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6th IEEE International Conference on Computer and Communications, ICCC 2020

作者： Yujie, Rong Muqing, Wu Yiming, Chen Beijing University of Posts and Telecommunications School of Information and Communication Engineering Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Acknowledgment Beijing China

ISBN: (纸本)9781728186351

Different from the traditional TCP/IP network, Software Defined network (SDN) uses a layered architecture to decouple the control plane and data plane. The controller is the core device of the control plane, and the control plane is mainly responsible for the decision-making control of the routing strategy. Because the processing power of a single controller is limited, the multi-controller network architecture has become an inevitable choice in the WAN. The layout of the controllers in SDN has an impact on the performance of the entire network. The controller placement problem (CPP) is an NP-hard problem. The challenges of CPP solution are as follows. 1) the number of controllers;2) the position of the controllers and the position of the switches under their management in the network topology. The clustering by fast search and find of density peaks (CFSFDP) algorithm is a density-based clustering algorithm. It has few initial parameters and does not require iterative solution. However, the important parameter dc of the CFSFDP algorithm is usually selected based on experience, and the number of cluster centers cannot be determined automatically. This paper proposes a new controller placement algorithm by improving the CFSFDP algorithm. We use the idea of information entropy to automatically determine the dc value, and automatically determine the number and location of the controllers based on the jumping point in the decision graph. It can be seen from the experimental results that compared with random placement, k-means and CFSFDP algorithm, our proposed algorithm can effectively reduce network propagation delay and improve network performance. © 2020 IEEE.

关键词： Controllers

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A Two-Pathway Convolutional Neural network with Temporal Pyramid network for Action Recognition 6

A Two-Pathway Convolutional Neural Network with Temporal Pyr...

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6th IEEE International Conference on Computer and Communications, ICCC 2020

作者： Jie, Zhu Muqing, Wu Weiyao, Xu Beijing University of Posts and Telecommunications School of Information and Communication Engineering Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Acknowledgment Beijing China

ISBN: (纸本)9781728186351

In order to solve the problem of imperfect capture of visual rhythm in action recognition, this paper proposes a novel model which is a combination of a two-pathway network and temporal pyramid networks (TPNs). Specifically, our work involves two aspects, on the one hand, we integrate TPNs into the fast pathway and the slow pathway of SlowFast network to capture multi-level features, and then merge the prediction results of the two pathways in the final recognition stage, which boosts performance of our network by enhancing the semantics extraction at input layer and feature layer. On the other hand, we apply a ConvLSTM module to improve the capability of temporal modeling in TPN, which can further strengthen the capture of features in the long-term dimensions, and the advanced TPN promotes the fusion of temporal and spatial features. Experiments on the Kinetics-400 dataset demonstrate the superiority of our novel architecture combining two-pathway network and advanced TPN in action recognition. © 2020 IEEE.

关键词： Convolutional neural networks

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Effective Fusion of 3DCNN and Convolutional GRU for Gesture Recognition 6

Effective Fusion of 3DCNN and Convolutional GRU for Gesture ...

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6th IEEE International Conference on Computer and Communications, ICCC 2020

作者： Yangbiao, Luo Muqing, Wu Weiyao, Xu Beijing University of Posts and Telecommunications School of Information and Communication Engineering Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Acknowledgment Beijing China

ISBN: (纸本)9781728186351

Gesture recognition is a challenging topic in the field of computer vision. This paper combines the advantages of 3DCNN and ConvRNN in spatial and temporal feature extraction respectively and proposes a network structure of 'Res3DDilated+ConvGRU+2DCNN'. After that, a variant of ConvGRU is proposed, which further exerts the advantages of ConvGRU in temporal feature extraction. The experiment compares the effect of combining dilated convolution in the temporal dimension with 3D Resnet, and the effectiveness of the ConvGRU variant in spatiotemporal information fusion. In the 3D dilated convolutional network, we designed a suitable convolution kernel structure and step size so that subsequent modules can be reused directly. The modular structure design can be easily replaced. The comparison on the IsoGD dataset shows our network effectively integrates spatial and long-short terms features in gesture recognition videos. The variant of ConvGRU also enables each module to play its own advantages in the framework. © 2020 IEEE.

关键词： Convolution

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Mobility-Aware Proactive Video Segment Caching Based on Deep Reinforcement Learning

Mobility-Aware Proactive Video Segment Caching Based on Deep...

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IEEE International Conference on network Infrastructure and Digital Content (IC-NIDC)

作者： Xuefei Li Jiawei Wang Zhilong Zhang Danpu Liu Beijing Laboratory of Advanced Information Network Beijing University of Posts and Telecommunications Beijing China Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781665405836

Maintaining efficient and successive video streaming services in cellular networks is challenging due to user mobility and ever-increasing volume of data traffic. A promising solution is to cache popular contents at the edge of wireless networks. Although caching schemes have been widely discussed, few of them jointly considered the characteristics of streamed video data and user mobility. In this paper, we construct a dynamic caching decision framework based on Long Short-Term Memory (LSTM) and Deep Q-network (DQN). Based on this framework, a mobility-aware segment-level caching strategy is proposed to maximize the cache hit rate. Simulation results show that our proposed method can achieve 20% performance improvement by comparing with baseline caching algorithms.

关键词： Cellular networks Simulation Wireless networks Heuristic algorithms Conferences Reinforcement learning Bandwidth

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Study on Pedestrian Detection Based on an Improved YOLOv4 Algorithm 6

Study on Pedestrian Detection Based on an Improved YOLOv4 Al...

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6th IEEE International Conference on Computer and Communications, ICCC 2020

作者： Wen, Boyuan Wu, Muqing Beijing University of Posts and Telecommunications School of Information and Communication Engineering Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Acknowledgment Beijing China

ISBN: (数字)9781728186351

ISBN: (纸本)9781728186351

Pedestrian detection, which is widely used in automatic driving and pedestrian analysis, has always been a hot research topic in the fields of artificial intelligence and computer vision. With the development of deep learning, pedestrian detectors are becoming more accurate and faster. However, most of them can't strike a balance between accuracy and speed well. Therefore, in this study, we propose a pedestrian detection model based on an improved YOLOv4 algorithm which concerns both detection accuracy and efficiency. The detection model combines a new type of SPP (Spatial Pyramid Pooling) network and K-means clustering algorithm with YOLOv4 model for easier feature extraction. Furthermore, Mish activation function is applied in the neck of the detection model, replacing Leaky ReLU activation function to improve the detection performance. Our pedestrian detector achieves excellent results on the Caltech pedestrian dataset: 84.7% AP at a real-time speed of 36.4 FPS on Titan XP. © 2020 IEEE.

关键词： K-means clustering

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Exploiting visual semantic reasoning for video-text retrieval 29

Exploiting visual semantic reasoning for video-text retrieva...

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29th International Joint Conference on Artificial Intelligence, IJCAI 2020

作者： Feng, Zerun Zeng, Zhimin Guo, Caili Li, Zheng Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China Beijing Laboratory of Advanced Information Networks Beijing China

ISBN: (纸本)9780999241165

Video retrieval is a challenging research topic bridging the vision and language areas and has attracted broad attention in recent years. Previous works have been devoted to representing videos by directly encoding from frame-level features. In fact, videos consist of various and abundant semantic relations to which existing methods pay less attention. To address this issue, we propose a Visual Semantic Enhanced Reasoning network (ViSERN) to exploit reasoning between frame regions. Specifically, we consider frame regions as vertices and construct a fully-connected semantic correlation graph. Then, we perform reasoning by novel random walk rule-based graph convolutional networks to generate region features involved with semantic relations. With the benefit of reasoning, semantic interactions between regions are considered, while the impact of redundancy is suppressed. Finally, the region features are aggregated to form frame-level features for further encoding to measure video-text similarity. Extensive experiments on two public benchmark datasets validate the effectiveness of our method by achieving state-ofthe-art performance due to the powerful semantic reasoning. © 2020 Inst. Sci. inf., Univ. Defence in Belgrade. All rights reserved.

关键词： Semantics

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Performance analysis and enhancement of random access process in cellular-IoT

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The Journal of China Universities of Posts and Telecommunications 2019年第6期26卷 1-10页

作者： Xing Shuchen Wen Xiangming Lu Zhaoming Pan Qi Jing Wenpeng Beijing Key Laboratory of Network System Architecture and Convergence Beijing Laboratory of Advanced Information NetworksBeijing University of Posts and TelecommunicationsBeijing 100876China

Narrowband Internet of things(NB-IoT) and enhanced machine-type communications(eMTC) are two new IoT-oriented solutions introduced by the 3 rd generation partnership project(3 GPP) in Rel-13. In order to meet the new requirements(such as long battery life, low device cost, low deployment cost, extended coverage and support for a massive number of devices) of machine-to-machine(M2 M) communication, these two technologies had some improvements on the random access(RA) mechanism compared to traditional long term evolution(LTE). For example, repetition of preamble transmission and coverage enhancement(CE) levels have been proposed to offer communication services in a wider area. In addition, NB-IoT has adopted a new spectrum allocation method and proposed a new type of preamble structure to meet the requirement of big amount of connections. We summarize details and differences of the RA process in LTE, eMTC and NB-IoT. Afterwards, as an improvement, we propose an enhanced access protocol for NB-IoT. Finally, performance analysis and comparison are presented in terms of access success probability, average access delay, access spectrum efficiency and average number of RA attempts.

关键词： NB-IoT eMTC LTE RA access protocol

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A Fast Global Adaptive Solution to Low-light Images Enhancement in Visual SLAM 6

A Fast Global Adaptive Solution to Low-light Images Enhancem...

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6th IEEE International Conference on Computer and Communications, ICCC 2020

作者： Cheng, Weishao Zhang, Yanting Qi, Yonggang Liu, Jun Liu, Fang Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing100876 China Donghua University Shanghai201620 China

ISBN: (纸本)9781728186351

Simultaneous Localization and Mapping (SLAM) is considered as an essential basis for autonomous robots and vehicles. Visual SLAM applies visual sensors to collect information and estimate the motion of the sensor in an unknown environment. However, it relies heavily on feature matching within images, so that the quality of the images has a great effect on the efficiency. In a low light intensity environment, the performance of motion estimation declines seriously. This paper presents a global adaptive solution to compensate the light condition and applies this solution to motion estimation in ORB-SLAM as an optimization module. key of the solution is to obtain global adaptive brightness gain for image intensifiers. The performance of the image intensifier is also evaluated in this paper as well as the proof of higher estimation accuracy. The result of the strengthened ORB-SLAM on the TUM benchmark shows that there is a significant performance boost especially in low luminance environment. © 2020 IEEE.

关键词： Luminance

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Wireless Channel Modeling, Simulation and Analysis for Electronic Registration Identification of Vehicles 3

Wireless Channel Modeling, Simulation and Analysis for Elect...

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3rd IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2020

作者： Cai, Tingxiao Fan, Wenmin Feng, Jing Hong, Weijun China Electronics Standardization Institute Beijing China Beijing Laboratory of Advanced Information Network Beijing University of Posts and Telecommunications Beijing China Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781728190457

Electronic registration identification (ERI) of the motor vehicle is an important application of passive radio frequency identification (RFID) in the field of intelligent transportation which has been put into use in some countries. ERI is in the pilot research stage now in China, but the release of the standard is accelerating its promotion. The performance evaluation of car-related RFID products is often accomplished by test and trial method currently. The test results are seriously affected by irrelevant environmental factors, making it impossible to carry out scientific repeatable experiments. In this paper, the communication channel model of ERI system in the highway traffic scene is modeled based on the ray tracing method. In order to accurately establish the model, we conducted a simulation analysis on the influence of factors such as antenna pattern, polarization mode, ground material, and environmental noise on the received signal power and tag reading distance. Files generated based on the model in this article can be loaded onto the channel simulator, so as to build an ERI test system with reproducible test results which has important application value. © 2020 IEEE.

关键词： Ray tracing

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Channel Model for RFID based Electronic Registration Identification of the motor vehicle in Practical Open Transportation Scenario 3

Channel Model for RFID based Electronic Registration Identif...

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3rd IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2020

作者： Feng, Jing Fan, Wenmin Hong, Weijun Cai, Tingxiao Shi, Chunteng Zhou, Jitianbai China Electronics Standardization Institute Beijing China Beijing Laboratory of Advanced Information Network Beijing University of Posts and Telecommunications Beijing China Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781728190457

Current researches on communication channel of electronic registration identification of the motor vehicle (ERI) are mostly based on the single lane two channel model, which is not consistent with the multi-lane multi-car scene in the practical application. In this paper, a channel model combined with deterministic and stochastic component is firstly proposed for ERI. The theoretical formula of the model is derived and simulated. The influence of Doppler shift on each transmission path in the channel model and the effect of adjacent lane reflection path on channel fading is analyzed in detail. The work of this paper is with great significance for evaluation of ERI system in practical scenario. © 2020 IEEE.

关键词： Stochastic systems

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