚁群算法的正反馈机制将各组解的信息素按一定比例作为最优路径信息素的积累,加快解集的寻找。最后将其与传统双目标蚁群算法相比较,结果表明:优化后的双目标算法更加适合复杂建筑人员疏散路径规划问题,在寻找多组满足要求解的同时展示目标之间的利弊关系,供决策者选择合适的路径,提高疏散效率。

天线整流罩对GNSS观测值与定位精度影响研究

当前大部分城市为保护卫星连续运行参考站(CORS)系统基准站天线安装了整流罩,但天线整流罩对观测值以及基准站坐标影响的研究仍显不足。为解决基于广州CORS(GZCORS)的网络RTK高程测量存在较大偏差的问题,基于2016—2021年观测站数据,以及拆除基准站天线罩前后的观测数据质量与定位效果相关分析,对天线整流罩对GNSS观测值与高程定位精度的影响进行了深入探究,并分别进行了静态仿动态和城市车载动态定位测试验证。研究结果显示,天线整流罩在一定程度上会增加原始观测值的多路径效应影响,降低约10%的数据可用率,并对基准站高程定位结果产生1~14 cm的系统性偏差,进而影响用户RTK高程定位效果。定位结果显示,拆除基准站天线罩后,基于GZCORS的RTK水平定位均方根误差(RMS)为1 cm左右,高程定位精度RMS为2 cm左右;城市场景下车辆动态定位精度RMS为15~20 cm,满足车道级定位性能。