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2018 3rd International Conference on Computational Modeling, Simulation and Applied Mathematics (CMSAM 2018)

作者： Hao WU Shu-fang LI Beijing Key Laboratory of Network System Architecture and Convergence Beijing Laboratory of Advanced Information Network Beijing University of Posts and Telecommunications Beijing

For the violent data fluctuation of the promotion day data and the characteristics of limited data size, combined with the idea of migration learning, two modeling ideas of parallel model and serial model are proposed. The algorithm avoids the difference in data distribution between promotion day and non-promotion day, and makes full use of non-promotion day data to improve the accuracy of model prediction. Experiments conducted by real promotion day data show that migration learning can effectively reduce prediction errors.

关键词： Promotion day Purchase forecast Model fusion Migration learning

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A Power system Transient Stability Assessment Model Based on Stacked Denoising Autoencoder

A Power System Transient Stability Assessment Model Based on...

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2018 3rd International Conference on Computational Modeling, Simulation and Applied Mathematics (CMSAM 2018)

作者： Mei FU Shu-fang LI Beijing Key Laboratory of Network System Architecture and Convergence Beijing Laboratory of Advanced Information Network Beijing University of Posts and Telecommunications Beijing

Since the grid data is not always "perfect", there are often cases where data is missing or contains noise. In order to solve the above problems and further improve the generalization ability of the power system transient stability assessment model, we introduce Denoising Autoencoder(DAE) structure and propose a model based on Stacked Denoising Autoencoder(SDAE). Firstly, construct the original input features that can reflect the transient stability characteristics of the power system. And then use the input features layer-by-layer unsupervised learning to get the encoder of DAE. Stacking all the trained encoders constitutes a SDAE as an advanced feature extraction model. Next, using the advanced features and labels has a supervised training classifier to obtain a complete transient stability assessment model. The model proposed in this paper has been tested on 10-machine New-England Power system. The simulation results show that the proposed model is robust to the "imperfection" of the input data, and the generalization ability is stronger.

关键词： Stacked denoising autoencoder Logistic regression Classification Transient stability assessment

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Adversarial Attack? Don't Panic

Adversarial Attack? Don't Panic

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International Conference on Big Data Computing and Communications (BIGCOM)

作者： Feixia Min Xiaofeng Qiu Fan Wu Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China

Deep learning is playing a more and more important role in our daily life and scientific research such as autonomous systems, intelligent life and data mining. However, numerous studies have showed that deep learning with superior performance on many tasks may suffer from subtle perturbations constructed by attacker purposely, called adversarial perturbations, which are imperceptible to human observers but completely effect deep neural network models. The emergence of adversarial attacks has led to questions about neural networks. Therefore, machine learning security and privacy are becoming an increasingly active research area. In this paper, we summarize the prevalent methods for the generating adversarial attacks according to three groups. We elaborated on their ideas and principles of generation. We further analyze the common limitations of these methods and implement statistical experiments of the last layer output on CleverHans to reveal that the detection of adversarial samples is not as difficult as it seems and can be achieved in some relatively simple manners.

关键词： Perturbation methods Iterative methods Machine learning Neural networks Manifolds Classification algorithms Machine learning algorithms

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A comprehensive analysis of video service quality on IQIYI from large-scale data sets 13th

A comprehensive analysis of video service quality on IQIYI f...

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13th International Conference on Heterogeneous networking for Quality, Reliability, Security and Robustness, QShine 2017

作者： Guo, Yao Lv, Qiujian Liu, Fang Yang, Jie Gao, Zhe Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Center for Data Science BUPT Beijing100876 China Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China Technology Research Institute Aisino Corporation Beijing100086 China

ISBN: (纸本)9783319780771

With the proliferation of online video, measuring the quality of the video service has become a vital aspect for improving user’s experience. Recent work shows that measurable quality metrics such as buffering, bitrate, and video resolutions impact user’s experience, but none of them reveal the real relationships between these metrics and user’s actual experience. This paper attempts to solve the problem above. We use IQIYI as the sample, and our large-scale dataset consists of 7 days real Internet traffic in a northern city of China. We quantify user’s experience at per-video level (or view). Using Apache Spark, we extract some video events and calculate several quality metrics. In order to investigate the relationship between the metrics and user’s experience, we use the FP-Growth algorithm to mining the implicit association rules and get some interesting results. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018.

关键词： Large dataset

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Status-based Detection of malicious code in Internet of Things (IoT) devices

Status-based Detection of malicious code in Internet of Thin...

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IEEE Conference on Communications and network Security (CNS)

作者： Dongdi Wei Xiaofeng Qiu Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China

We categorize the malicious code in IoT devices, analyze their characters and disassemble them as far as basic actions. Then we simulate these basic malicious code running in the background and show that we indeed can find out the malicious activity of the IoT device by monitoring the runtime of identified service tasks. We choose fluctuation and abrupt change point as our detection features according to the simulation result, then we design and implement our detection system to detect the activity of a web camera. Our result show that malicious code can be detected by monitoring the device's running status.

关键词： Malware Task analysis Runtime Internet of Things Feature extraction Hardware Cryptography

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Geographic Routing Based on Social Dynamic Features Aware in Vehicle Social network

Geographic Routing Based on Social Dynamic Features Aware in...

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International Symposium on Wireless Communication systems (ISWCS)

作者： Qing Liao Jingyi Zhang Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China

Vehicular ad-hoc network has the characteristics of Delay Tolerant network and social network. In this background, we take the social attributes of Delay Tolerant network as starting point and study the macroscopic dynamic features, micro dynamic features and dynamic contact features of vehicles. In this paper, we proposed a geographic multicast routing based on social dynamic features aware which solves messages transmission problems in vehicular ad hoc network. Different from the existing mobility-aware geocast algorithm, our algorithm takes into account not only the relationships between vehicles mobility and geographical location, but also the contact features between vehicles and destination areas. Finally, it is proved that our algorithm is superior to the existing mobility-aware geocast algorithm in term of delivery rate, network overhead and average delay by the real mobile data model simulation in large vehicular ad-hoc network. The results prove the effectiveness of our algorithm, and the routing protocol we proposed is suited for large urban vehicular ad hoc networks.

关键词： Routing Vehicle dynamics Public transportation Trajectory Social network services Entropy Heuristic algorithms

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A Community-Based Opportunistic Routing Protocol in Delay Tolerant networks

A Community-Based Opportunistic Routing Protocol in Delay To...

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International Conference on Computer and Communications (ICCC)

作者： Sun Haoran Wu Muqing Cao Yanan Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Post and Telecommunications Beijing China

ISBN: (纸本)9781538683408

In Delay Tolerant networks (DTN), the nodes are sparse and intermittently connected, the end-to-end connectivity between nodes is rare. To overcome the intermittent connectivity, DTN routing protocols employ the “store-carry-forward” strategy to transmit messages. A message is delivered to a destination node from a source node via opportunistic contacts between intermediate nodes. In addition, nodes in DTN have a feature of community. In a community, network node meet each other regularly, while between communities there are only few encounter opportunities. In this paper, we propose a community-based opportunistic routing protocol which works in two modes, the Intra-community mode and the inter-community mode. In Intra-community message transmission, we adopt reasonable forwarding conditions and E-PRoPHET algorithm to design the transmission mechanism. In inter-community message transmission, we use the communication probability and the remaining energy to select the most suitable forwarding node. All of these are designed to limit the number of copies of messages, so as to ensure the performance of the algorithm. We extensively simulated our proposal and have shown that our proposed protocol can raise the delivery ratio, reduce the delivery delay and improve the efficiency of forwarding messages.

关键词： Routing protocols Delays Relays Probability Mathematical model Routing

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Optimized Trajectory Design in UAV Based Cellular networks: A Double Q-Learning Approach

Optimized Trajectory Design in UAV Based Cellular Networks: ...

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International Conference on Communication systems

作者： Xuanlin Liu Mingzhe Chen Changchuan Yin Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781538678657;9781538678640

In this paper, the problem of trajectory design of unmanned aerial vehicles (UAVs) for maximizing the number of satisfied users is studied in a UAV based cellular network. In this network, the UAV works as a flying base station that serves users, and the user indicates its satisfaction in terms of completion of its data request within an allowable maximum waiting time. The trajectory design is formulated as an optimization problem whose goal is to maximize the number of satisfied users. To solve this problem, a machine learning framework based on double Q-learning algorithm is proposed. The algorithm enables the UAV to find the optimal trajectory that maximizes the number of satisfied users. Compared to the traditional learning algorithms, such as Q-learning that selects and evaluates the action using the same Q-table, the proposed algorithm can decouple the selection from the evaluation, therefore avoid overestimation which leads to sub-optimal policies. Simulation results show that the proposed algorithm can achieve up to 19.4% and 6.7% gains in terms of the number of satisfied users compared to random algorithm and Q-learning algorithm.

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Data Correlation-Aware Resource Management in Wireless Virtual Reality (VR): An Echo State Transfer Learning Approach

arXiv

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arXiv 2019年

作者： Chen, Mingzhe Saad, Walid Yin, Changchuan Debbah, Mérouane Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing100876 China Wireless@VT Bradley Department of Electrical and Computer Engineering Virginia Tech BlacksburgVA United States Mathematical and Algorithmic Sciences Lab Huawei France R and D Paris

Providing seamless connectivity for wireless virtual reality (VR) users has emerged as a key challenge for future cloud-enabled cellular networks. In this paper, the problem of wireless VR resource management is investigated for a wireless VR network in which VR contents are sent by a cloud to cellular small base stations (SBSs). The SBSs will collect tracking data from the VR users, over the uplink, in order to generate the VR content and transmit it to the end-users using downlink cellular links. For this model, the data requested or transmitted by the users can exhibit correlation, since the VR users may engage in the same immersive virtual environment with different locations and orientations. As such, the proposed resource management framework can factor in such spatial data correlation, so as to better manage uplink and downlink traffic. This potential spatial data correlation can be factored into the resource allocation problem to reduce the traffic load in both uplink and downlink. In the downlink, the cloud can transmit 360 contents or specific visible contents (e.g., user field of view) that are extracted from the original 360 contents to the users according to the users' data correlation so as to reduce the backhaul traffic load. In the uplink, each SBS can associate with the users that have similar tracking information so as to reduce the tracking data size. This data correlation-Aware resource management problem is formulated as an optimization problem whose goal is to maximize the users' successful transmission probability, defined as the probability that the content transmission delay of each user satisfies an instantaneous VR delay target. To solve this problem, a machine learning algorithm that uses echo state networks (ESNs) with transfer learning is introduced. By smartly transferring information on the SBS's utility, the proposed transfer-based ESN algorithm can quickly cope with changes in the wireless networking environment due to users' conten

关键词： Virtual reality

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Adaptive resource allocation scheme for wireless cellular networks 2

Adaptive resource allocation scheme for wireless cellular ne...

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2nd IEEE International Conference on Energy Internet, ICEI 2018

作者： Wang, Yue Miao, Jiansong Liang, Xinyu Wang, Jianmin Yue Wang Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China Beijing Laboratory of Advanced Information Networks Beijing University of Posts and Telecommunications Beijing China Beijing University of Posts and Telecommunications Beijing China 6th Research Institute of China Electronics Corporation Beijing China

ISBN: (纸本)9781538641316

As spectrum scarcity and inter cell interference (ICI) are both limiting factors in wireless cellular system, ICI coordination (ICIC) techniques play an important role in improving system performance. Soft Frequency Reuse (SFR) is an effective way to manage the spectrum and reduce ICI in cellular system. It carries out resource allocation prior to system deployment, and dynamic schemes allocate resource regardless of the actual network traffic and interference distribution, both of which limit the potential system performance. Energy Internet's deployment is becoming more and more intensive. It is important to increase system throughput and reduce data error rate. In this paper, an adaptive resource allocation scheme (ARAS) is proposed which first dynamically optimizes resource allocation according to interference distribution and traffic load. In ARAS, the interference thresholds and the roles of victim and aggressor require to be specific. For each victim user, their dominant interferer (DI) applies the Different Evolution (DE) to find the optimal transmission power reduction, aiming at improving victim users' performance and guaranteeing data requirement. To improve system performance, extra resources are allocated to balance ICIC and system capacity. Simulation results show that the ARAS achieves better SINR and throughput compared with existing ICIC schemes. © 2018 IEEE.

关键词： Resource allocation

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