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IEEE International Symposium on Network Coding

作者： Zhang, Minglong Li, Hui Chen, Fuxing Hou, Hanxu An, Huiyao Wang, Wei Huang, Jiaqing Shenzhen Key Lab. of Cloud Computing Tech. and Application Shenzhen Graduate School Peking Univ. 518055 China Dept. of Electronic and Information Engineering Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9781612841403

This paper presents a practical and general coder and decoder of network coding (NC) with HDL (Hardware Description Language) logic for wire-speed nodes in multisource multicast networks. The NC coders apply random linear network coding (RLNC) and the decoders recover the original packets by Cramer's rule. All these mathematical operations are carried out in the Galois Field (2 8). The structures and algorithms of NC coder and decoder were designed in detail and implemented in HDL with NetFPGA boards provided by Stanford University. Comparing with traditional stored-and-forward mechanism, network emulations showed that networks with wire-speed NC coder and decoder nodes could achieve the capacity bound of max-flow min-cut theorem in case of bottlenecks, and the end-to-end delay was guaranteed on a small constant. © 2011 IEEE.

关键词： Network coding

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A CUBIC-Based Explicit Congestion Control Mechanism in Named Data Networking

A CUBIC-Based Explicit Congestion Control Mechanism in Named...

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International Conference on Cyber-Enabled Distributed computing and Knowledge Discovery, CyberC

作者： Yongbin Liu Xuewei Piao Chaojun Hou Kai Lei Shenzhen Key Lab for Cloud Computing Technology & Applications Peking University SHENZHEN P.R.CHINA

ISBN: (纸本)9781509051557

As named data networking (NDN) continues to evolve into a mature and production network, a robust and efficient congestion control mechanism has become a fundamental requirement for the success and wide deployment of NDN. In this paper, upon exploring the unique hop-by-hop Interest forwarding feature, based on the CUBIC, we develop a novel congestion control mechanism for NDN. Our congestion control mechanism, namely EC-CUBIC, borrows the core idea of CUBIC to control the sending rate of interest packets on consumers. Specially, in routers, we queue the data packets in every face and according to the queue length to send a congestion signal to consumers, upon which consumers take action timely for the congestion. In addition, we implement this mechanism in ndnSIM, an NS3-based simulator, and conduct a number of experiments with various settings to evaluate the link utilization and packets-drop rate of the proposed algorithm. Comparing with the naive congestion control algorithm in NDN, our experimental results demonstrate that EC-CUBIC perform bette in terms of high link utilization and low packets-drop rate.

关键词： Algorithm design and analysis Face Downlink Bandwidth Topology Packet loss

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International Conference on Networking and Distributed computing (ICNDC)

作者： Kai Lei Qian Yu Rui Ning Shenzhen Key Lab for Cloud Computing Technology & Applications (SPCCTA) Peking University Shenzhen P.R. China

Smart Mobile device are becoming popular platforms for information accessing, especially when coupled with recommendation system technologies. They are also treated as key tools for mobile users both for leisure and business applications. Recommendation techniques can increase the usability of mobile systems by providing more personalized and interested content. In this paper, a novel personalized recommender system is proposed, focusing on Mobile Terminal (MT) similarities, such as brands, versions and types of Operating Systems. These similarities play a key role in filtering original recommendation data sets at the preprocessing stage. By calculating and comparing the Mean Absolute Error (MAE) values through 5-fold cross validation of the Slope One algorithm with/without optimizing data sets by device-similarity, the overall effectiveness and accuracy of the recommendation results are at least 20% improved in our experiment.

关键词： Mobile communication Context Mobile handsets Filtering Operating systems Educational institutions Collab.ration

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A Trust-Based Recommendation Model Constructed from Improved Page Rank Algorithm in a P2P Social Network

A Trust-Based Recommendation Model Constructed from Improved...

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2014 International Conference on Computer,Network Security and Communication Engineering(CNSCE 2014)

作者： Kai LEI Da-zhou QIN Kun ZHANG Shenzhen Key Lab for Cloud Computing Technology & Applications (SPCCTA) School of Electronics and Computer Engineering Peking University

With the rise of social networking in the web2.0 era, the Internet gradually evolves to be community-based [1]. The process of obtaining information via the Internet reflects certain social characteristics. In order to adapt recommendation technology to such changes, a trust-based recommendation algorithm is approached in this paper. The research is conducted in a practical application environment, a P2 P file-sharing system named Maze [2]. The algorithm is designed as follows: 1) digging download logs and friendship logs, 2) establishing trust-net social model. The empirical results show that the algorithm has improved recommendation quality significantly compared with the original content-based recommendation algorithm used in Maze.

关键词： Information filtering Personalization User behavior Trust mechanism Recommendation system

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MDPF: An NDN Probabilistic Forwarding Strategy based on Maximizing Deviation Method

MDPF: An NDN Probabilistic Forwarding Strategy based on Maxi...

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IEEE Global Communications Conference

作者： Kai Lei Jie Yuan Jiawei Wang Shenzhen Key Lab for Cloud Computing Technology and Applications (SPCCTA) School of Electronics and Computer Engineering Peking University

ISBN: (纸本)9781479959532

Forwarding strategy is the key feature of Named Data Networking (NDN) to realize dynamic, adaptive and intelligent forwarding, but work in this area is still at a very preliminary stage. In this paper, selecting which forwarding interface among multiple alternatives in NDN is defined as a multiple attribute decision making (MADM) problem and a maximizing deviation based probabilistic forwarding (MDPF) strategy is proposed to select forwarding interface on probability. Since multiple network metrics such as interface status, pending Interest numbers are considered together, each alternative interface's availab.lity is obtained more accurately. Thus, better content delivery efficiency can be achieved. In addition, MDPF provides good extensibility, as any appropriate metric can be added to enhance or customize it. We implement the proposal in ndnSIM and compare it with BestRoute and PI-based strategies under various topologies and scenarios. Experimental results show that MDPF strategy is more responsive and sensitive to network changes, and can realize higher throughput, lower drop rate as well as better load balance.

关键词： NDN gene Work area delivery efficiency

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Constructing Multiple Scene Graphs in Distributed Environment

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Computer Aided Drafting,Design and Manufacturing 2015年第1期25卷 16-21页

作者： XIA Rui WANG Guo-ping LI Sheng WANG Heng Shenzhen Key Lab for Cloud Computing Technology and Applications Shenzhen Graduate School of Peking University Graphics & Interaction Lab. School of Electronics Engineering and Computer SciencesPeking University Beijing Engineering Technology Research Center of Virtual Simulation and Visualization Peking University

Scene graph is a infrastructure of the virtual reality system to organize the virtual scene with abstraction, it can provide facility for the rendering engine and should be integrated effectively on demand into a real-time system, where a large quantities of scene objects and resources can be manipulated and managed with high flexibility and reliability. We present a new scheme of multiple scene graphs to accommodate the features of rendering engine and distributed systems. Based upon that, some other functions, e.g. block query, interactive editing, permission management, instance response, ＂redo＂ and ＂undo＂, are implemented to satisfy various requirements. At the same time, our design has compatibility to popular C/S architecture with good concurrent performance. Above all, it is convenient to be used for further development. The results of experiments including responding time demonstrate its good performance.

关键词： multiple scene graphs authority scene editing distributed systems

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A Practical Approach for Automatically Constructing Concept Map in E-learning Environments

A Practical Approach for Automatically Constructing Concept ...

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2014 IEEE International Conference on Progress in Informatics and computing

作者： Na Yi Hui Li Shenzhen Eng. Lab. of Converged Networks Technology Shenzhen Key Lab. of Cloud Computing Tech. and App Peking University Shenzhen Graduate School

With the prevalence of web-based learning, the application of concept mapping, as a powerful diagnostic and instructional tool, has been widely exploited in both education and computer science. In recent years, several methods have been presented toautomatically construct concept map that achieved encouraging results, while ignoring some critical issues when applied in actual E-learning system. In this paper,we propose a practical approach for constructing concept map,which is adapted tothe dynamic character of a real ***, we apply fuzzy set theory and fuzzy reasoning basis on fuzzy rules for similarity degree between twoconcepts, tofind direct prerequisite relationship among concepts. It provides a useful way toimprove accuracy and reduce complexity of the concept map.

关键词： concept map E-learning fuzzy set education

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IFS-RL: An intelligent forwarding strategy based on reinforcement learning in named-data networking

IFS-RL: An intelligent forwarding strategy based on reinforc...

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2018 ACM SIGCOMM Workshop on Network Meets AI and ML, NetAI 2018

作者： Zhang, Yi Xu, Kuai Bai, Bo Lei, Kai Shenzhen Key Lab for Cloud Computing Technology and Applications School of Electronic and Computer Engineering Peking University Shenzhen China School of Mathematical and Natural Sciences Arizona State University Arizona United States Future Network Theory Lab 2012 Labs Huawei Technologies Co. Ltd. Shatin N.T. Hong Kong

ISBN: (纸本)9781450359115

Named-Data Networking (NDN) is a new communication paradigm where network primitives are based on named-data rather than host identifiers. Compared with IP, NDN has a unique feature that forwarding plane enables each router to select the next forwarding hop independently without relying on routing. Therefore, forwarding strategies play a significant role for adaptive and efficient data transmission in NDN. Most of the existing forwarding strategies use fixed control rules based on simplified or inaccurate models of the deployment environment. As a result, existing schemes inevitably fail to achieve optimal performance across a broad set of network conditions and application demands. In this paper, We propose IFS-RL, an intelligent forwarding strategy based on reinforcement learning. IFS-RL trains a neural network model which chooses appropriate interfaces for the forwarding of Interest based on observations collected by routing node. Not relying on pre-programmed models, IFS-RL learns to make decisions solely through observations of the resulting performance of past decisions. Therefore, IFS-RL can implement intelligent forwrarding which adapt to a wide range of network conditions. Besides, we also researches the learning granularity and the enhancement for network topology change. We compare IFS-RL to state-of-the-art forwarding strategies in ndnSIM. Experimental results show that IFS-RL can achieve higher throughput and lower packet drop rates. © 2018 Association for computing Machinery.

关键词： Network topology

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An Entropy-based Probabilistic Forwarding Strategy in Named Data Networking

An Entropy-based Probabilistic Forwarding Strategy in Named ...

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IEEE International Conference on Communications

作者： Kai Lei Jiawei Wang Jie Yuan Institute of Big Data Technologies Shenzhen Key Lab for Cloud Computing Technology & Applications School of Electronics and Computer Engineering (SECE) Peking University

ISBN: (纸本)9781467364300

The forwarding strategy is the key to the resiliency and efficiency of Named Data Networking (NDN), which is a new and fundamental research area. For forwarding strategy, dynamically selecting an optimal interface from multiple alternative interfaces to forward an Interest packet is indeed a multiple attribute decision making (MADM) problem. In this paper, an entropy-based probabilistic forwarding (EPF) strategy is proposed to make a stochastic interface selection based on the combination of interfaces' dynamic availab.lities and static routing information, which achieves better load balance in comparison with deterministic interface selection. By objectively assigning weights to attributes and considering multiple real-time network condition metrics, EPF can obtain the availab.lities of interfaces more accurately and comprehensively. Since additional network metrics can be easily added and integrated into interfaces' assessment model, EPF provides good extensibility. In addition, we innovatively define two parameters (γ, δ) which can be used to trade off the effect factors between static routing information and dynamic running status of interfaces to customize EPF strategy for different network and application scenarios. Experiments show that EPF can realize preferable load balance and achieve higher throughput compared to the representative BestRoute forwarding strategy.

关键词： Entropy Throughput Routing Probabilistic logic Load modeling Packet loss

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Understanding Sina Weibo online social network: A community approach

Understanding Sina Weibo online social network: A community ...

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2013 IEEE Global Communications Conference (GLOBECOM)

作者： Kai Lei Kai Zhang Kuai Xu Shenzhen Key Lab for Cloud Computing Technology & Applications (SPCCTA) Peking University Shenzhen P.R. China School of Mathematical and Natural Sciences Arizona State University

ISBN: (纸本)9781479913510

Sina Weibo, one of the most popular online social networks in China, has recently become a critical medium for Internet users to disseminate and discuss breaking news, social events and other information. Although online social networks and social media have received significant attention from the research community, few studies have focused on Sina Weibo due to the lack of data collection. Given the sheer size of Sina Weibo online social network and vast amount of tweets, retweets and comments, this paper introduces a novel community approach for understanding Sina Weibo online social network. Specifically, we collect all Weibo users registered with shenzhen as primary geographic location, and build a shenzhen Weibo community graph based on their following or follower relationships. Our experimental results describe interesting graphical characteristics such as clustering coefficients of this community graph, and reveal the impact of user popularity on tweet influence. Through modeling interactions of shenzhen Weibo users and their tweeted messages with bipartite graphs and one-mode projections, we analyze the similarity of retweeting and commenting activities among these users, and discuss the implications of the findings on understanding different types of user accounts and the motivations of their following and retweeting behaviors. To the best of our knowledge, this study is the first effort to introduce a community approach for understanding the community characteristics of Sina Weibo and characterizing the similarity of retweeting behaviors and following relationships.

关键词： Communities Educational institutions Correlation Data collection Bipartite graph Twitter

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