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2020 International Conference on 5G Mobile Communication and Information Science, MCIS-5G 2020

作者： Tianmin, Xiong Xiaochun, Lei Xingwen, Zheng Junyan, Chen Yizhou, Feng School of Computer and Information Security Guilin University of Electronic Technology Guilin541004 China Guangxi Colleges and Universities Key Lab. of Intelligent Processing of Computer Images and Graphics Guilin541004 China Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guilin University of Electronic Technology Guilin541004 China

Due to the limitation of hardware resources, the traditional people flow monitoring system based on computer vision in public places can't meet different crowd-scale scenarios. Therefore, a people flow monitoring system based on MD-MCNN algorithm is designed, which is an application system combining the improved SSD object detection algorithm MNSSD and MCNN density map regression algorithm. In the initial stage, the system uses MNSSD for accurate detection and counting. If the people flow gradually reaches a certain threshold, the system automatically uses MCNN to estimate people flow until the people flow falls below the threshold. Through the experimental verification, the system can realize the people flow statistics of low-density and high-density people in different scenarios, and can be applied on the existing embedded platform. This scheme can be extended to smart cities, smart scenic spots, smart transportation and other fields. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Object detection

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Design of Intelligent Robot Platform based on Multi-sensor Fusion

Design of Intelligent Robot Platform based on Multi-sensor F...

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2020 International Conference on 5G Mobile Communication and Information Science, MCIS-5G 2020

作者： Dajin, Ya Xiaochun, Lei Yue, Li Junyan, Chen Rongcun, Huang Lin, Lan School of Computer and Information Security Guilin University of Electronic Technology Guilin541004 China Guangxi Colleges and Universities Key Lab. of Intelligent Processing of Computer Images and Graphics Guilin541004 China Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guilin University of Electronic Technology Guilin541004 China

The mobile robot adapts to the more complicated indoor and outdoor environments, and can expand its scope of application. In order to reduce the influence of the cumulative error caused by navigation in complex environments, the indoor mobile robot that combines Inertial Measurement Unit (IMU) and encoder fusion is designed and implemented. In view of the limitations of the traditional single lidar scheme, a Multi-sensor Fusion scheme is proposed to achieve indoor map construction, path planning, multi-point navigation and other functions, and a MSIF KartoSLAM (Multi-sensor Information Fusion) algorithm is proposed, which combines the KartoSLAM algorithm and Multi-sensor information to achieve map construction in complex environments. Through comprehensive testing in the indoor environment, the results show that the Multi-sensor Fusion scheme is superior to the traditional single lidar scheme, and can achieve higher accuracy in mapping and navigation. At the same time, the robot platform can also be combined with the Internet of Things technology and integrated into intelligent housing system. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Navigation

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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 availabilities 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 availabilities 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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HoPP: Hardware-Software Co-Designed Page Prefetching for Disaggregated Memory

HoPP: Hardware-Software Co-Designed Page Prefetching for Dis...

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IEEE Symposium on High-Performance Computer Architecture

作者： Haifeng Li Ke Liu Ting Liang Zuojun Li Tianyue Lu Hui Yuan Yinben Xia Yungang Bao Mingyu Chen Yizhou Shan Chinese Academy of Sciences State Key Lab of Processors Institute of Computing Technology University of Chinese Academy of Sciences Huawei Technologies Huawei Cloud

Memory disaggregation is a promising direction to mitigate memory contention in datacenters. To make memory disaggregation practical, prior efforts expose remote memory to applications transparently via virtual memory subsystem’s swapping interface. However, due to the semantic gap between OS and applications – OS cannot know the memory accessing sequences of an application but via page faults. This approach has two limitations. First, it learns little from page faults’ access history, which leads to sub-optimal prefetching predictions. Second, a page fault can still occur even if there is a prefetch-hit which leads to a large kernel *** address such limitations, our key insight is to decouple the address capturing from page faults by collecting full memory access traces in the memory controller. Using this idea, we build HoPP – a hardware-software co-designed prefetching framework. HoPP adds hardware modules to the memory controller to feed sufficient hot pages to OS in real-time, which has three benefits in HoPP ’s software design: 1) it improves existing prefetching algorithms with simple revamps, also offers more insights to build better policies; 2) the prefetch algorithm can run as a separate data path alongside the normal remote data path via page faults, potentially hiding the swap latency from applications, and enabling fine-grained control over prefetching behaviors; 3) the prefetch-hit overhead can be eliminated by early page table entry (PTE) injection, i.e., inject PTE for the prefetched page as soon as it returns. We implemented a proof-of-concept prototype using commodity servers along with a hardware-based memory tracking tool called HMTT to emulate a modified memory controller. Results show that compared to Fastswap and Leap, HoPP -optimized prefetching algorithm achieves over 90% accuracy and coverage, which leads to up to 59% completion time improvement for various datacenter applications.

关键词： Software design Prefetching Software algorithms Semantics Prototypes Real-time systems Hardware

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A computer-supported collaborative learning platform based on clouds

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Journal of Computational Information Systems 2011年第11期7卷 3811-3818页

作者： Li, Jiandun Peng, Junjie Zhang, Wu Han, Fangfang Yuan, Qin Joint Lab of Cloud Computing School of Computer Engineering and Science Shanghai University Shanghai 200072 China Key Laboratory of Computer System and Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China

Computer-supported collaborative learning (CSCL) is an emerging branch of learning science concerned with studying how people can learn together with the help of computers. As an indispensable ingredient, computer mediation evolves through couples of phases, e.g. centralized server, peer-to-peer network, grid computing. Nevertheless, with daily rising trend on requirement's dynamic changes in service, existing models fall short to respond on demand. Thus, in this paper, by taking advantage of cloud computing, we propose a feasible CSCL platform and the experiments show that it can not only fulfill the basic requirement of CSCL, but also respond to learner's dynamic need on demand. Copyright © 2011 Binary Information Press.

关键词： Peer to peer networks

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Uncertainty-aware complementary label queries for active learning

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Frontiers of Information technology & Electronic Engineering 2023年第10期24卷 1497-1503页

作者： Shengyuan LIU Ke CHEN Tianlei HU Yunqing MAO Key Lab of Intelligent Computing Based Big Data of Zhejiang Province Zhejiang UniversityHangzhou 310027China State Key Laboratory of Blockchain and Data Security Zhejiang UniversityHangzhou 310027China City Cloud Technology(China)Co. Ltd.Hangzhou 310000China

Many active learning methods assume that a learner can simply ask for the full annotations of some training data from *** methods mainly try to cut the annotation costs by minimizing the number of annotation ***,annotating instances exactly in many realworld classification tasks is still *** reduce the cost of a single annotation action,we try to tackle a novel active learning setting,named active learning with complementary labels(ALCL).ALCL learners ask only yes/no questions in some *** receiving answers from annotators,ALCL learners obtain a few supervised instances and more training instances with complementary labels,which specify only one of the classes to which the pattern does not *** are two challenging issues in ALCL:one is how to sample instances to be queried,and the other is how to learn from these complementary labels and ordinary accurate *** the first issue,we propose an uncertainty-based sampling strategy under this novel setup.

关键词： complementary instance ordinary

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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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Impact of HTTP Pipelining Mechanism for Web Browsing Optimization

Impact of HTTP Pipelining Mechanism for Web Browsing Optimiz...

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IEEE International Conference on Mobile Services (MS)

作者： Kai Shuang Tong Zhang Zhenjiang Dong Peng Xu State Key Lab of Networking & Switching Technology Beijing University of Posts & Telecommunications Beijing China ZTE cloud computing & IT Research Institute Nanjing China

With the rapid development and popularization of Web technology, how Web applications can be accessed quickly by users has become a concern in all Web application developers. At present, the optimization of the HTTP protocol is considered a mainstream method to achieve maximum generality Web acceleration. Among the optimization techniques, HTTP pipelining technology optimizes the traditional mechanisms of HTTP protocol interaction, resulting in a dramatic improvement in page load time. In this paper, the formulae for calculating page load time under four kinds of HTTP request contrast mechanisms were deduced by mathematical modeling. Then in order to accurately assess the impact of pipelining mechanism for web browsing optimization, the simulation of network protocol is carried out with different network environments and page features. Finally based on these results, some recommendations of HTTP pipelining configuration under different conditions are given.

关键词： Pipeline processing Delays Servers Browsers Load modeling Optimization Bandwidth

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Threshold-Based Secure and Privacy-Preserving Message Verification in VANETs

Threshold-Based Secure and Privacy-Preserving Message Verifi...

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IEEE International Conference on Trust, Security and Privacy in computing and Communications (TrustCom)

作者： Wei Gao Mingzhong Wang Liehuang Zhu Xiaoping Zhang Language Information Processing and Cloud Computing Application Beijing Institute of Technology National Key Lab of Vehicular Transmission China North Vehicle Research Institute

ISBN: (纸本)9781479965144

Messages spreading inside vehicular ad hoc networks (VANETs) generally need to achieve the property of verifiability and content integrity, while preserving user privacy. Otherwise, VANETs will either fall into chaos, or prevent users from embracing it. To achieve this goal, we propose a protocol, which contains a priori and posteriori countermeasures, to guarantee these features. The a priori process firstly verifies that each message is sent by a vehicle only once. Then it collects and checks whether the count of the message exceeds the threshold value to improve the trustworthiness of the message. The posteriori process verifies the integrity of the message, ensuring it is unchanged during transmission between the vehicle and the road side unit. The privacy is preserved by applying group signature. In case of disruptive events, the proposed solution can trace back to the source vehicle which generates the message.

关键词： Vehicles Privacy Authentication Protocols Public key Servers

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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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