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Prefetching-based Adaptive Video Streaming Strategy on Edge computing 29

Prefetching-based Adaptive Video Streaming Strategy on Edge ...

引用

29th IEEE international conference on parallel and distributed Systems, ICPADS 2023

作者： Yi, Xuanyu Zhou, Jipeng Jinan University Department of Computer Science Guangzhou China Jinan University School of Data Science of Guangzhou Huashang College Department of Computer Science Guangzhou China

ISBN: (纸本)9798350330717

Dynamic Adaptive Streaming over HTTP (DASH) is a widely adopted video streaming protocol. Adaptive Bitrate Streaming (ABR) algorithm is utilized to dynamically switch between different bitrates. However, traditional ABR algorithms have gradually failed to meet users' demands for high-quality video transmission, especially in complex network environments. Thus, the current research focus has shifted towards enhancing the accuracy of algorithm. The advent of edge computing has brought new possibilities for DASH transmission. Edge computing-based algorithms can make decisions from a more macroscopic perspective, which can enhance algorithm efficiency. In this paper, we propose an edge computing-based strategy that enables the edge server to obtain the actual file size of the next segment at every bitrate. As a result, edge servers can obtain more informations. We further propose an edge-based system model that assists the ABR algorithm in achieving better operational efficiency. With additional information, the algorithm located at the edge node possesses the capability to make more precise decisions, which is advantageous for enhancing the quality of experience (QoE) for users. Our experiments demonstrate that the proposed strategy can significantly enhance QoE and network resource utilization. © 2023 IEEE.

关键词： DASH Edge computing Video Streaming

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TPTO: A Transformer-PPO based Task Offloading Solution for Edge computing Environments 29

TPTO: A Transformer-PPO based Task Offloading Solution for E...

引用

29th IEEE international conference on parallel and distributed Systems, ICPADS 2023

作者： Gholipour, Niloofar De Assuncao, Marcos Dias Agarwal, Pranav Gascon-Samson, Julien Buyya, Rajkumar Univ. of Quebec Dept. of Software Engineering and IT École de Technologie Supérieure Montreal Canada The Univ. of Melbourne CLOUDS Lab School of Computing and Information Systems Australia

ISBN: (纸本)9798350330717

Emerging applications in healthcare, autonomous vehicles, and wearable assistance require interactive and low-latency data analysis services. Unfortunately, cloud-centric architectures cannot fulfill the low-latency demands of these applications, as user devices are often distant from cloud data centers. Edge computing aims to reduce the latency by enabling processing tasks to be offloaded to resources located at the network's edge. However, determining which tasks must be offloaded to edge servers to reduce the latency of application requests is not trivial, especially if the tasks present dependencies. This paper proposes a Deep Reinforcement Learning (DRL) approach called TPTO, which leverages Transformer Networks and Proximal Policy Optimization (PPO) to offload dependent tasks of IoT applications in edge computing. We consider users with various preferences, where devices can offload computation to an edge server via wireless channels. Performance evaluation results demonstrate that under fat application graphs, TPTO is more effective than state-of-the-art methods, such as Greedy, HEFT, and MRLCO, by reducing latency by 30.24%, 29.61%, and 12.41%, respectively. In addition, TPTO presents a training time approximately 2.5 times faster than an existing DRL approach. © 2023 IEEE.

关键词： Edge computing reinforcement learning task offloading Transformers

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Containerized Data-Flow Processing for Scalable Real-Time Analytics on Edge Devices 25th

Containerized Data-Flow Processing for Scalable Real-Time A...

引用

25th international conference on parallel and distributed computing, Applications and Technologies, PDCAT 2024

作者： HoseinyFarahabady, MohammadReza Y. Zomaya, Albert School of Computer Science Center for Distributed and High Performance Computing The University of Sydney SydneyNSW2006 Australia

ISBN: (纸本)9789819642069

The increasing demand for real-time data analysis in Internet of Things (IoT) ecosystems has created several challenges, particularly in environments where resources are limited, and minimizing data processing latency is critical. This paper investigates the use of Linux Containerization (LXC) as a lightweight, resource-efficient alternative to traditional virtual machine managers for accelerating data-flow processing applications. We propose an architecture that integrates Linux Containerization (LXC) with a Proportional-Integral-Derivative (PID) controller to dynamically manage I/O resource allocation, ensuring Quality of Service (QoS) for I/O-intensive data analytics workloads. The proposed PID controller continuously monitors system performance and dynamically adjusts I/O resource allocation to mitigate performance degradation. Through a series of experiments, we demonstrate that LXC-based solutions outperform traditional methods in managing I/O-intensive data analytics workloads in IoT and edge ecosystems. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Quality of service

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Research and Application of High Interaction Deception Defense and Traceability Based on RASP Technology 2

Research and Application of High Interaction Deception Defen...

引用

2nd international conference on Mobile Internet, Cloud computing and Information Security (MICCIS)

作者： Sun, Qiang Fan, Chunlei Zhang, Weichang Chen, Jianfei Wang, Huayang Zhang, Rui Wendeng Dist Power Supply Co State Grid Shandong Elect Power Co Weihai Weihai Shandong Peoples R China Power Supply Co State Grid Shandong Elect Power Co Weihai Weihai Shandong Peoples R China Power Supply Co State Grid Shandong Elect Power Co Jinan Jinan Shandong Peoples R China

ISBN: (纸本)9798350389913;9798350389906

This article explored a high interaction deception defense mechanism based on RASP (runtime application self-protection) technology and its application in network attack tracing. Traditional network security defense methods face some limitations, such as insufficient detection of complex attack patterns and difficult traceability. The purpose of this study was to enhance defense capabilities and improve the tracking efficiency of attack sources by integrating RASP technology and high interaction deception strategies. The experimental study demonstrated the potential of this comprehensive method in real-time attack detection, response, and traceability, and its effectiveness was verified through experiments. This study comprehensively evaluated the performance of a high interaction deception defense and traceability system based on RASP technology through three experiments during the research phase. In the first experiment, defense effectiveness tests against SQL (structured query language) injection, XSS (cross site scripting), and DDoS (distributed denial of service) attacks showed that the system exhibited high detection rates of 95%, 90%, and 92%, respectively, with response times of 0.3 seconds, 0.5 seconds, and 0.4 seconds, and false alarm rates maintained at a low level of 2%-4%. In the second experiment, the evaluation of interaction effects on different types of honeypots showed that high interaction honeypots were the most effective in attracting attackers, with an average dwell time of 30 minutes and 10 interaction operations, far exceeding other types of honeypots. Finally, the accuracy and speed testing of traceability revealed the traceability ability of the system under different types of attacks. Among them, the traceability accuracy of malicious software attacks was the highest, reaching 95%, but the longest required time was 50 seconds;the traceability accuracy of fishing attacks was 85%, taking 45 seconds. The above data conclusions collectively de

关键词： Network Security RASP Technology High Interaction Honeypot Attack Detection Deception Defense

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Integrating interactive performance analysis in Jupyter Notebooks for parallel programming education

Integrating interactive performance analysis in Jupyter Note...

引用

1st international conference on Smart Energy Systems and Artificial Intelligence (SESAI)

作者： Oden, Lena Noelp, Klaus Brauner, Philipp Univ Hagen Comp Engn Hagen Germany Rhein Westfal TH Aachen Human Comp Interact Ctr Aachen Germany

ISBN: (纸本)9798350364613;9798350364606

Understanding the performance behavior of parallel applications is important in many ways, but doing so is not easy. Most open source analysis tools are written for the command line. We are building on these proven tools to provide an interactive performance analysis experience within Jupyter Notebooks when developing parallel code with MPI, OpenMP, or both. Our solution makes it possible to measure the execution time, perform profiling and tracing, and visualize the results within the notebooks. For ease of use, it provides both a graphical JupyterLab extension and a C++ API. The JupyterLab extension shows a dialog where the user can select the type of analysis and its parameters. Internally, this tool uses Score -P, Scalasca, and Cube to generate profiling and tracing data. This tight integration gives students easy access to profiling tools and helps them better understand concepts such as benchmarking, scalability and performance bottlenecks. In addition to the technical development, the article presents hands-on exercises from our well-established parallel programming course. We conclude with a qualitative and quantitative evaluation with 19 students, which shows a positive effect of the tools on the students' perceived competence.

关键词： Jupyter parallel programming performance analysis interactive programming high perfonnance computing

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Research and Pilot Application of Visual Detection Method for Phase Distance Between Transformer Bushings Based on Binocular Stereo Vision 4

Research and Pilot Application of Visual Detection Method fo...

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4th international conference on Information Science, parallel and distributed Systems, ISPDS 2023

作者： Sun, Xiaqing Zhao, Jielin Zhu, Junlin Li, Hao Huang, Kejie Shen, Wang Luo, Zhiyuan Ji, Zhefu Electric Power Research Institute China Southern Power Grid Guangzhou China Shenzhen Power Supply Co. Ltd. Shenzhen China

ISBN: (纸本)9798350337181

This article proposes a method for detecting the distance between power transformer bushings based on binocular stereo vision, which utilizes the Grabcut image segmentation algorithm to achieve intelligent segmentation of the bushing. Based on the principle of binocular vision, visual measurement of the distance between sleeves is achieved. Finally, this article establishes a pilot application appearance model and verifies the feasibility of this method through simulation experiments. © 2023 IEEE.

关键词： Power transformers

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FedSKG: Self-supervised Federated Learning with Structural Knowledge of Global Model 29

FedSKG: Self-supervised Federated Learning with Structural K...

引用

29th IEEE international conference on parallel and distributed Systems, ICPADS 2023

作者： Li, Jun Luo, Dan Wei, Kang Mei, Zhen Shao, Yumeng Nanjing University of Science and Technology School of Electronic and Optical Engineering Nanjing China The Hong Kong Polytechnic University Department of Computing Hong Kong Hong Kong

ISBN: (纸本)9798350330717

Federated self-supervised learning (FedSSL) is an emerging method in the domain of machine learning. It collaboratively learns a powerful feature extractor among multiple participants by utilizing distributed unlabeled data. However, conventional FedSSL suffers from statistical heterogeneity due to the non-independent and identically distributed (Non-IID) data among participants. In this work, we introduce a novel method to tackle the Non-IID data issue in FedSSL. First, the relation knowledge distillation is utilized to enhance the learning from global models. Then, we dynamically update the local model with divergence-aware update (DAU) method to preserve the client's knowledge of Non-IID data. Our experimental results demonstrate that the proposed approach outperforms other methods by up to 8% on linear evaluation, verifying the effectiveness of our approach. © 2023 IEEE.

关键词： Federated self-supervised learning knowledge distillation non-independent and identically distributed

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A Load Balancing Model for parallel Simulation of Fluid-Structure Interaction in Cavitating Flow 23

A Load Balancing Model for Parallel Simulation of Fluid-Stru...

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4th international conference on computing, Networks and Internet of Things, CNIOT 2023

作者： Liu, Qiao Li, Chao Liu, Jie Guo, Xiaowei Zhang, Sen Zhang, Huajian Xu, Hanwen School of Computer Science and Technology National University of Defense Technology Changsha China

ISBN: (纸本)9798400700705

Load unbalancing problem has a significant impact on the parallel efficiency of fluid-structure interaction simulation in cavitating flow. When the total parallelism is determined, the speedup will be seriously affected by the distribution of cores for the fluid solver and solid solver. This paper proposes an adaptive-λ load balancing model to maximally achieve the optimal parallel efficiency by generating a proper distribution scheme for the participant solvers. Our model is an optimization of the Kannan's method, which changes the original fixed-value λ to an adaptive one. Specific formulas are set up by a series of liner fittings and the parameter λ is calculated by a function of grid scale and parallel scale. A parallel FSI platform for cavitating flow based on preCICE is constructed to verify the present model. Experiments show that, compared with the traditional Kannan model, the adaptive-λ model could perform better parallel speedup and achieve wider application scope. This could help give a guidance on parallel decomposition for each participant solver in FSI applications. © 2023 ACM.

关键词： Fluid structure interaction

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Fine-grained Calculation Method of Accepting distributed Generation Capacity in Distribution Network for Virtual Power Plant 6

Fine-grained Calculation Method of Accepting Distributed Gen...

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6th IEEE international Electrical and Energy conference, CIEEC 2023

作者： Zhong, Yongjie Ji, Ling Jiang, Yanjun Li, Jingxia Wang, Zidong Wang, Yong Guodian Nanjing Automation Co. Ltd Nanjing211153 China

ISBN: (纸本)9798350346671

The fine-grained calculation method of accepting distributed generation capacity in distribution network for virtual power plant is proposed in this paper. Firstly, a distributed generation capacity model including photovoltaic power generation and wind power generation are established based on the collection of virtual power plant information. Secondly, distribution network power flow model on power grid side, and distributed power generation output model on power supply side including photovoltaic generation model and wind power generation model are established. Thirdly, the fine-grained safe operation constraints including power supply side and power grid side are set. Then, the optimal coordinated scheduling model of acceptability of new energy distributed generation with adjustable importance factor setting mode is proposed. Finally, output virtual power plant information through optimal coordinated scheduling, and reverse determine the actual photovoltaic and wind power installed capacity selection. The proposed model and method can provide theoretical guidance and reference for the fine modeling of distributed generation capacity accepted by the distribution network of virtual power plant, fine-grained computing application, actual installed capacity selection of distributed generation, multi-mode coordinated scheduling and so on. © 2023 IEEE.

关键词： Virtual Power Plants

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Application research of time-slot task synchronization method based on timestamp counter polling in electromagnetic transient real-time simulation 6

Application research of time-slot task synchronization metho...

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6th international conference on Information Science, Electrical, and Automation Engineering, ISEAE 2024

作者： Guo, Qi Lu, Yuanhong Guo, Tianyu Zhang, Jie Huang, Libin Tu, Liang Guo, Zhilong Xu, Dehuai Guo, Chuang State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangzhou China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou China CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou China Dawning Network Technology Corp. Ltd. Wuhan China

ISBN: (纸本)9781510682924

In the practical application of electromagnetic transient real-time simulation computing platform, due to the large amount of calculation and long calculation time of electromagnetic transient simulation calculation, in order to improve the calculation speed and accuracy, it is usually necessary to use multiple CPU cores for parallel calculation at the same time, and ensure that each task synchronization and coordination among the computing cores. So, it is of great significance to select an appropriate task synchronization method for the realization of the electromagnetic transient real-time simulation computing platform. The paper puts forward a kind of based on TSC (Time Stamp Counter) Time Stamp Counter polling Time slot task synchronization method, this method supports high precision Time synchronization and coordination between different tasks, and can adapt to the transmission and efficient processing of large amounts of data. The test results prove that this method can avoid the overhead and delay of a large number of interrupts and thread switching, improve the efficiency, stability and predictability of task execution, and meet the performance requirements of the task synchronization method based on the centralized tightly coupled electromagnetic transient real-time simulation prototype. © 2024 SPIE.

关键词： Electromagnetic transients

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