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DeTAR: A Decision Tree-Based Adaptive Routing in networks-on-Chip 29th

DeTAR: A Decision Tree-Based Adaptive Routing in Networks-on...

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29th international conference on parallel and distributed computing (Euro-Par)

作者： Zhang, Xiaoyun Wang, Yaohua Dong, Dezun Li, Cunlu Wang, Shaocong Xiao, Liquan Natl Univ Def Technol Changsha Hunan Peoples R China

ISBN: (纸本)9783031396977;9783031396984

The deployment of heuristic algorithms is extensively utilized in the routing policy of networks-on-Chip (NoCs). However, the escalating complexity and heterogeneity of multi-core architectures present a formidable task for human-designed efficient heuristic routing policies. Although recent works have exhibited that machine learning (ML) can learn efficacious routing policies that surpass human-designed heuristics in simulation, the intricate design and costly hardware overhead of ML-based routing algorithms preclude their practical application in NoCs. In this paper, we propose a Decision Tree-based Adaptive Routing algorithm, DeTAR, which is effective yet simple. The key insight of DeTAR is that routing decisions can be treated as selecting and prioritizing the key features among various NoCs' metrics like free Virtual Channels (VCs), the buffer length, etc., that better affect the routing decision. This reveals a natural match between the adaptive routing algorithm and the Decision Tree (DT) model. We trained DeTAR from network behavior datasets and evaluated the DeTAR routing algorithm against existing routing algorithms. Our simulation results show that the average saturation throughput can be improved by up to 17.59% compared with existing heuristic routing algorithms. Compared with the previous ML-based adaptive routing algorithm, the area of our routing logic is reduced by 88.95% without significant performance degradation.

关键词： networks-on-Chip Machine Learning Decision Tree Model Adaptive Routing Algorithm

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Optimize and Analysis of Risk Assessment Method for Wireless networks

Optimize and Analysis of Risk Assessment Method for Wireless...

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international conference on parallel distributed and Grid computing (PDGC)

作者： V Biksham Salar Mohammad G. Sravan Kumar Dept. of CSE(Data Science) Anurag University Hyderabad India Dept. of CSE Nalla Narasimhareddy Education Society’s Group of Institutions Hydereabad India

ISBN: (数字)9798331521349

ISBN: (纸本)9798331521356

Regardless of the additions offered by remote interchanges organizations, for example, movability, adaptability, expanded profitability, wandering abilities, modest establishment costs, and some more, the security of remote organizations has kept on being of extraordinary test and concern. At present, remote correspondences weaknesses are on the expansion because of the more popularity for higher information rates, the requirement for cutting edge administrations and that of meandering, and the gigantic arrangement of administrations over the globe. Therefore, this has made genuine testing issues in the security of remote frameworks and it shows the viability and legitimacy of this technique.

关键词： Wireless sensor networks Profitability Wireless networks Organizations Network security Sensors Security Risk management Optimization Testing

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Recommendation-Aware Collaborative Edge Caching Strategy in the Internet of Vehicles 18th

Recommendation-Aware Collaborative Edge Caching Strategy in...

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18th international conference on Wireless Artificial Intelligent computing Systems and Applications, WASA 2024

作者： Ou, Pingjie Chen, Ningjiang Huang, Zizhan School of Computer and Electronic Information Guangxi University Guangxi Nanning530004 China Key Laboratory of Parallel Distributed and Intelligent Computing Education Department of Guangxi Zhuang Autonomous Region Guangxi University Guangxi Nanning530004 China

ISBN: (纸本)9783031714696

Due to the limited resources of edge networks, the heterogeneity of user content requests, high-cost caching from direct resource hits, and redundancy in resource retention time hinder system performance. Traditional caching methods based on learning and popularity tend to encounter data skew when handling vehicle requests, leading to untimely cache data updates. To address these issues, this paper proposes an efficient edge cooperative caching strategy with recommendation awareness. Firstly, a time series prediction model based on a multi-dense multilayer perceptron is designed. This model segments historical request information into sub-sequence level slivers to enhance positional correlations between information, predicting user requests through historical time series and covariates. Secondly, to optimize cache utilization, comprehensively considers user mobility and contribution to enable recommendation awareness. Additionally, an optimized lifecycle is introduced to design a cache replacement strategy. Simulation experiments demonstrate that, compared to caching schemes based on content popularity and deep reinforcement learning, the proposed method achieves lower caching costs and higher cache hit rates. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Deep reinforcement learning

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Data Structures for Routing Table of the distributed Key-Value Store Based on Order Preserving Linear Hashing and Skip Graph with the Load Balancing Method 23

Data Structures for Routing Table of the Distributed Key-Val...

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23rd ACIS international Summer Virtual conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed computing, SNPD-Summer 2022

作者： Higuchi, Ken Miyazaki, Ami Hasegawa, Kenya Tsuji, Tatsuo University of Fukui Center for Data Science and Artificial Intelligence Fukui Japan University of Fukui School of Engineering Fukui Japan

ISBN: (纸本)9798350396379

In this paper, data structures for reducing redundancy of routing information on the distributed key-value store based on order preserving linear hashing and Skip Graph with the load balancing method are proposed and evaluated. In this system, data are divided by order preserving linear hashing and Skip Graph is used for overlay network. For load balancing, by storing many Skip Graph nodes in one physical node, any highest-load Skip Graph can be divided. By this method, load balancing can be done. But the number of Skip Graph nodes becomes very many and redundant routing information exists. But this redundant routing information has regularity. In this paper, two types of data structure for reducing redundant routing elements are proposed. They are tree structure and array structure. By calculating space for them and searching time, the proposed data structures are experimentally evaluated. © 2022 IEEE.

关键词： Overlay networks

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Efficient Protective Jamming in 2D SINR networks 29th

Efficient Protective Jamming in 2D SINR Networks

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29th international conference on parallel and distributed computing (Euro-Par)

作者： Bojko, Dominik Klonowski, Marek Kowalski, Dariusz R. Marciniak, Mateusz Wroclaw Univ Sci & Technol Wroclaw Poland Augusta Univ Augusta GA USA

ISBN: (纸本)9783031396977;9783031396984

This paper studies how intentional jamming can be used for selective hiding communication in the 2D Signal-to-Interference-plus-Noise-Ratio (SINR) model. We aim to place a set of additional jamming stations to generate interference that blocks all the signals in a specified restricted area, i.e., by making the SINR value of the genuine stations' signal below a pre-defined threshold. We aim to optimize the accuracy of the jamming strategy by minimizing the impact of the jamming stations on the area of desired genuine communication while jamming the signals in the given restricted zone. We present solutions in various network settings for uniform and non-uniform networks. As a secondary aim, we try to minimize the total energy of the jamming stations. Among others, we show that, surprisingly, it is possible to jam arbitrarily large areas by jammers using total energy arbitrarily close to zero. Our contribution is an extension of recent results for the same problem in the 1D SINR network. Let us stress, however, that a 2D environment is closer to real-life settings. Still, the 2D model turned out to be much more complex in analysis (even for the most uncomplicated cases) and required a different approach to constructing algorithms.

关键词： SINR information hiding jamming

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Multi-scale TFT-Net Time-Frequency Representation for Multi-component Radar Signal Recognition 25th

Multi-scale TFT-Net Time-Frequency Representation for Multi...

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

作者： Tang, Zeyu Shen, Hong Lam, Chan-Tong Faculty of Applied Sciences Macao Polytechnic University China School of Engineering and Technology Central Queensland University Rockhampton Australia

ISBN: (纸本)9789819642069

Existing research on multi-component radar signal recognition widely adopts recognition frameworks based on time-frequency transformation (TFT) and convolutional neural networks (CNN). To address the issue of the vulnerability of traditional TFT-generated time-frequency representations (TFR) to noise under low signal-to-noise ratio (SNR) conditions, we propose a new TFT scheme, called Multi-Scale TFT Network (MTFT-Net). Specifically, MTFT-Net learns diverse and comprehensive basis functions to obtain various TF features of time-domain multi-component radar signals. It then uses subsequent aggregation modules to concentrate and reconstruct the energy of the TF features, ultimately outputting the TFR. Experimental results show that MTFT-Net generates better TFRs with superior noise resistance under low SNR conditions compared to traditional TFT methods. Moreover, MTFT-Net can mimic the styles of various traditional TFTs. Finally, we compare its performance with the advanced TFA-Net to demonstrate the effectiveness of the proposed method. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

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Analysis of Performance and Optimization in MindSpore on Ascend NPUs 29

Analysis of Performance and Optimization in MindSpore on Asc...

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

作者： Wang, Bangchuan Yang, Chuying Zhu, Rui Liu, Xiao Zhou, Mingyao Zheng, Nenggan Zhejiang University Qiushi Academy for Advanced Studies School of Software Technology Hangzhou China Zhejiang University Qiushi Academy for Advanced Studies Hangzhou China Beijing Huawei Digital Technology Co. Ltd. Beijing China Hangzhou Huawei Communication Technology Co. Ltd. Hangzhou China

ISBN: (纸本)9798350330717

With the rapid advancement of artificial intelligence, the complexity and depth of deep neural networks continues to grow, placing higher demands on computational power. To meet these requirements, various manufacturers have developed specialized computing processors for the training process of deep learning, such as Huawei's Ascend Neural Processing Unit (NPU). In order to fully leverage the capabilities of the Ascend NPU, Huawei has introduced the MindSpore deep learning framework. The computational performance of deep learning frameworks plays a critical role for developers. However, there is a lack of comprehensive research on the analysis of performance and optimization in MindSpore framework on the Ascend NPU, leading to a scarcity of relevant references for deep learning development utilizing MindSpore on the Ascend NPU. To address this gap, this study examined the performance and optimization of MindSpore on Ascend NPUs through detailed experiments involving diverse workloads and multiple analysis metrics. The analysis is conducted at three levels: operations, models, and techniques, investigating the operations configurations, performance bottleneck, along with techniques selections, within the training process of DNNs. Consequently, this study offers significant insights and guidance for DL researchers and practitioners using MindSpore on Ascend NPUs. © 2023 IEEE.

关键词： Ascend NPU Deep Learning Deep Learning Framework High Performance computing MindSpore

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GA-Net: Gated Attention Mechanism Based Global Refinement Network for Image Inpainting 29

GA-Net: Gated Attention Mechanism Based Global Refinement Ne...

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

作者： Qiu, Ran Zhao, Shengrong Liang, Hu Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Jinan China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan China

ISBN: (纸本)9798350330717

Underwater images are often affected by problems such as light attenuation, color distortion, noise and scattering, resulting in image defects. A novel image inpainting method is proposed to intelligently predict and fill damaged areas for complete and continuous visualization of the image. First, in order to effectively solve the problem of color distortion caused by light refraction in underwater environments, the improved gated attention mechanism is used. This mechanism improves the local details by learning and weighting the important features of the image. Second, gated convolution automatically determines the degree of restoration for each pixel based on local features of the original image. It eliminates distractions such as low contrast and scattering, retaining more original detailed information. By doing so, image inpainting techniques improve the quality and visualization of underwater images. © 2023 IEEE.

关键词： Gated convolution Image inpainting Underwater images

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A Low BER Cooperative-adaptive-equalizer for Serial Receiver in HPC networks 25

A Low BER Cooperative-adaptive-equalizer for Serial Receiver...

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25th IEEE international conferences on High Performance computing and Communications, 9th international conference on Data Science and Systems, 21st IEEE international conference on Smart City and 9th IEEE international conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Mingche, Lai Fangxu, Lv Geng, Zhang Chaolong, Xu School of Computer National University of Defense Technology State Key Laboratory of High Performance Computing Changsha410073 China

ISBN: (纸本)9798350330014

With the evolution of high-performance computer and data center interconnect communication rates from 53.125Gbps to 106.25Gbps, high-speed serial interfaces face a dramatic increase in BER challenges, which seriously affects interconnect performance and system stability. To address the challenge of high BER of 106.25Gbps PAM4 receiver, this paper proposes a cooperative adaptive equalizer structure, which adopts three equalizers and adaptive cooperative equalization algorithm to achieve low BER under large insertion loss conditions. In addition, a blind adaptive equalization algorithm based on judgment feedback equalizer is proposed to shorten the link training time. In this paper, a 12nm CMOS process is used to design a receiver based on cooperative adaptive equalizer. Simulation shows that the receiver with cooperative adaptive equalizer can support BER less than e-12 for a de-emphasized l06.25Gbps PAM4 signal after 34.3dB @ 26.5625G Hz channel, and the convergence period is less then 0.2 us. © 2023 IEEE.

关键词： System stability

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An Efficient Sybil Attack Detection Approach for Vehicular Ad-Hoc networks 7

An Efficient Sybil Attack Detection Approach for Vehicular A...

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7th international conference on parallel, distributed and Grid computing, PDGC 2022

作者： Lohar, Durgesh Panda, Sanjaya Kumar Padhi, Slokashree Nayak, Sanjib Kumar National Institute of Technology Warangal Department of Computer Science and Engineering Telangana Warangal5060004 India Veer Surendra Sai University of Technology Burla Department of Computer Application Odisha Burla768018 India

ISBN: (纸本)9781665454018

Vehicular ad-hoc networks (VANETs) play a vital role in next-generation wireless communication. It consists of a set of moving vehicles, stationary vehicles, and roadside units (RSUs) that are connected through a wireless network. However, security and privacy issues are always challenging in VANETs as they lead to attacks. One such attack is the detection of the Sybil attack. This attack makes use of a vehicle or node to create multiple fake identities, at a time, to take advantage of a particular network. This attack leads to traffic congestion, rerouting, and accident. Many researchers have proposed solutions to identify the Sybil attack. Recently, Ayaida et al. [1] have presented an approach to detect the Sybil attack based on a macroscopic traffic flow model. This approach calculates the estimated speed and real speed, and their difference. If the difference is more than a predetermined threshold, then it suspects an attack and sends a message to nearby vehicles. This paper modifies their approach to provide a better solution by estimating the speed of vehicles and by RSU, thereby averaging their speed. The proposed approach is simulated using network simulator (ns) 3 and simulation of urban mobility (SUMO) to show its effectiveness. © 2022 IEEE.

关键词： Vehicular ad hoc networks

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