Concurrency and Computation-Practice & Experience最新文献

{"title":"Dynamic Load Balancing in Kubernetes Environments With Kubernetes Scheduling Extension (KSE)","authors":"Pedro Moritz de Carvalho Neto,&nbsp;Márcio Castro,&nbsp;Frank Siqueira","doi":"10.1002/cpe.8344","DOIUrl":"https://doi.org/10.1002/cpe.8344","url":null,"abstract":"<div>\u0000 \u0000 <p>Kubernetes is a flexible and reliable container orchestrator that has been employed to maintain massive cloud infrastructures worldwide. The task of allocating “Pods” (deployable units of computing that have one or more containers) to cluster nodes in Kubernetes is done by the <span>Kube-Scheduler</span> module, which determines which nodes are valid placements for each Pod according to constraints and available resources. Since it only acts at Pod creation, it does not take any action when the load of the system becomes uneven. In imbalanced scenarios, overloaded nodes can compromise the performance and availability of services hosted by them, whereas underloaded nodes may be a waste of financial resources, especially when using public clouds. In this paper, we propose an extension to the Kubernetes scheduler, called Kubernetes Scheduling Extension (KSE), which allows users to implement dynamic load-balancing algorithms that can migrate Pods between nodes at runtime. We also provide the implementation of two well-known load-balancing algorithms (KSE-<span>GreedyLB</span> and <span>KSE-RefineLB</span>) in KSE, which can balance the load of system nodes using CPU and memory consumption metrics. We carried out several experiments to assess the effectiveness of KSE-<span>GreedyLB</span> and <span>KSE-RefineLB</span> and compared their results with <span>Kube-Scheduler</span>. Overall, we evaluated 32 different scenarios using synthetic and realistic applications. Our results showed that <span>KSE-RefineLB</span> achieves better results than <span>Kube-Scheduler</span> when the workload is highly imbalanced while keeping similar performance when the load imbalance is low.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"37 3","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143112394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing Invariant Feature Learning via Cross-Composition and Self-Enrichment Normalization for Visible-Infrared Person Re-Identification","authors":"Zexin Zhang","doi":"10.1002/cpe.8346","DOIUrl":"https://doi.org/10.1002/cpe.8346","url":null,"abstract":"<div>\u0000 \u0000 <p>Visible-Infrared Person Re-Identification (VI-ReID) is a complex challenge in cross-modality retrieval, wherein the goal is to recognize individuals from images captured via RGB and IR cameras. While many existing methods focus on narrowing the gap between different modalities through designing various feature-level constraints, they often neglect the consistency of channel statistics information across the modalities, which results in suboptimal matching performance. In this work, we introduce a new approach for VI-ReID that incorporates Cross-Composition Normalization (CCN) and Self-Enrichment Normalization (SEN). Specifically, Cross-Composition Normalization is a plug-and-play module that can be seamlessly integrated into shallow CNN layers without requiring modifications to the training objectives. It probabilistically blends feature statistics between instances, thereby fostering the model's ability to learn inter-modality feature distributions. Conversely, Self-Enrichment Normalization leverages attention mechanisms to recalibrate statistics, effectively bridging the gaps between training and test distributions. This enhancement markedly boosts the discriminability of features in VI-ReID tasks. To validate the efficacy of our proposed method, we carried out comprehensive experiments on two public cross-modality datasets. The results clearly demonstrate the superiority of our Cross-Composition and Self-Enrichment normalization techniques in addressing the challenges of the VI-ReID problem.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"37 3","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143110643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Fast Parallel Approach for Neighborhood-Based Link Prediction by Disregarding Large Hubs","authors":"Subhajit Sahu,&nbsp;Kishore Kothapalli","doi":"10.1002/cpe.8331","DOIUrl":"https://doi.org/10.1002/cpe.8331","url":null,"abstract":"<div>\u0000 \u0000 <p>Link prediction can help rectify inaccuracies in various graph algorithms, stemming from unaccounted-for or overlooked links within networks. However, many existing works use a baseline approach, which incurs unnecessary computational costs due to its high time complexity. Further, many studies focus on smaller graphs, which can lead to misleading conclusions. Here, we study the prediction of links using neighborhood-based similarity measures on large graphs. In particular, we improve upon the baseline approach (IBase), and propose a heuristic approach that additionally disregards large hubs (DLH), based on the idea that high-degree nodes contribute little similarity among their neighbors. On a server equipped with dual 16-core Intel Xeon Gold 6226R processors, DLH is on average <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mn>1019</mn>\u0000 <mo>×</mo>\u0000 </mrow>\u0000 <annotation>$$ 1019times $$</annotation>\u0000 </semantics></math> faster than IBase, especially on web graphs and social networks, while maintaining similar prediction accuracy. Notably, DLH achieves a link prediction rate of 38.1<i>M</i> edges/s and improves performance by <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mn>1.6</mn>\u0000 <mo>×</mo>\u0000 </mrow>\u0000 <annotation>$$ 1.6times $$</annotation>\u0000 </semantics></math> for every doubling of threads.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"37 2","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143120160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fatigue Detection Based on Blood Volume Pulse Signal and Multi-Physical Features","authors":"Xiaowen Chen,&nbsp;Jian Lv,&nbsp;Qingsheng Xie","doi":"10.1002/cpe.8339","DOIUrl":"https://doi.org/10.1002/cpe.8339","url":null,"abstract":"<div>\u0000 \u0000 <p>Fatigue detection holds paramount importance in the timely identification of safety hazards. Nonetheless, prevailing fatigue detection methodologies often overlook the diverse spectrum of fatigue features or temporal cues. To address this lacuna, we introduce fatigue detection based on blood volume pulse signal and multi-physical features (FDBVPS-MF). Initially, a non-invasive technique is employed to extract the blood volume pulse signal (BVPS) from the forehead region, which is subsequently fed into a one-dimensional convolutional neural network (1D CNN) to formulate a fatigue detection model based on BVPS. Concurrently, features such as percentage of eyelid closure (PERCLOS), blink frequency (BF), and maximum closing time (MCT) are computed from eye images, and amalgamated with yawning frequency (YF) derived from mouth images to generate multi-physical features (MF). MF is then input into the 1D CNN network to construct a fatigue detection model based on MF. Subsequently, employing weights, derived through Adaboosting, a fusion approach is executed to integrate the outputs of the two fatigue detection models, thus facilitating multi-modal fatigue detection. On the UTA-RLDD dataset, the proposed FDBVPS-MF exhibits an accuracy and precision of 88.9% and 88.2%, respectively. Experimental findings substantiate the superior efficacy of FDBVPS-MF over conventional methodologies.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"37 3","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143120161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"New Continual Federated Learning System for Intrusion Detection in SDN-Based Edge Computing","authors":"Ameni Chetouane,&nbsp;Kamel Karoui","doi":"10.1002/cpe.8332","DOIUrl":"https://doi.org/10.1002/cpe.8332","url":null,"abstract":"<div>\u0000 \u0000 <p>Software Defined Networking (SDN) is an open network approach that has been proposed to address some of the main problems with traditional networks. However, SDN faces cybersecurity issues. To provide a network defense against attacks, an Intrusion Detection System (IDS) needs to be updated and included into the SDN architecture on a regular basis. Machine learning methods have proved effective in detecting intrusions in SDN. Moreover, these techniques pose the problem of significant computational overload and the absence of regular updates when new cyber-attacks appear. To address these issues, we propose a new SDN-based cloud intrusion detection system called Continual Federated Learning (CFL). In CFL, we modify the classical federated learning process by granting a more important and dynamic role to each participating client. On the one hand, it can trigger this process whenever a new type of intrusion is detected. On the other hand, once the new model has been identified, the customer can decide whether or not to deploy it in his network. In addition, to verify the accuracy of the CFL system, we have formally specified it by a communication protocol. This specification organizes the exchanges between the different communicating entities involved in the CFL. To verify the accuracy of this specification, we described it using the PROMELA language and checked with the associated SPIN tool. On the experimental side, we deployed this specification of the CFL system in an SDN computing environment. We defined different scenarios, and we proposed that each client decides locally to deploy or not the newly obtained intrusion detection model. The decision is based on a modified metric where we integrate the severity of the intrusions. Experimental results using private local datasets show that the proposed CFL system can efficiently and accurately detect new types of intrusions while preserving client confidentiality. Thus, it can be considered a promising system for SDN-based edge computing.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"37 2","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143120164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on the Application of Improved BERT-DPCNN Model in Chinese News Text Classification","authors":"Heda Wang,&nbsp;Shuyan Zhang","doi":"10.1002/cpe.8338","DOIUrl":"https://doi.org/10.1002/cpe.8338","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper introduces an enhanced BERT-DPCNN model for the task of Chinese news text classification. The model addresses the common challenge of balancing accuracy and computational efficiency in existing models, especially when dealing with large-scale, high-dimensional text data. To tackle this issue, the paper proposes an improved BERT-DPCNN model that integrates BERT's pre-trained language model with DPCNN's efficient convolutional structure to capture deep semantic information and key features from the text. Additionally, the paper incorporates the zebra optimization algorithm (ZOA) to dynamically optimize the model's hyperparameters, overcoming the limitations of manual tuning in traditional models. By automatically optimizing hyperparameters such as batch size, learning rate, and the number of filters through ZOA, the model's classification performance is significantly enhanced. Experimental results demonstrate that the improved ZOA-BERT-DPCNN model outperforms traditional methods on the THUCNEWS Chinese news dataset, not only verifying its effectiveness in news text classification tasks but also showcasing its potential to enhance classification performance.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"37 3","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143120162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reliability Assessment of Multiprocessor System Based on Exchanged Crossed Cube Networks","authors":"Xuanli Liu,&nbsp;Weibei Fan,&nbsp;Jing He,&nbsp;Zhijie Han,&nbsp;Chi-Hung Chi","doi":"10.1002/cpe.8325","DOIUrl":"https://doi.org/10.1002/cpe.8325","url":null,"abstract":"<div>\u0000 \u0000 <p>With the increasingly widespread application of multiprocessor systems, some processors in multiprocessor systems are inevitably prone to malfunctions. The reliability and effectiveness of the system are key issues. As a standard for measuring system fault tolerance, connectivity, and edge connectivity have many drawbacks. Therefore, Haray proposed conditional connectivity by restricting the connected components in disconnected subgraphs <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>G</mi>\u0000 <mo>−</mo>\u0000 <mi>F</mi>\u0000 </mrow>\u0000 <annotation>$$ G-F $$</annotation>\u0000 </semantics></math> to satisfy certain properties, where <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>G</mi>\u0000 </mrow>\u0000 <annotation>$$ G $$</annotation>\u0000 </semantics></math> and <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>F</mi>\u0000 </mrow>\u0000 <annotation>$$ F $$</annotation>\u0000 </semantics></math> represent the interconnection network and its set of faulty vertices, respectively. Restricted connectivity is a special type of conditional connectivity. Exchanged crossed cube, as a deformation of hypercube, has more favorable properties, such as smaller diameter, smaller link size, and lower cost. We prove that the 2-restricted connectivity of the exchanged crossed cubes <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mtext>ECQ</mtext>\u0000 <mo>(</mo>\u0000 <mi>s</mi>\u0000 <mo>,</mo>\u0000 <mi>t</mi>\u0000 <mo>)</mo>\u0000 </mrow>\u0000 <annotation>$$ mathrm{ECQ}left(s,tright) $$</annotation>\u0000 </semantics></math> is <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mn>4</mn>\u0000 <mi>s</mi>\u0000 <mo>−</mo>\u0000 <mn>4</mn>\u0000 </mrow>\u0000 <annotation>$$ 4s-4 $$</annotation>\u0000 </semantics></math> for <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mn>2</mn>\u0000 <mo>≤</mo>\u0000 <mi>s</mi>\u0000 <mo>≤</mo>\u0000 <mi>t</mi>\u0000 </mrow>\u0000 <annotation>$$ 2le sle t $$</annotation>\u0000 </semantics></math>.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"37 2","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143119789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"REHAS: Robust and Efficient Hyperelliptic Curve-Based Authentication Scheme for Internet of Drones","authors":"Bhanu Pratap,&nbsp;Ayush Singh,&nbsp;Pawan Singh Mehra","doi":"10.1002/cpe.8333","DOIUrl":"https://doi.org/10.1002/cpe.8333","url":null,"abstract":"<div>\u0000 \u0000 <p>Internet of Drones (IoD) is one of the most beneficial and has many versatile applications like Surveillance and Security, Delivery and Logistics, Environmental Monitoring, Agriculture, and so forth. The IoD network is crucial for collecting sensitive data like geo-coordinates, vehicle traffic data, and property details while surveying the various deployment locations in smart cities. The communication between users and drones can be compromised over insecure wireless channels by multiple attacks such as Man-in-the-middle-attack, Denial of Service, and so forth. Many schemes have already been propounded in the field of IoD. Still, many of them cannot address the resource constraints problem of drones, and existing protocols have higher computation and communication costs. Therefore, this paper has proposed a robust and efficient Hyper-Elliptic Curve-based authentication scheme (REHAS), which provides a session key for secure communication. Artificial Identities are generated using a hash function and random numbers. Fuzzy Extractor is used for user biometric authentication, which makes the smart device secure when lost. HECC is used with a smaller bit size of 80 bits rather than ECC of 160 bits. The security of the REHAS has been ensured using Scyther simulation. Furthermore, the resilience, safety, and robustness of REHAS are ensured by Informal security analysis. Lastly, a comparative study of the REHAS has been performed with other related Authentication and key agreement (AKA) protocols regarding communication cost, Computation cost, and security features, demonstrating that REHAS incurred less computation cost (6.7171 ms), communication overhead (1696 bits), and energy consumption (22.5 mJ) than other existing AKA schemes.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"37 3","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143119790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI Based Resource Management for 5G Network Slicing: History, Use Cases, and Research Directions","authors":"Monika Dubey,&nbsp;Ashutosh Kumar Singh,&nbsp;Richa Mishra","doi":"10.1002/cpe.8327","DOIUrl":"https://doi.org/10.1002/cpe.8327","url":null,"abstract":"<div>\u0000 \u0000 <p>5G, 6G, and beyond networks promise to support vertical industrial services with strict QoS parameters, but the hardware-based \"one-size-fits-all\" model of legacy networks lacks the flexibility needed for diverse services. The foundation of 5G networks lies in softwarization, with network slicing, Software Defined Networking (SDN), and Network Function Virtualisation (NFV) serving as its core components. The network-slicing-based shared network environment necessitates an intelligent and flexible resource management approach. In this case, traditional approaches are no longer suitable for dealing with a dynamic network environment. With recent advancements, AI-based approaches have the potential to manage resources autonomously. This paradigm shift underscores the need for deep and extensive investigation. However, existing literature on this subject is fragmented and lacks a cohesive overview of network slicing. To address these gaps, our review paper aims to provide a comprehensive scope of network slicing in a unified manner. In this sequence at first, this paper presented a conceptual overview of network slicing and enabling technologies, including SDN, NFV, and edge computing. Secondly, this paper identifies the relevant phases of resource management and presents AI-based resource management for network traffic classification, admission, allocation, and scheduling. Finally, it also discusses the deployment of network slicing-enabled key use cases and their practical deployment, the research gap, and open research challenges. To the best of our knowledge, this is the first attempt to critically analyze and present a consolidated review of the state of the art in network slicing resource management modules and network slicing-enabled key industrial use cases. This paper aims to guide researchers in developing innovative solutions and assist network players in the practical deployment of network slices for industrial applications.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"37 2","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143117455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Quantum-Inspired Source-Distributed Opportunistic Routing Protocol for Reliable Routing in Underwater Wireless Sensor Networks","authors":"T. R. Chenthil,&nbsp;G. Balachandran,&nbsp;S. Ranjith,&nbsp;E. Sakthivel","doi":"10.1002/cpe.8330","DOIUrl":"https://doi.org/10.1002/cpe.8330","url":null,"abstract":"<div>\u0000 \u0000 <p>Underwater Wireless Sensor Networks (UWSNs) play a pivotal role in various applications, ranging from environmental monitoring to disaster prevention, necessitating robust and efficient communication protocols tailored to the challenging underwater environment. This paper introduces the Quantum-Inspired Void-Based Source Distributed Opportunistic Routing Protocol (QIVSORP) to address the inherent limitations of classical routing protocols in UWSNs. Motivated by the unique challenges posed by underwater conditions, QIVSORP leverages principles from quantum mechanics to enhance routing efficiency. The protocol employs a source-distributed approach, utilizing quantum entanglement, superposition, and opportunistic routing strategies to enable adaptive and reliable data transmission in underwater scenarios. QIVSORP incorporates void-based forwarding, adaptive decision-making, and multipath routing to dynamically adjust routing decisions based on real-time network conditions. The protocol's source-informed decisions and opportunistic forwarding contribute to the adaptability and reliability of communication in dynamic underwater environments. QIVSORP achieves outstanding performance metrics: maintaining a Packet Delivery Ratio (PDR) of 98.9% with 50 nodes and 80% with 400 nodes, reducing end-to-end delays to 12 ms at 50 nodes, 15 ms at 100 nodes, and 52 ms at 600 nodes, and demonstrating energy efficiency ranging from 0.2 to 200 J per delivered packet across varying node densities. These results highlight the QIVSORP's capability to optimize communication in dynamic underwater environments effectively.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"37 2","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143116663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}