Journal of King Saud University-Computer and Information Sciences最新文献_第4页

Multi-objective optimization in order to allocate computing and telecommunication resources based on non-orthogonal access, participation of cloud server and edge server in 5G networks 基于非正交访问、云服务器和边缘服务器在 5G 网络中的参与，进行多目标优化以分配计算和电信资源

IF 5.2 2区计算机科学

Journal of King Saud University-Computer and Information Sciences Pub Date : 2024-09-16 DOI: 10.1016/j.jksuci.2024.102187

Liying Zhao , Chao Liu , Entie Qi , Sinan Shi

{"title":"Multi-objective optimization in order to allocate computing and telecommunication resources based on non-orthogonal access, participation of cloud server and edge server in 5G networks","authors":"Liying Zhao , Chao Liu , Entie Qi , Sinan Shi","doi":"10.1016/j.jksuci.2024.102187","DOIUrl":"10.1016/j.jksuci.2024.102187","url":null,"abstract":"<div><div>Mobile edge processing is a cutting-edge technique that addresses the limitations of mobile devices by enabling users to offload computational tasks to edge servers, rather than relying on distant cloud servers. This approach significantly reduces the latency associated with cloud processing, thereby enhancing the quality of service. In this paper, we propose a system in which a cellular network, comprising multiple users, interacts with both cloud and edge servers to process service requests. The system assumes non-orthogonal multiple access (NOMA) for user access to the radio spectrum. We model the interactions between users and servers using queuing theory, aiming to minimize the total energy consumption of users, service delivery time, and overall network operation costs. The problem is mathematically formulated as a multi-objective, bounded non-convex optimization problem. The Structural Correspondence Analysis (SCA) method is employed to obtain the global optimal solution. Simulation results demonstrate that the proposed model reduces energy consumption, delay, and network costs by approximately 50%, under the given assumptions.</div></div>","PeriodicalId":48547,"journal":{"name":"Journal of King Saud University-Computer and Information Sciences","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142319258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A novel edge intelligence-based solution for safer footpath navigation of visually impaired using computer vision 基于边缘智能的新型解决方案，利用计算机视觉为视障人士提供更安全的人行道导航

IF 5.2 2区计算机科学

Journal of King Saud University-Computer and Information Sciences Pub Date : 2024-09-16 DOI: 10.1016/j.jksuci.2024.102191

Rashik Iram Chowdhury, Jareen Anjom, Md. Ishan Arefin Hossain

{"title":"A novel edge intelligence-based solution for safer footpath navigation of visually impaired using computer vision","authors":"Rashik Iram Chowdhury, Jareen Anjom, Md. Ishan Arefin Hossain","doi":"10.1016/j.jksuci.2024.102191","DOIUrl":"10.1016/j.jksuci.2024.102191","url":null,"abstract":"<div><p>Navigating through a tactile paved footpath surrounded by various sizes of static and dynamic obstacles is one of the biggest impediments visually impaired people face, especially in Dhaka, Bangladesh. This problem is important to address, considering the number of accidents in such densely populated footpaths. We propose a novel deep-edge solution using Computer Vision to make people aware of the obstacles in the vicinity and reduce the necessity of a walking cane. This study introduces a diverse novel tactile footpath dataset of Dhaka covering different city areas. Additionally, existing state-of-the-art deep neural networks for object detection have been fine-tuned and investigated using this dataset. A heuristic-based breadth-first navigation algorithm (HBFN) is developed to provide navigation directions that are safe and obstacle-free, which is then deployed in a smartphone application that automatically captures images of the footpath ahead to provide real-time navigation guidance delivered by speech. The findings from this study demonstrate the effectiveness of the object detection model, YOLOv8s, which outperformed other benchmark models on this dataset, achieving a high mAP of 0.974 and an F1 score of 0.934. The model’s performance is analyzed after quantization, reducing its size by 49.53% while retaining 98.97% of the original mAP.</p></div>","PeriodicalId":48547,"journal":{"name":"Journal of King Saud University-Computer and Information Sciences","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1319157824002805/pdfft?md5=67af390c0280c8b6ae2c05684fbae69f&pid=1-s2.0-S1319157824002805-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142272843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Graph contrast learning for recommendation based on relational graph convolutional neural network 基于关系图卷积神经网络的推荐图对比学习

IF 5.2 2区计算机科学

Journal of King Saud University-Computer and Information Sciences Pub Date : 2024-09-14 DOI: 10.1016/j.jksuci.2024.102168

Xiaoyang Liu , Hanwen Feng , Xiaoqin Zhang , Xia Zhou , Asgarali Bouyer

{"title":"Graph contrast learning for recommendation based on relational graph convolutional neural network","authors":"Xiaoyang Liu , Hanwen Feng , Xiaoqin Zhang , Xia Zhou , Asgarali Bouyer","doi":"10.1016/j.jksuci.2024.102168","DOIUrl":"10.1016/j.jksuci.2024.102168","url":null,"abstract":"<div><div>Current knowledge graph-based recommendation methods heavily rely on high-quality knowledge graphs, often falling short in effectively addressing issues such as the cold start problem and heterogeneous noise in user interactions. This leads to biases in user interest and popularity. To overcome these challenges, this paper introduces a novel recommendation approach termed Knowledge-enhanced Perceptive Graph Attention with Graph Contrastive Learning (KPA-GCL), which leverages relational graph convolutional neural networks. The proposed method optimizes the triplet embedding representation of entity-item interactions based on relationships between adjacent entities in a heterogeneous graph. Subsequently, a graph convolutional neural network is employed for enhanced aggregation. Similarity scores from a contrastive view serve as the selection criterion for high-quality embedded representations, facilitating the extraction of refined knowledge subgraphs. Multiple adaptive contrast-loss optimization functions are introduced by combining Bayesian Personalized Ranking (BPR) and hard negative sampling techniques. Comparative experiments are conducted with ten popular existing methods using real public datasets. Results indicate that the KPA-GCL method outperforms compared methods in all datasets based on Recall, NDCG, Precision, and Hit-ratio measures. Furthermore, in terms of mitigating cold start and noise, the KPA-GCL method surpasses other ten methods. This validates the reasonability and effectiveness of KPA-GCL in real-world datasets.</div></div>","PeriodicalId":48547,"journal":{"name":"Journal of King Saud University-Computer and Information Sciences","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S131915782400257X/pdfft?md5=d69bd7bfcc27dc9c754378e21af4a8b9&pid=1-s2.0-S131915782400257X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142315441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improving embedding-based link prediction performance using clustering 利用聚类提高基于嵌入的链接预测性能

IF 5.2 2区计算机科学

Journal of King Saud University-Computer and Information Sciences Pub Date : 2024-09-13 DOI: 10.1016/j.jksuci.2024.102181

Fitri Susanti , Nur Ulfa Maulidevi , Kridanto Surendro

{"title":"Improving embedding-based link prediction performance using clustering","authors":"Fitri Susanti , Nur Ulfa Maulidevi , Kridanto Surendro","doi":"10.1016/j.jksuci.2024.102181","DOIUrl":"10.1016/j.jksuci.2024.102181","url":null,"abstract":"<div><p>Incomplete knowledge graphs are common problem that can impair task accuracy. As knowledge graphs grow extensively, the probability of incompleteness increases. Link prediction addresses this problem, but accurate and efficient link prediction methods are needed to handle incomplete and extensive knowledge graphs. This study proposed modifications to the embedding-based link prediction using clustering to improve performance. The proposed method involves four main processes: embedding, clustering, determining clusters, and scoring. Embedding converts entities and relations into vectors while clustering groups these vectors. Selected clusters are determined based on the shortest distance between the centroid and the incomplete knowledge graph. Scoring measures relation rankings, and link prediction result is selected based on highest scores. The link prediction performance is evaluated using Hits@1, Mean Rank, Mean Reciprocal Rank and prediction time on three knowledge graph datasets: WN11, WN18RR, and FB13. The link prediction methods used are TransE and ComplEx, with BIRCH as the clustering technique and Mahalanobis for short-distance measurement. The proposed method significantly improves link prediction performance, achieving accuracy up to 98% and reducing prediction time by 99%. This study provides effective and efficient solution for improving link prediction, demonstrating high accuracy and efficiency in handling incomplete and extensive knowledge graphs.</p></div>","PeriodicalId":48547,"journal":{"name":"Journal of King Saud University-Computer and Information Sciences","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1319157824002702/pdfft?md5=e31143cd70a22f8ffa2da3a54e983856&pid=1-s2.0-S1319157824002702-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142241566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A sharding blockchain protocol for enhanced scalability and performance optimization through account transaction reconfiguration 通过账户交易重新配置增强可扩展性和性能优化的分片区块链协议

IF 5.2 2区计算机科学

Journal of King Saud University-Computer and Information Sciences Pub Date : 2024-09-11 DOI: 10.1016/j.jksuci.2024.102184

Jiaying Wu , Lingyun Yuan , Tianyu Xie , Hui Dai

{"title":"A sharding blockchain protocol for enhanced scalability and performance optimization through account transaction reconfiguration","authors":"Jiaying Wu , Lingyun Yuan , Tianyu Xie , Hui Dai","doi":"10.1016/j.jksuci.2024.102184","DOIUrl":"10.1016/j.jksuci.2024.102184","url":null,"abstract":"<div><p>Sharding is a critical technology for enhancing blockchain scalability. However, existing sharding blockchain protocols suffer from a high cross-shard ratio, high transaction latency, limited throughput enhancement, and high account migration. To address these problems, this paper proposes a sharding blockchain protocol for enhanced scalability and performance optimization through account transaction reconfiguration. Firstly, we construct a blockchain transaction account graph network structure to analyze transaction account correlations. Secondly, a modularity-based account transaction reconfiguration algorithm and a detailed account reconfiguration process is designed to minimize cross-shard transactions. Finally, we introduce a transaction processing mechanism for account transaction reconfiguration in parallel with block consensus uploading, which reduces the reconfiguration time overhead and system latency. Experimental results demonstrate substantial performance improvements compared to existing shard protocols: up to a 34.7% reduction in cross-shard transaction ratio, at least an 83.2% decrease in transaction latency, at least a 52.7% increase in throughput and a 7.8% decrease in account migration number. The proposed protocol significantly enhances the overall performance and scalability of blockchain, providing robust support for blockchain applications in various fields such as financial services, supply chain management, and industrial Internet of Things. It also enables better support for high-concurrency scenarios and large-scale network environments.</p></div>","PeriodicalId":48547,"journal":{"name":"Journal of King Saud University-Computer and Information Sciences","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1319157824002738/pdfft?md5=107fe417689144e59c75fddd0f5b671f&pid=1-s2.0-S1319157824002738-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142169351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

RAPID: Robust multi-pAtch masker using channel-wise Pooled varIance with two-stage patch Detection RAPID：利用信道汇集变异和两级补丁检测的鲁棒多咀屏蔽器

IF 5.2 2区计算机科学

Journal of King Saud University-Computer and Information Sciences Pub Date : 2024-09-11 DOI: 10.1016/j.jksuci.2024.102188

Heemin Kim , Byeong-Chan Kim , Sumi Lee , Minjung Kang , Hyunjee Nam , Sunghwan Park , Il-Youp Kwak , Jaewoo Lee

{"title":"RAPID: Robust multi-pAtch masker using channel-wise Pooled varIance with two-stage patch Detection","authors":"Heemin Kim , Byeong-Chan Kim , Sumi Lee , Minjung Kang , Hyunjee Nam , Sunghwan Park , Il-Youp Kwak , Jaewoo Lee","doi":"10.1016/j.jksuci.2024.102188","DOIUrl":"10.1016/j.jksuci.2024.102188","url":null,"abstract":"<div><p>Recently, adversarial patches have become frequently used in adversarial attacks in real-world settings, evolving into various shapes and numbers. However, existing defense methods often exhibit limitations in addressing specific attacks, datasets, or conditions. This underscores the demand for versatile and robust defenses capable of operating across diverse scenarios. In this paper, we propose the RAPID (<strong>R</strong>obust multi-p<strong>A</strong>tch masker using channel-wise <strong>P</strong>ooled var<strong>I</strong>ance with two-stage patch <strong>D</strong>etection) framework, a stable solution to restore detection efficacy in the presence of multiple patches. The RAPID framework excels in defending against attacks regardless of patch number or shape, offering a versatile defense adaptable to diverse adversarial scenarios. RAPID employs a two-stage strategy to identify and mask coordinates associated with patch attacks. In the first stage, we propose the ‘channel-wise pooled variance’ to detect candidate patch regions. In the second step, upon detecting these regions, we identify dense areas as patches and mask them accordingly. This framework easily integrates into the preprocessing stage of any object detection model due to its independent structure, requiring no modifications to the model itself. Evaluation indicates that RAPID enhances robustness by up to 60% compared to other defenses. RAPID achieves mAP50 and mAP@50-95 values of 0.696 and 0.479, respectively.</p></div>","PeriodicalId":48547,"journal":{"name":"Journal of King Saud University-Computer and Information Sciences","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1319157824002775/pdfft?md5=097312e661d7cf2bd4bcbc118fd164bd&pid=1-s2.0-S1319157824002775-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142169352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Design and FPGA implementation of nested grid multi-scroll chaotic system 嵌套网格多卷混沌系统的设计与 FPGA 实现

IF 5.2 2区计算机科学

Journal of King Saud University-Computer and Information Sciences Pub Date : 2024-09-10 DOI: 10.1016/j.jksuci.2024.102186

Guofeng Yu, Chunlei Fan, Jiale Xi, Chengbin Xu

{"title":"Design and FPGA implementation of nested grid multi-scroll chaotic system","authors":"Guofeng Yu, Chunlei Fan, Jiale Xi, Chengbin Xu","doi":"10.1016/j.jksuci.2024.102186","DOIUrl":"10.1016/j.jksuci.2024.102186","url":null,"abstract":"<div><p>Conventional multi-scroll chaotic systems are often constrained by the number of attractors and the complexity of generation, making it challenging to meet the increasing demands of communication and computation. This paper revolves around the modified Chua’s system. By modifying its differential equation and introducing traditional nonlinear functions, such as the step function sequence and sawtooth function sequence. A nested grid multi-scroll chaotic system (NGMSCS) can be established, capable of generating nested grid multi-scroll attractors. In contrast to conventional grid multi-scroll chaotic attractors, scroll-like phenomena can be initiated outside the grid structure, thereby revealing more complex dynamic behavior and topological features. Through the theoretical design and analysis of the equilibrium point of the system and its stability, the number of saddle-focused equilibrium points of index 2 is further expanded, which can generate (2 N+2) × M attractors, and the formation mechanism is elaborated and verified in detail. In addition, the generation of an arbitrary number of equilibrium points in the <em>y</em>-direction is achieved by transforming the <em>x</em> and <em>y</em> variables, which can generate M×(2 N+2) attractors, increasing the complexity of the system. The system’s dynamical properties are discussed in depth via time series plots, Lyapunov exponents, Poincaré cross sections, 0–1 tests, bifurcation diagrams, and attraction basins. The existence of attractors is confirmed through numerical simulations and FPGA-based hardware experiments.</p></div>","PeriodicalId":48547,"journal":{"name":"Journal of King Saud University-Computer and Information Sciences","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1319157824002751/pdfft?md5=5a97268ac1950c4cb177bec835b9c871&pid=1-s2.0-S1319157824002751-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142233768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Towards the development of believable agents: Adopting neural architectures and adaptive neuro-fuzzy inference system via playback of human traces 开发可信的代理：通过回放人类痕迹采用神经架构和自适应神经模糊推理系统

IF 5.2 2区计算机科学

Journal of King Saud University-Computer and Information Sciences Pub Date : 2024-09-02 DOI: 10.1016/j.jksuci.2024.102182

Naveed Anwer Butt , Mian Muhammad Awais , Samra Shahzadi , Tai-hoon Kim , Imran Ashraf

{"title":"Towards the development of believable agents: Adopting neural architectures and adaptive neuro-fuzzy inference system via playback of human traces","authors":"Naveed Anwer Butt , Mian Muhammad Awais , Samra Shahzadi , Tai-hoon Kim , Imran Ashraf","doi":"10.1016/j.jksuci.2024.102182","DOIUrl":"10.1016/j.jksuci.2024.102182","url":null,"abstract":"<div><p>Artificial intelligence (AI) research on video games primarily focused on the imitation of human-like behavior during the past few years. Moreover, to increase the perceived worth of amusement and gratification, there is an enormous rise in the demand for intelligent agents that can imitate human players and video game characters. However, the agents developed using the majority of current approaches are perceived as rather more mechanical, which leads to frustration, and more importantly, failure in engagement. On that account, this study proposes an imitation learning framework to generate human-like behavior for more precise and accurate reproduction. To build a computational model, two learning paradigms are explored, artificial neural networks (ANN) and adaptive neuro-fuzzy inference systems (ANFIS). This study utilized several variations of ANN, including feed-forward, recurrent, extreme learning machines, and regressions, to simulate human player behavior. Furthermore, to find the ideal ANFIS, grid partitioning, subtractive clustering, and fuzzy c-means clustering are used for training. The results demonstrate that ANFIS hybrid intelligence systems trained with subtractive clustering are overall best with an average accuracy of 95%, followed by fuzzy c-means with an average accuracy of 87%. Also, the believability of the obtained AI agents is tested using two statistical methods, i.e., the Mann–Whitney U test and the cosine similarity analysis. Both methods validate that the observed behavior has been reproduced with high accuracy.</p></div>","PeriodicalId":48547,"journal":{"name":"Journal of King Saud University-Computer and Information Sciences","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1319157824002714/pdfft?md5=542b4e8449657f4dbd195276e5fb54c1&pid=1-s2.0-S1319157824002714-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142229614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

GCNT: Identify influential seed set effectively in social networks by integrating graph convolutional networks with graph transformers GCNT：通过将图卷积网络与图转换器整合，有效识别社交网络中具有影响力的种子集

IF 5.2 2区计算机科学

Journal of King Saud University-Computer and Information Sciences Pub Date : 2024-09-02 DOI: 10.1016/j.jksuci.2024.102183

Jianxin Tang , Jitao Qu , Shihui Song , Zhili Zhao , Qian Du

{"title":"GCNT: Identify influential seed set effectively in social networks by integrating graph convolutional networks with graph transformers","authors":"Jianxin Tang , Jitao Qu , Shihui Song , Zhili Zhao , Qian Du","doi":"10.1016/j.jksuci.2024.102183","DOIUrl":"10.1016/j.jksuci.2024.102183","url":null,"abstract":"<div><p>Exploring effective and efficient strategies for identifying influential nodes from social networks as seeds to promote the propagation of influence remains a crucial challenge in the field of influence maximization (IM), which has attracted significant research efforts. Deep learning-based approaches have been adopted as an alternative promising solution to the IM problem. However, a robust model that captures the associations between network information and node influence needs to be investigated, while concurrently considering the effects of the overlapped influence on training labels. To address these challenges, a GCNT model, which integrates Graph Convolutional Networks with Graph Transformers, is introduced in this paper to capture the intricate relationships among the topology of the network, node attributes, and node influence effectively. Furthermore, an innovative method called <span><math><mrow><mi>G</mi><mi>r</mi><mi>e</mi><mi>e</mi><mi>d</mi><mi>y</mi></mrow></math></span>-<span><math><mrow><mi>L</mi><mi>I</mi><mi>E</mi></mrow></math></span> is proposed to generate labels to alleviate the issue of overlapped influence spread. Moreover, a Mask mechanism specially tailored for the IM problem is presented along with an input embedding balancing strategy. The effectiveness of the GCNT model is demonstrated through comprehensive experiments conducted on six real-world networks, and the model shows its competitive performance in terms of both influence maximization and computational efficiency over state-of-the-art methods.</p></div>","PeriodicalId":48547,"journal":{"name":"Journal of King Saud University-Computer and Information Sciences","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1319157824002726/pdfft?md5=fb687d0a26ab54db6f7c889e608384a1&pid=1-s2.0-S1319157824002726-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142149684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Learning-driven Data Fabric Trends and Challenges for cloud-to-thing continuum 学习驱动的数据架构趋势与挑战，实现从云到物的连续性

IF 5.2 2区计算机科学

Journal of King Saud University-Computer and Information Sciences Pub Date : 2024-09-01 DOI: 10.1016/j.jksuci.2024.102145

Praveen Kumar Donta , Chinmaya Kumar Dehury , Yu-Chen Hu

{"title":"Learning-driven Data Fabric Trends and Challenges for cloud-to-thing continuum","authors":"Praveen Kumar Donta , Chinmaya Kumar Dehury , Yu-Chen Hu","doi":"10.1016/j.jksuci.2024.102145","DOIUrl":"10.1016/j.jksuci.2024.102145","url":null,"abstract":"<div><p>This special issue is a collection of emerging trends and challenges in applying learning-driven approaches to data fabric architectures within the cloud-to-thing continuum. As data generation and processing increasingly occur at the edge, there is a growing need for intelligent, adaptive data management solutions that seamlessly operate across distributed environments. In this special issue, we received research contributions from various groups around the world. We chose the eight most appropriate and novel contributions to include in this special issue. These eight contributions were further categorized into three themes: Data Handling approaches, resource optimization and management, and security and attacks. Additionally, this editorial suggests future research directions that will potentially lead to groundbreaking insights, which could pave the way for a new era of learning techniques in Data Fabric and the Cloud-to-Thing Continuum.</p></div>","PeriodicalId":48547,"journal":{"name":"Journal of King Saud University-Computer and Information Sciences","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1319157824002349/pdfft?md5=286285bbd5dfa0b63dd8785bf5349c2e&pid=1-s2.0-S1319157824002349-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142230508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0