检索结果-内蒙古大学图书馆

Multi-Dimensional QoS Evaluation and Optimization of Mobile Edge Computing for IoT:A Survey

Chinese Journal of Electronics 2024年第4期33卷 859-874页

作者： Jiwei HUANG Fangzheng LIU Jianbing ZHANG Beijing Key Laboratory of Petroleum Data Mining China University of Petroleum Department of Computer Science and Technology China University of Petroleum

With the evolvement of the Internet of things(IoT), mobile edge computing(MEC) has emerged as a promising computing paradigm to support IoT data analysis and processing. In MEC for IoT, the differentiated requirements on quality of service(QoS) have been growing rapidly, making QoS a multi-dimensional concept including several attributes, such as performance, dependability, energy efficiency, and economic factors. To guarantee the QoS of IoT applications, theories and techniques of multi-dimensional QoS evaluation and optimization have become important theoretical foundations and supporting technologies for the research and application of MEC for IoT,which have attracted significant attention from both academia and industry. This paper aims to survey the existing studies on multi-dimensional QoS evaluation and optimization of MEC for IoT, and provide insights and guidance for future research in this field. This paper summarizes the multi-dimensional and multi-attribute QoS metrics in Io T scenarios, and then several QoS evaluation methods are presented. For QoS optimization, the main research problems in this field are summarized, and optimization models as well as their corresponding solutions are elaborated. We take notice of the booming of edge intelligence in artificial intelligence-empowered Io T scenarios, and illustrate the new research topics and the state-of-the-art approaches related to QoS evaluation and optimization. We discuss the challenges and future research directions.

关键词： Internet of things Mobile edge computing Quality of service Quality of service evaluation Quality of service optimization

来源：评论

学校读者我要写书评

暂无评论

Quantum algorithm for minimum dominating set problem with circuit design

引用

Chinese Physics B 2024年第2期33卷 178-188页

作者：张皓颖王绍轩刘新建沈颖童王玉坤 Beijing Key Laboratory of Petroleum Data Mining China University of PetroleumBeijing 102249China State Key Laboratory of Cryptology P.O.Box 5159Beijing 100878China

Using quantum algorithms to solve various problems has attracted widespread attention with the development of quantum *** are particularly interested in using the acceleration properties of quantum algorithms to solve NP-complete *** paper focuses on the well-known NP-complete problem of finding the minimum dominating set in undirected *** expedite the search process,a quantum algorithm employing Grover’s search is ***,a challenge arises from the unknown number of solutions for the minimum dominating set,rendering direct usage of original Grover’s search ***,a swap test method is introduced to ascertain the number of iterations *** oracle,diffusion operators,and swap test are designed with achievable quantum *** query complexity is O(1.414^(n))and the space complexity is O(n).To validate the proposed approach,qiskit software package is employed to simulate the quantum circuit,yielding the anticipated results.

关键词： quantum algorithm circuit design minimum dominating set

来源：评论

学校读者我要写书评

暂无评论

Enhance Broadcasting Throughput by Associating Network Coding with UAVs Relays Deployment in Emergency Communications 19th

Enhance Broadcasting Throughput by Associating Network Codi...

引用

19th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2023

作者： Xu, Chaonong Jiang, Yujie Beijing Key Lab of Petroleum Data Mining China University of Petroleum-Beijing Beijing China

ISBN: (纸本)9783031545306

During emergency scenarios, network access may be disrupted due to damaged Base Stations (BSs), and deploying Unmanned Aerial Vehicles (UAVs) as communication relays is common in rescue scenarios due to their convenience in ensuring network access. In such situations, the dissemination of rescue-related information messages is crucial, and broadcast messages are often prioritized. Thus, ensuring high broadcast throughput while guaranteeing accessibility for all victims and rescue teams is a significant challenge. Moreover, the broadcast burden is further aggravated by multiple rescue teams broadcasting messages simultaneously. To address this issue, Network Coding Based Cooperative (NCBC) broadcast scheme is a promising approach for enhancing broadcast throughput in emergency scenarios. By employing the NCBC broadcast scheme, we show that the broadcast throughput can be significantly improved. We propose a heuristic algorithm for generating optimal deployment of UAVs using network coding strategy and evaluate the broadcast throughput quantitatively. Simulation results show that our approach can ensure user accessibility and yield at least 26.69% throughput improvement compared to the traditional copy-and-forward relay protocol in a typical scenario. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Network coding

来源：评论

学校读者我要写书评

暂无评论

data Sinks Deployment for Backbone-Assisted Real-Time PD-NOMA Networks based on Reinforcement Learning 10

Data Sinks Deployment for Backbone-Assisted Real-Time PD-NOM...

引用

10th IEEE Smart World Congress, SWC 2024

作者： Lv, Zhenjie Xu, Chaonong Wei, Jiachen China University of Petroleum-Beijing Beijing Key Lab of Petroleum Data Mining Beijing China

ISBN: (纸本)9798331520861

Real-time performance is one of the most vital metrics in Backbone-assisted Power-Domain Non-Orthogonal Multiple Access Wireless Networks(BA-PDNOMAWNs) for Industrial Internet of Things applications. Since the relative geographic relationship between data sinks and wireless sensors affects real-time performance greatly, setting reasonable locations for data sinks is thus a feasible way to achieve high real-time performance for the scenarios where wireless sensors are not mobile. In this paper, we model the problem of finding the optimal locations for given sinks in BA-PDNOMAWNs so as to minimize uplink transmission latency. To find a low-complexity algorithm, we first formalize the problem as a Markov Decision Process, and then propose a reinforcement learning algorithm based on the classic Multi-Agent Deep Deterministic Policy Gradient, where its reward function is designed elaborately to accelerate convergences. Experimental results show that multiple data sinks in the BAPDNOMAWNs can reduce uplink transmission latency by 2.2 × compared to that with a single data sink. Additionally, compared to the classic Simulated Annealing optimization algorithm and the other siting algorithms, such as Clustering Center and Grid Partitioning in BA-PDNOMAWNs, our proposed algorithm can even reduce the uplink transmission delay by 2 ×, thus achieving better real-time performance. © 2024 IEEE.

关键词： Simulated annealing

来源：评论

学校读者我要写书评

暂无评论

Collaborative Inference Acceleration with Non-Penetrative Tensor Partitioning

Collaborative Inference Acceleration with Non-Penetrative Te...

引用

2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Liu, Zhibang Xu, Chaonong Lv, Zhenjie Liu, Zhizhuo Zhao, Suyu Beijing Key Lab of Petroleum Data Mining China University of Petroleum Beijing China

ISBN: (纸本)9798350368741

The inference of large-sized images on Internet of Things (IoT) devices is commonly hindered by limited resources, while there are often stringent latency requirements for Deep Neural Network (DNN) inference. Currently, this problem is generally addressed by collaborative inference, where the large-sized image is partitioned into multiple tiles, and each tile is assigned to an IoT device for processing. However, since significant latency will be incurred due to the communication overhead caused by tile sharing, the existing collaborative inference strategy is inefficient for convolutional computation, which is indispensable for any DNN. To reduce it, we propose Non-Penetrative Tensor Partitioning (NPTP), a fine-grained tensor partitioning method that reduces the communication latency by minimizing the communication load of tiles shared, thereby reducing inference latency. We evaluate NPTP with four widely-adopted DNN models. Experimental results demonstrate that NPTP achieves a 1.44-1.68× inference speedup relative to CoEdge, a state-of-the-art (SOTA) collaborative inference algorithm. © 2025 IEEE.

关键词： collaborative inference distributed computing edge intelligence

来源：评论

学校读者我要写书评

暂无评论

Cost-Efficient Edge Caching for NOMA-Enabled IoT Services

引用

China Communications 2024年第8期21卷 182-191页

作者： Chen Ying Xing Hua Ma Zhuo Chen Xin Huang Jiwei School of Computer Science Beijing Information Science and Technology UniversityBeijing 100101China Beijing Key Laboratory of Petroleum Data Mining China University of PetroleumBeijing 102249China

Mobile edge computing(MEC)is a promising paradigm by deploying edge servers(nodes)with computation and storage capacity close to IoT *** Providers can cache data in edge servers and provide services for IoT devices,which effectively reduces the delay for acquiring *** the increasing number of IoT devices requesting for services,the spectrum resources are generally *** order to effectively meet the challenge of limited spectrum resources,the Non-Orthogonal Multiple Access(NOMA)is proposed to improve the transmission *** this paper,we consider the caching scenario in a NOMA-enabled MEC *** the devices compete for the limited resources and tend to minimize their own *** formulate the caching problem,and the goal is to minimize the delay cost for each individual device subject to resource *** reformulate the optimization as a non-cooperative game *** prove the existence of Nash equilibrium(NE)solution in the game ***,we design the Game-based Cost-Efficient Edge Caching Algorithm(GCECA)to solve the *** effectiveness of our GCECA algorithm is validated by both parameter analysis and comparison experiments.

关键词： caching cost Internet of Things mobile edge computing non-orthogonal multiple access

来源：评论

学校读者我要写书评

暂无评论

Siamese transformer with hierarchical concept embedding for fine-grained image recognition

引用

Science China(Information Sciences) 2023年第3期66卷 188-203页

作者： Yilin LYU Liping JING Jiaqi WANG Mingzhe GUO Xinyue WANG Jian YU School of Computer and Information Technology Beijing Jiaotong University Beijing Key Lab of Traffic Data Analysis and Mining Beijing Jiaotong University Alibaba Group

Distinguishing the subtle differences among fine-grained images from subordinate concepts of a concept hierarchy is a challenging task. In this paper, we propose a Siamese transformer with hierarchical concept embedding(STr HCE), which contains two transformer subnetworks sharing all configurations,and each subnetwork is equipped with the hierarchical semantic information at different concept levels for fine-grained image embeddings. In particular, one subnetwork is for coarse-scale patches to learn the discriminative regions with the aid of the innate multi-head self-attention mechanism of the transformer. The other subnetwork is for finer-scale patches, which are adaptively sampled from the discriminative regions, to capture subtle yet discriminative visual cues and eliminate redundant information. STr HCE connects the two subnetworks through a score margin adjustor to enforce the most discriminative regions generating more confident predictions. Extensive experiments conducted on four commonly-used benchmark datasets, including CUB-200-2011, FGVC-Aircraft, Stanford Dogs, and NABirds, empirically demonstrate the superiority of the proposed STr HCE over state-of-the-art baselines.

关键词： fine-grained image recognition transformer hierarchical concept embedding adaptive sampling Siamese network

来源：评论

学校读者我要写书评

暂无评论

Dynamic community detection algorithm based on hyperbolic graph convolution

引用

International Journal of Intelligent Computing and Cybernetics 2024年第3期17卷 632-653页

作者： Weijiang Wu Heping Tan Yifeng Zheng College of Information Science and Engineering/College of Artificial Intelligence China University of Petroleum BeijingBeijingChina Beijing Key Laboratory of Petroleum Data Mining China University of Petroleum BeijingBeijingChina School of Computer Science Minnan Normal UniversityZhangzhouChina

Purpose:Community detection is a key factor in analyzing the structural features of complex ***,traditional dynamic community detection methods often fail to effectively solve the problems of deep network information loss and computational complexity in hyperbolic *** address this challenge,a hyperbolic space-based dynamic graph neural network community detection model(HSDCDM)is ***/methodology/approach:HSDCDM first projects the node features into the hyperbolic space and then utilizes the hyperbolic graph convolution module on the Poincare and Lorentz models to realize feature fusion and information *** addition,the parallel optimized temporal memory module ensures fast and accurate capture of time domain information over extended ***,the community clustering module divides the community structure by combining the node characteristics of the space domain and the time *** evaluate the performance of HSDCDM,experiments are conducted on both artificial and real ***:Experimental results on complex networks demonstrate that HSDCDM significantly enhances the quality of community detection in hierarchical *** shows an average improvement of 7.29%in NMI and a 9.07%increase in ARI across datasets compared to traditional *** complex networks with nonEuclidean geometric structures,the HSDCDM model incorporating hyperbolic geometry can better handle the discontinuity of the metric space,provides a more compact embedding that preserves the data structure,and offers advantages over methods based on Euclidean geometry ***/value:This model aggregates the potential information of nodes in space through manifoldpreserving distribution mapping and hyperbolic graph topology ***,it optimizes the Simple Recurrent Unit(SRU)on the hyperbolic space Lorentz model to effectively extract time series data in hyperbolic space,thereby enhancing computing efficiency by eliminating t

关键词： Complex networks Dynamic community detection Hyperbolic graph neural network

来源：评论

学校读者我要写书评

暂无评论

CollabKG: A Learnable Human-Machine-Cooperative Information Extraction Toolkit for (Event) Knowledge Graph Construction 30

CollabKG: A Learnable Human-Machine-Cooperative Information ...

引用

Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Wei, Xiang Chen, Yufeng Cheng, Ning Cui, Xingyu Xu, Jinan Han, Wenjuan Beijing Key Lab of Traffic Data Analysis and Mining Beijing Jiaotong University Beijing China

ISBN: (纸本)9782493814104

In order to construct or extend entity-centric and event-centric knowledge graphs (KG and EKG), the information extraction (IE) annotation toolkit is essential. However, existing IE toolkits have several non-trivial problems, such as not supporting multi-tasks, and not supporting automatic updates. In this work, we present CollabKG, a learnable human-machine-cooperative IE toolkit for KG and EKG construction. Specifically, for the multi-task issue, CollabKG unifies different IE subtasks, including named entity recognition (NER), entity-relation triple extraction (RE), and event extraction (EE), and supports both KG and EKG. Then, combining advanced prompting-based IE technology, the human-machine-cooperation mechanism with Large Language Models (LLMs) as the assistant machine is presented which can provide a lower cost as well as a higher performance. Lastly, owing to the two-way interaction between the human and machine, CollabKG with learning ability allows self-renewal. Besides, CollabKG has several appealing features (e.g., customization, training-free, and label propagation) that make the system powerful and high-productivity. We holistically compare our toolkit with other existing tools on these features. Human evaluation quantitatively illustrates that CollabKG significantly improves annotation quality, efficiency, and stability simultaneously. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Knowledge graph

来源：评论

学校读者我要写书评

暂无评论

Noisy Multi-label Text Classification via Instance-label Pair Correction

Noisy Multi-Label Text Classification via Instance-Label Pai...

引用

2024 Findings of the Association for Computational Linguistics: NAACL 2024

作者： Xu, Pengyu Song, Mingyang Liu, Linkaida Liu, Bing Sun, Hongjian Jing, Liping Yu, Jian Beijing Key Lab of Traffic Data Analysis and Mining Beijing Jiaotong University Beijing China

ISBN: (纸本)9798891761193

In noisy label learning, instance selection based on small-loss criteria has been proven to be highly effective. However, in the case of noisy multi-label text classification (NMLTC), the presence of noise is not limited to the instance-level but extends to the (instance-label) pair-level. This gives rise to two main challenges. (1) The loss information at the pair-level fails to capture the variations between instances. (2) There are two types of noise at the pair-level: false positives and false negatives. Identifying false negatives from a large pool of negative pairs presents an exceedingly difficult task. To tackle these issues, we propose a novel approach called instance-label pair correction (iLaCo), which aims to address the problem of noisy pair selection and correction in NMLTC tasks. Specifically, we first introduce a holistic selection metric that identifies noisy pairs by simultaneously considering global loss information and instance-specific ranking information. Secondly, we employ a filter guided by label correlation to focus exclusively on negative pairs with label relevance. This filter significantly reduces the difficulty of identifying false negatives. Experimental analysis indicates that our iLaCo framework effectively corrects noisy pairs in NMLTC datasets, leading to a significant improvement in model performance. © 2024 Association for Computational Linguistics.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：