A maximum-independent-set-based channel allocation algorithm for multi-channel wireless networks

A channel allocation algorithm based on the maximum independent set is proposed to decrease network conflict and improve network performance. First, a channel allocation model is formulated and a series of the maximum independent sets （MISs） are obtained from a contention graph by the proposed approximation algorithm with low complexity. Then, a weighted contention graph is obtained using the number of contention vertices between two MISs as a weighted value. Links are allocated to channels by the weighted contention graph to minimize conflicts between independent sets. Finally, after channel allocation, each node allocates network interface cards （NICs） to links that are allocated channels according to the queue lengths of NICs. Simulations are conducted to evaluate the proposed algorithm. The results show that the proposed algorithm significantly improves the network throughput and decreases the end to end delay.

Joint channel assignment and cross-layer routing protocol for multi-radio multi-channel Ad Hoc networks

To study multi-radio multi-channel （MR-MC） Ad Hoc networks based on 802.11, an efficient cross-layer routing protocol with the function of joint channel assignment, called joint channel assignment and cross-layer routing （JCACR）, is presented. Firstly, this paper introduces a new concept called channel utilization percentage （CUP）, which is for measuring the contention level of different channels in a node’s neighborhood, and deduces its optimal value for determining whether a channel is overloaded or not. Then, a metric parameter named channel selection metric （CSM） is designed, which actually reffects not only the channel status but also corresponding node’s capacity to seize it. JCACR evaluates channel assignment by CSM, performs a local optimization by assigning each node a channel with the smaller CSM value, and changes the working channel dynamically when the channel is overloaded. Therefore, the network load balancing can be achieved. In addition, simulation shows that, when compared with the protocol of weighted cumulative expected transfer time （WCETT）, the new protocol can improve the network throughput and reduce the end-to-end average delay with fewer overheads.

Joint Link Allocation and Rate Assignment Algorithm for Multi-Channel Wireless Networks

This paper presents a link allocation and rate assignment algorithm for multi-channel wireless networks. The objective is to reduce network con-flicts and guarantee the fairness among links. We first design a new network model. With this net-work model, the multi-channel wireless network is divided into several subnets according to the num-ber of channels. Based on this, we present a link allocation algorithm with time complexity O（l^2）to al-locate all links to subnets. This link allocation algo-rithm adopts conflict matrix to minimize the network contention factor. After all links are allocated to subnets, the rate assignment algorithm to maximize a fairness utility in each subnet is presented. The rate assignment algorithm adopts a near-optirml al-gorithm based on dual decomposition and realizes in a distributed way. Simulation results demonstrate that, compared with IEEE 802.11b and slotted see-ded channel hopping algorithm, our algorithm de-creases network conflicts and improves the net-work throughput significantly.

Performance Analysis of Multi-Channel CR Enabled IoT Network with Better Energy Harvesting

Wireless Sensor Networks(WSNs)can be termed as an autoconfigured and infrastructure-less wireless networks to monitor physical or environmental conditions,such as temperature,sound,vibration,pressure and motion etc.WSNs may comprise thousands of Internet of Things(IoT)devices to sense and collect data from its surrounding,process the data and take an automated and mechanized decision.On the other side the proliferation of these devices will soon cause radio spectrum shortage.So,to facilitate these networks,we integrate Cognitive Radio(CR)functionality in these networks.CR can sense the unutilized spectrum of licensed users and then use these empty bands when required.In order to keep the IoT nodes functional all time,continuous energy is required.For this reason the energy harvested techniques are preferred in IoT networks.Mainly it is preferred to harvest Radio Frequency(RF)energy in the network.In this paper a region based multi-channel architecture is proposed.In which the coverage area of primary node is divided as Energy Harvesting Region and Communication Region.The Secondary User(SU)that are the licensed user is IoT enabled with Cognitive Radio(CR)techniques so we call it CR-enabled IoT node/device and is encouraged to harvest energy by utilizing radio frequency energy.To harvest energy efficiently and to reduce the energy consumption during sensing,the concept of overlapping region is given that supports to sense multiple channels simultaneously and help the SU to find best channel for transmitting data or to harvest energy from the ideal channel.From the experimental analysis,it is proved that SU can harvest more energy in overlapping region and this architecture proves to consume less energy during data transmission as compared to single channel.We also show that channel load can be highly reduced and channel utilization is proved to be more proficient.Thus,this proves the proposed architecture cost-effective and energy-efficient.

CAPACITY EVALUATION OF MULTI-CHANNEL WIRELESS AD HOC NETWORKS

In this paper, the capacity of multi-channel, multi-hop ad hoc network is evaluated.In particular, the performance of multi-hop ad hoc network with single channel IEEE 802.11MAC utilizing different topologies is shown. Also the scaling laws of throughputs for large-scale ad hoc networks and the theoretical guaranteed throughput bounds for multi-channel gridtopology systems are proposed. The results presented in this work will help researchers to choosethe proper parameter settings in evaluation of protocols for multi-hop ad hoc networks.

Network-Wide Time Synchronization in Multi-Channel Wireless Sensor Networks

Recent advances in wireless sensor technology have enabled simultaneous exploitation of multiple channels in wireless sensor systems. In this paper, a novel time synchronization algorithm is proposed for multi- channel Wireless Sensor Networks (WSNs) called Multi-Channel Time Synchronization (MCTS) protocol. Time synchronization is critical for many WSN applications and enables efficient communications between sensor nodes along with intelligent spectrum access. Contrary to many existing protocols that do not exploit multi-channel communications, the protocol takes advantage of potential multiple channels and distributes the synchronization of different nodes to distinct channels and thus, reduces the convergence time of synchronization processes significantly.

Monitoring Sea Fog over the Yellow Sea and Bohai Bay Based on Deep Convolutional Neural Network

In this paper,we utilized the deep convolutional neural network D-LinkNet,a model for semantic segmentation,to analyze the Himawari-8 satellite data captured from 16 channels at a spatial resolution of 0.5 km,with a focus on the area over the Yellow Sea and the Bohai Sea(32°-42°N,117°-127°E).The objective was to develop an algorithm for fusing and segmenting multi-channel images from geostationary meteorological satellites,specifically for monitoring sea fog in this region.Firstly,the extreme gradient boosting algorithm was adopted to evaluate the data from the 16 channels of the Himawari-8 satellite for sea fog detection,and we found that the top three channels in order of importance were channels 3,4,and 14,which were fused into false color daytime images,while channels 7,13,and 15 were fused into false color nighttime images.Secondly,the simple linear iterative super-pixel clustering algorithm was used for the pixel-level segmentation of false color images,and based on super-pixel blocks,manual sea-fog annotation was performed to obtain fine-grained annotation labels.The deep convolutional neural network D-LinkNet was built on the ResNet backbone and the dilated convolutional layers with direct connections were added in the central part to form a string-and-combine structure with five branches having different depths and receptive fields.Results show that the accuracy rate of fog area(proportion of detected real fog to detected fog)was 66.5%,the recognition rate of fog zone(proportion of detected real fog to real fog or cloud cover)was 51.9%,and the detection accuracy rate(proportion of samples detected correctly to total samples)was 93.2%.

5G背景下气象媒体以MCN模式发力短视频的策略探究

多频道网络(Multi-Channel Network,MCN)作为一种产品形态,近年来广受各大行业关注。随着MCN业态的崛起,气象媒体也创建了MCN机构,结合市场受众需求,以MCN模式布局短视频、直播,深耕气象领域的内容,盘活气象资源,促进媒体融合转型,实现营销变现。5G时代,借助MCN机构进行内容营销,有助于提升气象品牌的商业价值。基于此,探讨融媒体环境下气象MCN发展现状和问题,分析当前气象媒体以MCN模式运营短视频的优势,并结合实际工作和优秀案例,探究气象媒体以MCN运营短视频的路径和有效策略。

Traffic-aware static channel assignment algorithm in wireless mesh networks

A channel assignment algorithm with awareness of link traffic is proposed in multi-radio multi-channel wireless mesh networks. First, the physical interference model based on the signal-to-interference-plus-noise ratio and successful transmission condition is described. The model is more suitable for a wireless communication environment than other existing models. Secondly, a pure integer quadratic programming （PIQP） model is used to solve the channel assignment problem and improve the capacity of wireless mesh networks. Consequently, a traffic- aware static channel assignment algorithm（TASC） is designed. The algorithm adopts some network parameters, including the network connectivity, the limitation of the number of radios and the successful transmission conditions in wireless communications. The TASC algorithm can diminish network interference and increase the efficiency of channel assignment while keeping the connectivity of the network. Finally, the feasibility and effectivity of the channel assignment solution are illustrated by the simulation results. Compared witb similar algorithms, the proposed algorithm can increase the capacity of WMNs.

基于MCN的起重吊装指挥手势信号自动识别

为了消除起重吊装因指挥手势信号不规范、交流视野被遮挡、人员注意力不集中等产生的安全隐患,利用基于计算机视觉的混合卷积神经网络(MCN)方法,建立人-机交互高风险场景下起重吊装指挥手势信号识别模型,并提出指挥手势信号识别-确认机制。根据国家标准指挥手势信号的运动特点,选择MCN在起重吊装指挥手势信号数据集上进行训练,得到起重吊装指挥手势信号识别模型。起重机驾驶员对比模型识别结果与直接观察结果,判断是否进行相应的操作。选取五种指挥手势信号为例验证。结果表明:模型在多角度多距离下,平均识别准确率为97.13%,模型泛化能力较强。识别速度为36.9 ms,实际应用中平均帧数可达到27.1 fps,满足实时识别的需求。模型具有一定的实用性。

A Hybrid Deep Learning Scheme for Multi-Channel Sleep Stage Classification

Sleep stage classification plays a significant role in the accurate diagnosis and treatment of sleep-related diseases.This study aims to develop an efficient deep learning based scheme for correctly identifying sleep stages using multi-biological signals such as electroencephalography(EEG),electrocardiogram(ECG),electromyogram(EMG),and electrooculogram(EOG).Most of the prior studies in sleep stage classification focus on hand-crafted feature extraction methods.Traditional hand-crafted feature extraction methods choose features manually from raw data,which is tedious,and these features are limited in their ability to balance efficiency and accuracy.Moreover,most of the existing works on sleep staging are either single channel(a single-lead EEG may not contain enough information)or only EEG signal based which can not reveal more complicated physical features for reliable classification of various sleep stages.This study proposes an approach to combine Convolutional Neural Networks(CNNs)and Gated Recurrent Units(GRUs)that can discover hidden features from multi-biological signal data to recognize the different sleep stages efficiently.In the proposed scheme,the CNN is designed to extract concealed features from the multi-biological signals,and the GRU is employed to automatically learn the transition rules among different sleep stages.After that,the softmax layers are used to classify various sleep stages.The proposed method was tested on two publicly available databases:Sleep Heart Health Study(SHHS)and St.Vincent’s University Hospital/University College Dublin Sleep Apnoea(UCDDB).The experimental results reveal that the proposed model yields better performance compared to state-of-the-art works.Our proposed scheme will assist in building a new system to deal with multi-channel or multi-modal signal processing tasks in various applications.

Traffic-Aware Channelization Medium Access Control for Wireless Ad Hoc Networks

Existing multi-channel Medium Access Control (MAC) protocols have been demonstrated to significantly increase wireless network performance compared to single channel MAC protocols. Traditionally, the channelization structure in IEEE 802.11 based wireless networks is pre-configured, and the entire available spectrum is divided into subchannels and equal channel widths. In contrast, this paper presents a Traffic-Aware Channelization MAC (TAC-MAC) protocol for wireless ad hoc networks, where each node is equipped with a single half duplex transceiver. TAC-MAC works in a distributed, fine-grai-ned manner, which dynamically divides variable-width subchannels and allocates subchannel width based on the Orthogonal Frequency Division Multiplexing (OFDM) technique according to the traffic demands of nodes. Simulations show that the TAC-MAC can significantly improve network throughput and reduce packet delay compared with both fixed-width multi-channel MAC and single channel 802.11 protocols, which illustrates a new paradigm for high-efficient multi-channel MAC design in wireless ad hoc networks.

多频道网络(MCN)机构与网络主播劳动关系认定的困境与路径研究

近几年,网络直播依托于互联网的发展迅速崛起,网络主播作为新兴行业也逐渐进入大家的视野。为寻求自身发展,网络主播纷纷选择与多频道网络(MCN)机构进行签约。但在立法上对于MCN机构和主播之间的法律关系尚未有明确的认定标准,在实践中也存在多种情况通常难以认定为劳动关系,因此网络主播通常不能得到劳动法的保护。对此,我国应当引入非标准劳动关系,建立多层次的分类保护机制;制定下位法,对网络用工关系进行规制;同时,司法裁判中也应当认识到此类新型用工形式的特殊性,转变唯“从属性”的观念。

A Routing Metric Based on Available Bandwidth Routing in Wireless Mesh Networks

Wireless Mesh Network has drawn much attention due to wide area service coverage with low system cost and being easy to install.However,WMN suffers from high bit error rate,which provides different link capacity among wireless mesh routers.The conventional routing metrics select the path based on link quality.The link with the best quality is preferred as the data transmission path,and thus all nodes likely select the same link,which leads to network performance degradation.This paper proposes a routing metric that considers the available bandwidth and the number of nodes suffering congestion in the path.It is confirmed that the proposed method provides higher network performance of reduced delay,reduced packet loss and increased throughput than conventional routing metrics.

Opportunistic Routing with Multi-Channel Cooperative Neighbour Discovery

Due to the scattered nature of the network,data transmission in a dis-tributed Mobile Ad-hoc Network(MANET)consumes more energy resources(ER)than in a centralized network,resulting in a shorter network lifespan(NL).As a result,we build an Enhanced Opportunistic Routing(EORP)protocol architecture in order to address the issues raised before.This proposed routing protocol goal is to manage the routing cost by employing power,load,and delay to manage the routing energy consumption based on theflooding of control pack-ets from the target node.According to the goal of the proposed protocol techni-que,it is possible to manage the routing cost by applying power,load,and delay.The proposed technique also manage the routing energy consumption based on theflooding of control packets from the destination node in order to reduce the routing cost.Control packet exchange between the target and all the nodes,on the other hand,is capable of having an influence on the overall efficiency of the system.The EORP protocol and the Multi-channel Cooperative Neighbour Discovery(MCCND)protocol have been designed to detect the cooperative adja-cent nodes for each node in the routing route as part of the routing path discovery process,which occurs during control packet transmission.While control packet transmission is taking place during the routing path discovery process,the EORP protocol and the Multi-channel Cooperative Neighbour Discovery(MCCND)protocol have been designed to detect the cooperative adjacent nodes for each node in the routing.Also included is a simulation of these protocols in order to evaluate their performance across a wide range of packet speeds using Constant Bit Rate(CBR).When the packet rate of the CBR is 20 packets per second,the results reveal that the EORP-MCCND is 0.6 s quicker than the state-of-the-art protocols,according to thefindings.Assuming that the CBR packet rate is 20 packets per second,the EORP-MCCND achieves 0.6 s of End 2 End Delay,0.05 s of Routing Overhead Delay,120 s of Network Lifetime,and 20 J of Energy Consumption efficiency,which is much better than that of the state-of-the-art protocols.

Research of Tile Type Transceiver Module Integrating with Two-Dimensional Sum Difference Network

Transceiver module and two-dimensional sum difference network are important components of phased array antenna. In this paper, multilayer printed board is used to integrate millimeter wave multi-channel transceiver circuit and sum difference network. The interconnection between them is realized through RF coaxial vertical transition. At the same time, the heat dissipation design and inter channel shielding design of the module are carried out. The RF and low frequency required by the module are completed through the wiring between and within the dielectric plate layers. Finally, 128 arrays are fabricated and verified by multi-channel passive test. The results show that the type transceiver module integrating with two-dimensional sum difference network has good performance, and 128 channels have excellent amplitude and phase characteristics. The integration technology has the characteristics of lightweight, miniaturization, high integration and low manufacturing cost. It can be widely used in miniaturized phased array antennas.

UGC平台内容治理策略——中介机构参与下的三方博弈

用户生成内容(UGC)质量问题日益凸显,内容治理成为UGC平台发展的关键行为。研究探索了UGC平台内容治理的影响因素,分析了不同因素对平台、中介机构和用户三方行为路径的影响,为平台开展内容治理、探寻“安全-发展”路径提供决策依据。通过构建“UGC平台-MCN机构-头部用户”三方演化博弈模型,运用复制动态方程分析和MATLAB软件仿真分析,模拟三方博弈主体在内容治理中的策略演化路径。研究发现,惩罚成本和治理强度、中介机构管理成本、流量损失和声誉损失等因素对内容治理主体的决策行为具有重要影响,据此提出有利于博弈主体向{治理,管理,合规}稳定点演化的建议措施,以期促进UGC行业更加健康稳定发展。

网络中心环境下的军事通信超网络结构模型

网络中心环境下的军事通信网络是一个多重边异构的人工功能网络。为了分析、设计和构建网络中心环境下的军事通信网络,通过扩展、综合Jeff的作战网络模型和Hans的网络兵力参考模型,提出了一种能够清晰描述网络节点功能和链路传输类型的军事通信超网络结构模型,给出了模型的数学描述,并说明基于它可将军事通信网络分解为多个具有军事特征的功能子网或专业通信网。最后通过分析某联合作战部队通信的超网络结构特征,验证了模型的有效性。

基于信息功能链的军事通信网络拓扑抗毁性评估方法

为更加准确地评估军事通信网络（military communication network，MCN）拓扑抗毁性（topology survivability，TS），建立了基于节点功能类型的MCN拓扑模型；给出了T-CPUE（transport-collect，process，use，effect）信息功能链的概念，定义MCN拓扑抗毁性为使T-CPUE信息功能链保持连通的能力；分别基于节点连通度、链路结合度、节点重要度、链路重要度和T-CPUE信息功能链的连通度，提出了的5种MCN拓扑抗毁性指标。以某体系作战通信网络为例，分析了在逐渐移除最大度节点和最重要节点的策略下，网络的各种拓扑抗毁性随移除节点数的变化情况，验证了所提方法的合理性和有效性。

基于基站切换的交通信息采集技术应用研究

基于移动通信网络基站切换的交通信息采集技术,突破传统交通信息采集技术许多的局限性,仅需增加少量处理设备情况下,能够实时、广域范围内采集交通数据,表现出了良好的实用性、经济性,是一种新型的交通信息采集技术。分析这种新型技术的实现原理、关键技术、影响要素,并结合实践应用给出了技术评估指标体系,多方面评估该技术推广发展可行性,提出该技术应用、发展、完善重点,为规模性应用提供研究基础。