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A key frame extraction algorithm oriented for video copy detection based on PCC and the histogram of video frames

Journal of Computational Information Systems 2014年第16期10卷 6999-7006页

作者： Peng, Fei Qian, Qin Long, Min College of Computer Science and Electronics Engineering Hunan University Changsha China Key Laboratory for Embedded and Network Computing of Hunan Province Changsha China College of Computer and Communication Engineering Changsha University of Science and Technology Changsha China

Aim to improve the accuracy and the robustness of the video copy detection, a novel key frame extraction algorithm is proposed. The shot segmentation is accomplished by evaluating the Pearsons correlation coefficients (PCC) between adjacent frames, while the key frames are extracted by combining the boundary-based and visual content-based methods. Experimental results show that the proposed key frame extraction algorithm is effective, and it is robust against some content preserving video processing attacks for some existed video hash methods. It provides a novel effective method for key-frames extraction in the video copy detection. 1553-9105/Copyright © 2014 Binary Information Press

关键词： Extraction

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STURE: Spatial-Temporal Mutual Representation Learning for Robust Data Association in Online Multi-Object Tracking

arXiv

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arXiv 2022年

作者： Wang, Haidong Li, Zhiyong Li, Yaping Nai, Ke Wen, Ming College of Computer Science Electronic Engineering of Hunan University Key Laboratory for Embedded and Network Computing of Hunan Province Hunan Province Changsha410082 China State Grid Hunan Electric Power Company Limited Economical Technical Research Institute Hunan Key Laboratory of Energy Internet Supply-demand and Operation Hunan Province Changsha410000 China

Online multi-object tracking (MOT) is a longstanding task for computer vision and intelligent vehicle platform. At present, the main paradigm is tracking-by-detection, and the main difficulty of this paradigm is how to associate current candidate detections with historical tracklets. However, in the MOT scenarios, each historical tracklet is composed of an object sequence, while each candidate detection is just a flat image, which lacks temporal features of the object sequence. The feature difference between current candidate detections and historical tracklets makes the object association much harder. Therefore, we propose a Spatial-Temporal Mutual Representation Learning (STURE) approach which learns spatial-temporal representations between current candidate detections and historical sequences in a mutual representation space. For historical trackelets, the detection learning network is forced to match the representations of sequence learning network in a mutual representation space. The proposed approach is capable of extracting more distinguishing detection and sequence representations by using various designed losses in object association. As a result, spatial-temporal feature is learned mutually to reinforce the current detection features, and the feature difference can be relieved. To prove the robustness of the STURE, it is applied to the public MOT challenge benchmarks and performs well compared with various state-of-the-art online MOT trackers based on identity-preserving metrics. Copyright © 2022, The Authors. All rights reserved.

关键词： E-learning

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Minimizing Schedule Length of Energy Consumption Constrained Parallel Applications on Heterogeneous Distributed Systems

Minimizing Schedule Length of Energy Consumption Constrained...

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

作者： Xiongren Xiao Guoqi Xie Renfa Li Keqin Li College of Computer Science and Electronic Engineering Hunan University China Key Laboratory for Embedded and Network Computing of Hunan Province China Department of Computer Science State University of New York USA

ISBN: (纸本)9781509032068

Energy consumption is one of the primary design constraints in heterogeneous parallel and distributed systems ranging from small embedded devices to large-scale data centers. The problem of minimizing schedule length of an energy consumption constrained parallel application has been studied recently in homogeneous systems with shared memory. To adapt the heterogeneity and distribution of high-performance computing systems, this study solves the problem of minimizing schedule length of an energy consumption constrained parallel application on heterogeneous distributed systems based on dynamic voltage and frequency scaling (DVFS) energy-efficient design technique. Such problem is decomposed into two sub-problems in this study, namely, satisfying energy consumption constraint and minimizing schedule length. The first sub-problem is solved by transferring the energy consumption constraint of the application to that of each task, and the second sub-problem is solved by heuristically scheduling each task with low time complexity. Experiments with Fast Fourier transform parallel applications show that not only the actual energy consumptions always do not exceed and are close to given energy consumption constraints, but also the minimum schedule lengths are generated by using the proposed algorithm.

关键词： Energy consumption Program processors Schedules Time-frequency analysis Processor scheduling Optimization Job shop scheduling

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Software-Defined Edge computing: A New Architecture Paradigm to Support IoT Data Analysis

arXiv

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arXiv 2021年

作者： Wu, Di Xie, Xiaofeng Nie, Xiang Fu, Bin Deng, Hanhui Zeng, Haibo Qin, Zhijin Key Laboratory for Embedded and Network Computing of Hunan Province Hunan University China Department of Electrical and Computer Engineering Virginia Tech United States EECS Queen Mary University of London United Kingdom

—The rapid deployment of Internet of Things (IoT) applications leads to massive data that need to be processed. These IoT applications have specific communication requirements on latency and bandwidth, and present new features on their generated data such as time-dependency. Therefore, it is desirable to reshape the current IoT architectures by exploring their inherent nature of communication and computing to support smart IoT data process and analysis. We introduce in this paper features of IoT data, trends of IoT network architectures, some problems in IoT data analysis, and their solutions. Specifically, we view that software-defined edge computing is a promising architecture to support the unique needs of IoT data analysis. We further present an experiment on data anomaly detection in this architecture, and the comparison between two architectures for ECG diagnosis. Results show that our method is effective and feasible. Copyright © 2021, The Authors. All rights reserved.

关键词： Edge computing

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Cyber-Physical Systems Design in An Uncertain Environment with Time Uncertainty Concern

Cyber-Physical Systems Design in An Uncertain Environment wi...

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International Conference on Parallel and Distributed Systems (ICPADS)

作者： Si Chen Lida Huang Xiongren Xiao Yan Liu Guoqi Xie Renfa Li College of Computer Science and Electronic Engineering Key Laboratory for Embedded and Network Computing of Hunan Province Hunan University Changsha China Center for Convergence of Automobile and Cyberspace Research Institute of Hunan University in Chongqing Chongqing China

Multiple processors system on chip (MPSoC) has been the trend in cyber-physical systems (CPSs), and reasonable partitioning for MPSoC resources is a critical step in CPSs design. The uncertainties of environment and time are both important factors that need to be considered in the design, but none of the previous work pays attention to two uncertainties at the same time. The state-of-the-art work presented a detailed process of applying uncertain programming to solve the partitioning problem, which provides a solution for designing in an uncertain environment. However, this work only considers the bipartition scenario which cannot be directly applied to MPSoC, and it does not focus specifically on time uncertainty. In this paper, we propose a method for modeling the MPSoC partitioning problem in an uncertain environment, with the time uncertainty concern. We present the uncertain model that can be applied to the multiple optional resources scenario. We build the optimization model with the objective of minimizing time, analyze two different cases of minimizing the uncertain time, and finally prove a unified deterministic model to solve. We come up with three algorithms, including the heuristic algorithm, the genetic algorithm, and the exact algorithm, and experiments show that the heuristic algorithm and the genetic algorithm can obtain good approximate solutions compared with the exact algorithm.

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Dynamic negotiation strategy based parallel-offer in cloud computing

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Journal of Computational Information Systems 2015年第10期11卷 3691-3699页

作者： Hu, Jun Xu, Ru Xiao, Deyu College of Computer Science and Electronics Engineering Hunan University Changsha China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China Key Laboratory for Embedded and Network Computing of Hunan Province Changsha China

Cloud computing can dynamically provide service based on service level agreements that between cloud services and consumers. Establish a viable and efficient dynamic negotiation strategy is one of hot research in cloud negotiation. This paper proposes a dynamic negotiation strategy based on parallel-offer under cloud computing environment, which combines dynamic concession strategy with parallel-offer tradeoff mechanism. The strategy can adjust negotiation strategy according to the supply demand relationship and tradeoff strategy of multi-issue, to achieve flexible and efficient cloud computing negotiation. This work firstly, establishes predicting market supply-demand relationship model, to build the dynamic concession strategy. Then on the base of above, introduces a parallel offer multi-issue tradeoff strategy into negotiation strategy, to achieve the dynamic concession tradeoff strategy (DCT). Finally, DCT mechanism is implemented in CloudSim test bed, and empirical results show DCT negotiation mechanism reach faster agreements and achieve higher utilities than other related approaches in cloud computing environment. ©, 2015, Binary Information Press. All right reserved.

关键词： Cloud computing

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CityGPT: Towards Urban IoT Learning, Analysis and Interaction with Multi-Agent System

arXiv

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arXiv 2024年

作者： Guan, Qinghua Ouyang, Jinhui Wu, Di Yu, Weiren Zhu, Yi Yuan, Xiang The Key Laboratory for Embedded and Network Computing of Hunan Province Hunan University Hunan Changsha410082 China The Department of Computer Science University of Warwick CoventryCV4 7AL United Kingdom

The spatiotemporal data generated by massive sensors in the Internet of Things (IoT) is extremely dynamic, heterogeneous, large scale and time-dependent. It poses great challenges (e.g. accuracy, reliability, and stability) in real-time analysis and decision making for different IoT applications. The complexity of IoT data prevents the common people from gaining a deeper understanding of it. Agentized systems help address the lack of data insight for the common people. We propose a generic framework, namely CityGPT, to facilitate the learning and analysis of IoT time series with an end-to-end paradigm. CityGPT employs three agents to accomplish the spatiotemporal analysis of IoT data. The requirement agent facilitates user inputs based on natural language. Then, the analysis tasks are decomposed into temporal and spatial analysis processes, completed by corresponding data analysis agents (temporal and spatial agents). Finally, the spatiotemporal fusion agent visualizes the system’s analysis results by receiving analysis results from data analysis agents and invoking sub-visualization agents, and can provide corresponding textual descriptions based on user demands. To increase the insight for common people using our framework, we have agnentized the framework, facilitated by a large language model (LLM), to increase the data comprehensibility. Our evaluation results on real-world data with different time dependencies show that the CityGPT framework can guarantee robust performance in IoT computing. Copyright © 2024, The Authors. All rights reserved.

关键词： Internet of things

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RTISM: Real-Time Inter-VM Communication Based on Shared Memory for Mixed-Criticality Flows

RTISM: Real-Time Inter-VM Communication Based on Shared Memo...

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Real-Time Systems Symposium (RTSS)

作者： Zonghong Li Guoqi Xie Wenhong Ma Xiongren Xiao Yong Xie Wei Ren Wanli Chang Key Laboratory for Embedded and Network Computing of Hunan Province College of Computer Science and Electronic Engineering Hunan University China Research Institute of Hunan University in Chongqing China Nanjing University of Posts and Telecommunications China Huawei Technologies China

Virtual machines (VMs) have been increasingly deployed in real-time systems to enhance heterogeneous resource sharing. Despite being isolated for security and prevention of failure propagation, VMs need to communicate with each other to complete certain tasks jointly. A real-time inter-VM communication framework has been proposed based on VirtIO, which is in essence a mechanism of message passing with high latency and low scalability on data amount. In contrary, IVSHMEM implements inter-VM communication with shared memory, which is generally fast and large in throughput. Unfortunately, IVSHMEM does not resolve resource contention between flows and hence cannot be applied in real-time scenarios. In this work, we propose a real-time inter-VM communication framework RTISM built upon shared memory and IVSHMEM. RTISM provides priority-based scheduling and supports mixed-criticality flows. Worst-Case Response Time (WCRT) analysis is reported to bound the end-to-end communication delay and a Limited Priority Assignment (LPA) algorithm is developed to enhance schedulability. Experimental evaluation shows that (i) RTISM has about 4 times higher throughput than the VirtIO-based inter-VM communication framework; (ii) LPA improves schedulability by over 25% compared to the state-of-the-art; (iii) WCRT produces a tight bound.

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RELIABILITY-DRIVEN REAL-TIME TASK REPLICATION FOR FAULT TOLERANCE IN HIERARCHICAL SCHEDULING MULTIPROCESSOR SYSTEMS

RELIABILITY-DRIVEN REAL-TIME TASK REPLICATION FOR FAULT TOLE...

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2013IET International Conference on Information and Communication Technologies(IETICT2013)2013IET信息与通信技术国际会议

作者： Lin Liu Renfa Li Rui Li Yong Xie Qingguang Zeng Key Laboratory for Embedded and Network Computing of Hunan Province Hunan UniversityChangshaChina

ISBN: (纸本)9781629931357

The increasing complexity of systems poses a big challenge to design systems with fault-tolerant *** aim of this study was to establish fault-tolerant system for multiprocessor platform with the help of hierarchical scheduling framework.A mathematical fault and reliability model for hierarchical scheduling framework was proposed firstly,and then a heuristic algorithm by exploiting the difference of task resource overhead and the probability of task failures was presented and a task replication scheme was given *** experimental results demonstrated the proposed scheme could effectively guarantee reliability goal and reduce resource consumption simultaneously.

关键词： multiprocessor fault tolerance task replication reliability requirements the hierarchical scheduling

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A Real-Time CAN-CAN Gateway with Tight Latency Analysis and Targeted Priority Assignment

A Real-Time CAN-CAN Gateway with Tight Latency Analysis and ...

引用

Real-Time Systems Symposium (RTSS)

作者： Guoqi Xie Haijie Gong Yunbo Han Samarjit Chakraborty Wanli Chang College of Computer Science and Electronic Engineering Hunan University China Key Laboratory for Embedded and Network Computing of Hunan Province China Future Network Lab CSIG Tencent China University of North Carolina at Chapel Hill USA University of York UK

ISBN: (数字)9781728183244

ISBN: (纸本)9781728183251

There is a demand in the automotive industry to connect two CAN-based subsystems. The commercial CAN-CAN gateway supports basic message forwarding with no real-time behavior. To address this issue, a new gateway architecture is described, on which we present a novel worst-case latency analysis. Specifically, we bound the arrival of the messages at the gateway, which is then used by the Pointer Reachability Exploration (PRE) to derive the interfering message jobs. Our analysis computes a safe gateway latency tighter than the conventional one applied in CAN. Furthermore, we propose a Targeted Priority Assignment (TPA) algorithm that targets at the priorities assigned at the CAN bus and runs a reordering at the gateway to enhance the schedulability. TPA performs better than DMPO (Deadline Monotonic Priority Ordering), while OPA (Audsley's Optimal Priority Assignment) cannot be applied in this context. Evaluation over real-life and scalable CAN message sets is conducted. The reported analysis and priority assignment algorithm are developed for dynamic use to improve the acceptance ratio and can also be deployed statically to provide timing guarantees. This work can be easily extended to support multiple CAN subsystems.

关键词： Heuristic algorithms Prototypes Computer architecture Logic gates Real-time systems Timing Vehicle dynamics

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