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Fog computing for vehicular Ad-hoc networks: paradigms, scenarios, and issues

The Journal of China Universities of Posts and Telecommunications 2016年第2期23卷 56-65,96页

作者： Kang Kai Wang Cong Luo Tao School of Software Engineering Beijing University of Posts and Telecommunications Key Laboratory of Trustworthy Distributed Computing and Service Beijing University of Posts Telecommunications School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts Telecommunications

Vehicular Ad-hoc networks（VANETs） are kinds of mobile Ad-hoc networks（MANETs）, which consist of mobile vehicles with on-board units（OBUs） and roadside units（RSUs）. With the rapid development of computation and communication technologies, peripheral or incremental changes in VANETs evolve into a revolution in process. Cloud computing as a solution has been deployed to satisfy vehicles in VANETs which are expected to require resources（such as computing, storage and networking）. Recently, with special requirements of mobility, location awareness, and low latency, there has been growing interest in research into the role of fog computing in VANETs. The merging of fog computing with VANETs opens an area of possibilities for applications and services on the edge of the cloud computing. Fog computing deploys highly virtualized computing and communication facilities at the proximity of mobile vehicles in VANET. Mobile vehicles in VANET can also demand services of low-latency and short-distance local connections via fog computing. This paper presents the current state of the research and future perspectives of fog computing in VANETs. Moreover, we discuss the characteristics of fog computing and services based on fog computing platform provided for VANETs. In this paper, some opportunities for challenges and issues are mentioned, related techniques that need to be considered have been discussed in the context of fog computing in VANETs. Finally, we discuss about research directions of potential future work for fog computing in VANETs. Within this article, readers can have a more thorough understanding of fog computing for VANETs and the trends in this domain.

关键词： VANET fog computing cloud computing application vehicular cloud computing

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A new routing and connectivity availability metric of low duty cycle random sleep scheduled multi-hop wireless sensor networks

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Journal of China Universities of Posts and Telecommunications 2011年第SUPPL.2期18卷 101-108页

作者： Zhang, Tian-Le Yuan, Yu-Yu Wu, Xu Luo, Zong-Wei Wang, Chun-Lu Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education Beijing University of Posts and Telecommunications Beijing 100876 China E-Business Technology Institute University of Hong Kong Hong Kong Hong Kong

Wireless sensor network (WSN) is attracting intensive interests in many application areas. In some scenarios such as monitoring of the coal-mining area or remote area, nodes seldom move and may switch from sleeping to waking mode to minimize power consumption. Energy conservation design for the network lifetime extension is the primary issue. By adopting sleep scheduling to keep low duty cycle can help reduce the energy consumption. Random sleep scheduling is a desirable mechanism for its simplicity and guaranteed stable low duty cycle. Moreover, the low duty cycle sleeping of nodes may destroy the connectivity of network. Most of existing WSN routing techniques are designed for fully connected networks assuming that the nodes of the routing path between source and destination are all available at the same time. Maintaining fully connected backbone involves high duty cycle and costly clock synchronization which consumes more energy. If certain delay is tolerant, partially connected routing can achieve successful packet forwarding in networks with the deficiency of connectivity. In this paper a new partially connected routing and simple random sleep scheduling scheme is proposed for WSN with low duty cycle. A continuous time Markov chains (CTMC) connectivity availability model is introduced to evaluate the end to end packet delivery ratio of multi-hop networks subjected to the impact of both frequent disconnection and random sleep latency. The proposed connectivity availability model can also be used as the key metric for route path selection to achieve stable and high performance. Deployment guidelines are given for WSN with random sleep scheduling policy satisfying reliability, timeliness and duty cycle requirements. By modeling and simulation, we find that as compared to the fully connected routing protocol, the partially connected routing design can achieve much higher packet delivery ratio and lower duty cycle within the tolerant delay. The computation and simul

关键词： Energy utilization

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PAUP: a pre-awareness insider threat detection method based on user psychoanalysis 9

PAUP: a pre-awareness insider threat detection method based ...

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9th International Symposium on Advances in Electrical, Electronics, and Computer Engineering, ISAEECE 2024

作者： Kong, Weiyu Li, Xiaoyong Yuan, Kaiguo Song, Yiyang Key Laboratory of Trustworthy Distributed Computing and Service Beijing University of Posts and Telecommunications Xitucheng Street Haidian District Beijing100876 China

ISBN: (纸本)9781510683303

Internal personnel within an organization often have privileged access to critical systems and sensitive information. They are familiar with the internal network structure, business processes, and security measures, which can lead to insider threats that are more insidious, long-term, destructive and diverse, posing a serious threat to enterprises and organizations. However, existing models for detecting insider threats primarily focus on modeling user behavior information but seldom take into account the valuable information from the psychological personality of insider personnel for threat detection. To address this limitation and better analyze the impact of user attributes on insider threats, a new direction for insider threat user analysis is proposed. This involves analyzing and visualizing the relationship between users' personalities and the execution of insider threat behaviors, using data analysis. Additionally, a decision tree model is constructed to realize insider threat detection based on user psychology, using feature_importance, a relative importance metric of features generated in the decision tree decision-making process, to judge the importance of different personality traits for insider threat detection. To further enhance the detection process, an insider threat user clustering method based on Fuzzy C-Means clustering is realized, and the groups are divided according to the user's psychological assessment scores to realize the early perceived localization of risky users. These approaches provide new ideas for finding new research directions in the field of insider threat. © 2024 SPIE.

关键词： Decision making

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Word activation forces-based language modeling and smoothing

Word activation forces-based language modeling and smoothing

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2013 5th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2013

作者： Qin, Min Liu, Gang Li, Baoxiang Lu, Yueming School of Information and Communication Engineering BUPT Beijing China Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education BUPT China

ISBN: (纸本)9780769550114

N-gram language models are useful for modeling the local dependencies of word occurrences but not for capturing global word dependencies. When the window size n is limited, the n-gram is weak in terms of capturing long distance dependencies. Long-distance Dependency information has long been proven useful in language model. However, the improved performance of long-distance LMs over conventional n-gram models generally comes at the cost of increased decoding complexity and model size. Word Activation Forces has been proven a simple and human-comparable accurate measure to identify word closest associates. In this paper, Word Activation Forces-Based language model is proposed to capture the long distance dependency between words, but which is as fast for decoding as a conventional word n-gram. As shown by experiments on broadcast news, the proposed language modeling and smoothing can significantly reduce the perplexity of language models and word error rate with moderate computational cost. © 2013 IEEE.

关键词： Decoding

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A Non-Statistical Reinstatement Algorithm for Orientation Field of Incomplete Fingerprint

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电子学报(英文版) 2012年第3期21卷 477-480页

作者： JING Xiaojun ZHANG Bo LIU Xinjing WANG Dong School of Infornation and Communication Engineering Beijing University of Posts and Telecommunications Beijing 100876 China Key Laboratory of Trustworthy Distributed Computing and Service (BUPT) Ministry of Education Beijing University o.f Posts and Telecommunications Beijing 100876 China

Fingerprint orientation is the key informa- tion in fingerprint enhancement and matching. Accord- ing to the problem of incomplete fingerprint orientation, a novel algorithm of fingerprint orientation reinstatement is proposed based on Local binary pattern (LBP) and mutual information function. Firstly, mutual information of finger- print orientation is computed. Secondly, the feature vec- tor is defined for incomplete area classification by Support vector machines (SVM). Then, the fingerprint orientation field of the incomplete area is re-computed and measured by LBP and mutual information function. For orientation reinstatement, LBP is used to measure the similarity of incomplete and complete area, while the mutual informa- tion function is used to measure correlation and compe- tition of the neighborhood. Additionally, fuzzy criterion is proposed to assign different weights for neighborhood block and incomplete block for modifying orientation. As a result, the modified fingerprint orientation is used for post-processing. And the performance is shown in the ex- perimental and proves the efficiency and reliability of our algorithm.

关键词：指纹图像增强方向场算法互信息函数统计支持向量机 LBP 二值模式

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IDEATE: Detecting AI-Generated Text using Internal and External Factual Structures 30

IDEATE: Detecting AI-Generated Text using Internal and Exter...

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Wang, Quan Zhang, Licheng Guo, Zikang Mao, Zhendong MOE Key Laboratory of Trustworthy Distributed Computing and Service Beijing University of Posts and Telecommunications Beijing China University of Science and Technology of China Hefei China

ISBN: (纸本)9782493814104

The effective detection of AI-generated text is a vital principle to ensure responsible use of large language models (LLMs). Previous studies mainly focused on discovering and utilizing internal evidences contained in the text itself to perform the detection, while ignoring external evidences implicated in an established knowledge graph (KG) which may also be key discriminative factors between AI-generated and human-written text. To address this deficiency, we propose IDEATE, a novel hierarchical graph network that utilizes both internal and external factual structures to detect AI-generated text. IDEATE consists of a mention-level subgraph at the bottom to describe internal factual structures of mentioned entities reflected in the input text, and an entity-level subgraph at the top to describe external factual structures of mentioned entities reflected in an external KG. Hierarchical graph convolution is then applied successively on the two subgraphs, through which the two types of factual structures will be embedded into the output and used for the final detection. Extensive experiments on four benchmarking datasets show that IDEATE consistently outperforms current state-of-the-art methods in detecting text generated by various LLMs, ranging from GPT-2 to the more powerful ChatGPT, verifying the necessity and superiority of introducing external evidences for AI-generated text detection. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Knowledge graph

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REINFORCEMENT LEARNING BASED TIME-DOMAIN MUTUAL INTERFERENCE AVOIDANCE FOR AUTOMOTIVE RADAR

REINFORCEMENT LEARNING BASED TIME-DOMAIN MUTUAL INTERFERENCE...

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IET International Radar Conference 2023, IRC 2023

作者： Xiao, He Wang, Jianping Li, Runlong He, Yuan Key Laboratory of Trustworthy Distributed Computing and Service Beijing University of Posts and Telecommunications Beijing China Faculty of EEMCS Delft University of Technology Delft Netherlands

ISBN: (纸本)9781839539954

Due to the extensive usage of automotive radars on vehicles, mutual interference among radars on the road is becoming considerable. To address this, we propose a time domain strategy based on deep reinforcement learning (DRL). This approach helps avoid mutual interference for automotive radars in the time domain without extra communications. The numerical simulation results demonstrate that the proposed approach can avoid interference as effectively as frequency hopping. Moreover, the time domain strategy has more advantages than frequency hopping when encountering dynamic interference. © The Institution of Engineering & Technology 2023.

关键词： Frequency hopping

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Exact analysis of transmit/receive zero-forcing based Mimo AF two-way relaying when relay has two antennas

Exact analysis of transmit/receive zero-forcing based Mimo A...

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International Conference on Cyberspace Technology, CCT 2013

作者： Li, Rongsheng Lv, Tiejun Lu, Yueming Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing 100876 China

ISBN: (纸本)9781849198011

In this paper, the performance of joint transmit/receive zero-forcing (ZF) is analyzed for multiple-input multiple-out (IV11MO) amplify-and-forward (AT) two-way relay network when the relay has two antennas. The performance is studied by deriving exact expressions of the overall outage probability and the diversity order under the uncorrelated Rayleigh fading channel and relay-corr elated Rayleigh fading channel as well. Analysis and simulation results indicate that, compared to uncorrelated Rayleigh fading, spatial correlation at the relay deteriorates the performance of the system greatly, but does not affect the diversity order of the system.

关键词： Antennas

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Research and Implementation of Trusted Data Collection Technology in Network Community 6

Research and Implementation of Trusted Data Collection Techn...

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6th Annual 2018 International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2018

作者： Wu, Xu Duan, Sishu Xie, Xiaqing Key Laboratory of Trustworthy Distributed Computing and Service BUPT China School of Cyberspace Security BUPT China Beijing University of Posts and Telecommunications Library China

This paper attempts to research and implement the data collection technology and trusted mechanism in network communities, and explore how to improve the reliability and credibility of the data collection process from multiple levels, providing reliable data sources for data analysis. © Published under licence by IOP Publishing Ltd.

关键词： Data acquisition

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A decomposition based multiobjective evolutionary algorithm for dynamic overlapping community detection 13th

A decomposition based multiobjective evolutionary algorithm ...

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13th International Conference on Bio-Inspired computing: Theories and Applications, BIC-TA 2018

作者： Wan, Xing Zuo, Xingquan Song, Feng School of Computer Science Beijing University of Posts and Telecommunications Beijing China Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education Beijing China

ISBN: (纸本)9789811328282

Dynamic and overlapping are common features of community structures of many real world complex networks. There are few studies on detecting dynamic overlapping communities, but those studies consider only single optimization objective. In practice, it is necessary to evaluate the community detection by multiple metrics to reflect different aspects of a community structure. In this paper, we propose a multi-objective evolutionary algorithm based approach for the problem of dynamic overlapping community detection, with consideration of three optimization objectives: partition density (D), the extended modularity (EQ), and the community smoothing (NMILFK). The dynamic overlapping network is regarded as a set of network snapshots. The multi-objective evolutionary algorithm based on decomposition (MOEA/D) is used to detect the communities for each snapshot. Experiments show that our approach can find uniformly distributed Pareto solutions for the problem and outperforms those comparative approaches. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Complex networks

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