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2nd IEEE International Conference on Energy Internet, ICEI 2018

作者： Shen, Yidi Wen, Xiangming Wang, Luhan Guan, Wanqing Beijing Advanced Innovation Center for Future Internet Technology Beijing China Beijing Laboratory of Advanced Information Networks Beijing University of Posts and Telecommunications Beijing China Beijing Key Laboratory of Network System Architecture and Convergence Beijing China

ISBN: (纸本)9781538641316

A microgrid is a novel energy production-storageconsumption mode in which energy entities can both generate and consume energy. With the access of these entities, the energy internet becomes a super complex network of information and physics integration. The computational difficulty of obtaining the topological information is improved. Studying the topology for energy trading of energy entities in different geographic regions can help to analyze the transmission of energy and information. Visualization is an important measure to display the network topological structure intuitively and clearly. In this paper, a compression algorithm that considered cross-regional interaction is proposed to obtain the main topology for visualization effectively. The proposed algorithm can realize the different degrees of compression between intra-regional topology and inter-regional topology. The simulation results have shown that the algorithm can preserve the main topological information and has a considerable compression rate. © 2018 IEEE.

关键词： Visualization

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Multi-Agent Deep Reinforcement Learning based Spectrum Allocation for D2D Underlay Communications

arXiv

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arXiv 2019年

作者： Li, Zheng Guo, Caili School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China

—Device-to-device (D2D) communication underlay cellular networks is a promising technique to improve spectrum efficiency. In this situation, D2D transmission may cause severe interference to both the cellular and other D2D links, which imposes a great technical challenge to spectrum allocation. Existing centralized schemes require global information, which causes a large signaling overhead. While existing distributed schemes requires frequent information exchange among D2D users and cannot achieve global optimization. In this paper, a distributed spectrum allocation framework based on multi-agent deep reinforcement learning is proposed, named multi-agent actor critic (MAAC). MAAC shares global historical states, actions and policies during centralized training, requires no signal interaction during execution and utilizes cooperation among users to further optimize system performance. Moreover, in order to decrease the computing complexity of the training, we further propose the neighbor-agent actor critic (NAAC) based on the neighbor users’ historical information for centralized training. The simulation results show that the proposed MAAC and NAAC can effectively reduce the outage probability of cellular links, greatly improve the sum rate of D2D links and converge quickly. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep learning

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Dynamic Resource Orchestration of Service Function Chaining in network Function Virtualizations 1st

Dynamic Resource Orchestration of Service Function Chaining ...

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1st International Conference on 5G for Future Wireless networks, 5GWN 2017

作者： Yu, Bangchao Zheng, Wei Wen, Xiangming Lu, Zhaoming Wang, Luhan Ma, Lu Beijing Laboratory of Advanced Information Networks Beijing China Beijing Advanced Innovation Center for Future Internet Technology Beijing China Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9783319728223

network Functions Virtualization is a new network architecture framework and is revolutionizing the way networking service that how to design and deploy. NFV promotes virtualizing network functions and improves the flexibility to resource orchestration for request service function chains. However, how to find the most suitable resource in NFV-based network resource is a challenge. This paper presents a comprehensive state of the NFV resource orchestration by introducing a dynamic resource orchestration architecture that can configure dynamic resources. With consideration of load balance, energy cost and resource consumption, the resource orchestration is formulated as a multi-objective optimal problem. Finally, a multi-objective simulated annealing algorithm is used to obtain the optimal resource strategy to deploy network functions. Simulation results show that the solution for dynamic resource orchestration can achieve approximate optimal solution in acceptable time and reduce 8% energy consumption with a 0.89 Jain’s fairness index. © 2018, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： network function virtualization

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A fault-tolerant data acquisition scheme with MDS and dynamic clustering in energy internet 2

A fault-tolerant data acquisition scheme with MDS and dynami...

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2nd IEEE International Conference on Energy Internet, ICEI 2018

作者： Chen, Xin Wen, Xiangming Wang, Luhan Jing, Wenpeng Beijing Laboratory of Advanced Information Networks Beijing University of Posts and Telecommunications Beijing China Beijing Key Laboratory of Network System Architecture and Convergence Beijing China Beijing Advanced Innovation Center for Future Internet Technology Beijing China

ISBN: (纸本)9781538641316

Energy Internet (EI) is regarded as a promising method to solve the energy shortage and improve the efficiency of renewable energy. It demands frequent exchanges of data flow and energy flow, which puts forward strict requests for data veracity and availability. As a result, a reliable and robust data network is critical to realize the promises of EI. This paper introduces the fog nodes with computing ability to enable erasure coding based fault-tolerant techniques so that the data availability can be guaranteed. However, the distributed and irregular deployment of EI nodes have brought many challenges to maximum distance separable code (MDS) based fault-tolerant schemes. As a result, this paper investigates the design of encoding parameters and clustering mechanism to adjust the flexible situations. And then, we propose a novel fault-tolerant mechanism based on MDS and dynamic clustering to improve the data availability. Numerical simulation results show our scheme works better than the backup and traditional MDS based schemes with determined cluster size. © 2018 IEEE.

关键词： Internet of Energy

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Exploiting offset-guided network for pose estimation and tracking

arXiv

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arXiv 2019年

作者： Zhang, Rui Zhu, Zheng Li, Peng Wu, Rui Guo, Chaoxu Huang, Guan Xia, Hailun Bejing 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 Institute of Automation Chinese Academy of Sciences Beijing China Horizon Robotics Beijing

Human pose estimation has witnessed a significant advance thanks to the development of deep learning. Recent human pose estimation approaches tend to directly predict the location heatmaps, which causes quantization errors and inevitably deteriorates the performance within the reduced network output. Aim at solving it, we revisit the heatmap-offset aggregation method and propose the Offset-guided network (OGN) with an intuitive but effective fusion strategy for both two-stages pose estimation and Mask R-CNN. For two-stages pose estimation, a greedy box generation strategy is also proposed to keep more necessary candidates while performing person detection. For mask R-CNN, ratio-consistent is adopted to improve the generalization ability of the network. State-of-the-art results on COCO and PoseTrack dataset verify the effectiveness of our offset-guided pose estimation and tracking. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep learning

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Dynamic backoff based access mechanism for LoRaWAN class A 2

Dynamic backoff based access mechanism for LoRaWAN class A

引用

2nd IEEE International Conference on Energy Internet, ICEI 2018

作者： Yuan, Pengyu Wen, Xiangming Lu, Zhaoming Pan, Qi Beijing Key Laboratory of Network System Architecture and Covergence Beijing University of Posts and Telecommunications Beijing Laboratory of Advanced Information Networks Beijing China

ISBN: (纸本)9781538641316

LoRaWAN is a popular technology in Low Power Wide Area networks(LPWANs). It can be applied to the smart agriculture, smart building, logistics tracking, disaster monitoring, and so on. The Class A terminal device in LoRaWAN adopts the pure ALOHA access mode. It has the problems of low channel utilization, high access delay and high collision probability. In this paper, we mainly study the access process of Class A devices in LoRaWAN, and derive the mathematical analytical model. To solve this problem, we propose a enhanced access mechanism, dynamic backoff mechanism. The backoff window size would be adaptively adjusted according to the access user attempts. The results show that our model is correct and the proposed scheme can effectively improve the successful access probability for LoRaWAN nodes. © 2018 IEEE.

关键词： Probability

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Markov chain based on path selection in the heterogeneous internet of things model 2

Markov chain based on path selection in the heterogeneous in...

引用

2nd IEEE International Conference on Energy Internet, ICEI 2018

作者： Wu, Huan Wen, Xiangming Lu, Zhaoming Huang, Shuyang Beijing Key Laboratory of Network System Architecture and Convergence Beijing Laboratory of Advanced Information Networks Beijing University of Posts and Telecommunications Beijing100876 China School of Electronics and Information Engineering West Anhui University Lu'an237012 China

ISBN: (纸本)9781538641316

The Internet of Things (IoT) is a new heterogeneous system integrated by various end-users with different technologies. However, the limiting factor is bandwidth in the IoT due to exploding the end-users and the network bandwidth requirement. A novel IoT model, which integrates the Power Line Carrier (PLC) and the Wireless network (WN), is proposed to solve the bandwidth problem from the architecture, especially in the areas lacking network facilities. In addition, we exploit an effective virtual layer (EVL) which allows the different end-users access to the model seamlessly. Then, the attractor selection algorithm based on Markov chain (ASMA) is employed to select an optimal path among the PLC or the WN. Simulation results demonstrate that the proposed model has the smaller delay than other algorithms and makes the model more stable. © 2018 IEEE.

关键词： Internet of things

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Energy Consumption Optimization Scheme of Cloud Data Center Based on SDN

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Procedia Computer Science 2018年 131卷 1318-1327页

作者： Qing Liao Zun Wang Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing 100876 China

In response to the mobile Internet, Internet of things and cloud computing technology fast development, the operation of large-scale distributed computing cloud data center construction in the world at the same time, the network data calculation of energy consumption problem is causing extensive concern. And the software-defined network (SDN) provides a feasible solution to the rigid problem of traditional network architecture. Based on SDN technology, this paper proposes a method of energy consumption control based on cloud data center. Aiming at server energy saving, the multi-objective optimization model of virtual machine migration integration is established, and the integration mechanism of virtual machine migration based on mixed single-parent genetic algorithm is proposed. The experimental results show that the algorithm can be used to solve the problem of virtual machine migration and integration in data center.

关键词： Cloud data center software-defined network energy consumption control VM migration integration

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Generative Model with Kernel Density Estimation

Generative Model with Kernel Density Estimation

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

作者： Jing Tan Sixing Yin Shuo Zhao Beijing Key Laboratory of Network System Architecture and Convergence Beijing China

In this paper, a novel generative model is proposed based on kernel density estimation. Different from other generative models like GANs [1] and VAEs [2], the model directly learns the distribution of training dataset in a non-parametric way. The mean absolute error (MAE) between the estimated probability density of the real and generated samples is used as loss function for model to train. To address the sparsity of high-dimensional distribution, we associate the proposed generative model with an encoder, by which the observed high-dimensional data can be transformed to low-dimensional latent features. Results on the MNIST dataset show that our proposed model is able to generate samples visually indistinguishable from the real ones.

关键词： Kernel Estimation Training Generators Training data Gallium nitride Bandwidth

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Terajet effect of dielectric sphere and THz imaging 5

Terajet effect of dielectric sphere and THz imaging

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Infrared, Millimeter-Wave, and Terahertz Technologies V 2018

作者： Qu, Qingshan Liu, Hailing Zhu, Di Yang, Menghan Cui, Bin Feng, Shuai Yang, Yuping School of Science Minzu University of China Beijing100081 China Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Acknowledgment School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China

ISBN: (数字)9781510622517

ISBN: (纸本)9781510622500

Analogous to microsphere optical nanoscope, an easy and low-price method of THz imaging is proposed and developed for improving the spatial resolution beyond the diffraction limit. By attaching a 2-4 mm diameter Teflon sphere, a narrow, high-intensity, subdiffraction-waist THz beam with a strong jet-like distribution propagates into the background medium from the sphere's shadow-side surface and a subwavelength spatial resolution better than λ/3 is demonstrated. Furthermore, the dielectric sphere-coupled THz microscope not only enables far-field, large-area measurement but also characterizes high-throughput and broad-band imaging properties. In addition, the size effect on terajet of dielectric sphere was simulated and shows that its magnification capability and focal length are size-dependent and frequencysensitive. © 2018 SPIE.

关键词： Spheres

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