Computer Communications最新文献_第2页

Authenticated data visualization for hybrid blockchain-based digital product passports

IF 4.5 3区计算机科学

Computer Communications Pub Date : 2025-03-01 DOI: 10.1016/j.comcom.2025.108110

Domenico Tortola , Claudio Felicioli , Andrea Canciani , Fabio Severino

{"title":"Authenticated data visualization for hybrid blockchain-based digital product passports","authors":"Domenico Tortola , Claudio Felicioli , Andrea Canciani , Fabio Severino","doi":"10.1016/j.comcom.2025.108110","DOIUrl":"10.1016/j.comcom.2025.108110","url":null,"abstract":"<div><div>The Digital Product Passport (DPP), introduced by the European Green Deal in 2022, is a key innovation designed to improve product sustainability and circularity by enabling secure and transparent communication among stakeholders. Despite its potential, existing blockchain-based implementations of the DPP face significant limitations, such as scalability challenges and usability issues, which hinder widespread adoption. To address these shortcomings, this paper proposes a hybrid blockchain-based implementation of the DPP that enhances data transparency, integrity, and accessibility while minimizing common drawbacks. The proposed solution utilizes a hybrid blockchain architecture, where data is collected and managed within a private blockchain network and notarized on a public blockchain. Additionally, the central problem of authenticated blockchain data visualization is addressed by proposing a new solution that not only ensures the provenance, integrity, and history consistency of DPP data, but also preserves these properties throughout data processing and visualization. Our experiments demonstrates the effectiveness of our approach, achieving low time consumption and storage overhead. To further promote transparency and collaboration, a selection of the implementation has been made available as open-source projects. We show that hybrid blockchains offer a promising path for realizing the full potential of the Digital Product Passport.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"236 ","pages":"Article 108110"},"PeriodicalIF":4.5,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143580332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Active queue management in 5G and beyond cellular networks using Machine Learning

IF 4.5 3区计算机科学

Computer Communications Pub Date : 2025-03-01 DOI: 10.1016/j.comcom.2025.108108

Alexandros Stoltidis, Kostas Choumas, Thanasis Korakis

{"title":"Active queue management in 5G and beyond cellular networks using Machine Learning","authors":"Alexandros Stoltidis, Kostas Choumas, Thanasis Korakis","doi":"10.1016/j.comcom.2025.108108","DOIUrl":"10.1016/j.comcom.2025.108108","url":null,"abstract":"<div><div>This paper proposes a state-of-the-art framework for adapting Active Queue Management (AQM) in 5G and beyond cellular networks with disaggregated Radio Access Network (RAN) deployments. While existing AQM algorithms effectively mitigate bufferbloat in monolithic RAN deployments, their potential in disaggregated ones remains largely unexplored. This gap particularly relates to AQM algorithms relying on communication between layers distributed across distinct network entities to operate. Our research explores the current literature on AQM, identifies the gaps regarding disaggregated deployments, and introduces a comprehensive framework that employs Artificial Intelligence (AI) and Machine Learning (ML) within the RAN Intelligent Controller (RIC) for adapting AQM in such deployments. We evaluate our novel solution on a previously proposed AQM algorithm which requires cross-layer communication, using OpenAirInterface5G (OAI5G) to deploy a disaggregated RAN and a connected User Equipment (UE) that experiences realistic network conditions, including noise and mobility. Finally, we assess its accuracy through the Quality of Service (QoS) achieved for our disaggregated deployment on the NITOS testbed.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"236 ","pages":"Article 108108"},"PeriodicalIF":4.5,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143580333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

In-time conditional handover for B5G/6G

IF 4.5 3区计算机科学

Computer Communications Pub Date : 2025-02-27 DOI: 10.1016/j.comcom.2025.108107

Sardar Jaffar Ali , Syed M. Raza , Huigyu Yang , Duc Tai Le , Rajesh Challa , Moonseong Kim , Hyunseung Choo

{"title":"In-time conditional handover for B5G/6G","authors":"Sardar Jaffar Ali , Syed M. Raza , Huigyu Yang , Duc Tai Le , Rajesh Challa , Moonseong Kim , Hyunseung Choo","doi":"10.1016/j.comcom.2025.108107","DOIUrl":"10.1016/j.comcom.2025.108107","url":null,"abstract":"<div><div>Conditional Handover (CHO) by the 3rd Generation Partnership Project (3GPP) enables efficient user mobility between Base Stations (BSs) by preselecting and preparing Target BSs (T-BSs). However, CHO relies on signal strength for T-BS selection, leading to resource blocking on multiple T-BSs due to signal fluctuations. Existing state-of-the-art methods use deep learning to narrow the list of T-BSs but still lack an effective method for resource reservation timing. This paper presents in-time CHO (iCHO) which exploits historical mobility data to estimate user dwell time at the current BS to reduce resource reservation duration. The proposed iCHO employs a Multivariate Multi-output Single-step Prediction (MMSP) model that leverages a multi-task learning approach to simultaneously predict the minimal list of required T-BSs together with the user dwell time. The model demonstrates remarkable performance across two mobility datasets of different scales, achieving T-BS prediction accuracies of 98% and 95%. It also ensures a 100% handover success rate with a minimum of three and four predicted T-BSs for both datasets, respectively, significantly limiting the list of T-BSs. Moreover, the MMSP model achieves a Mean Absolute Error (MAE) of 19s and 45s when predicting the user’s dwell time at the current BS. By utilizing these predictions, iCHO reserves resources at the minimum number of T-BSs immediately before handover. Thus, iCHO can save up to 99% of resources from blockage as compared to the CHO, enabling operators to increase revenue by serving up to eighteen more users with the saved resources.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"236 ","pages":"Article 108107"},"PeriodicalIF":4.5,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143580331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancing the ACME protocol to automate the management of all X.509 web certificates (Extended version)

IF 4.5 3区计算机科学

Computer Communications Pub Date : 2025-02-27 DOI: 10.1016/j.comcom.2025.108106

David A. Cordova Morales , Ahmad Samer Wazan , David W. Chadwick , Romain Laborde , April Rains Reyes Maramara

{"title":"Enhancing the ACME protocol to automate the management of all X.509 web certificates (Extended version)","authors":"David A. Cordova Morales , Ahmad Samer Wazan , David W. Chadwick , Romain Laborde , April Rains Reyes Maramara","doi":"10.1016/j.comcom.2025.108106","DOIUrl":"10.1016/j.comcom.2025.108106","url":null,"abstract":"<div><div>X.509 Public Key Infrastructures (PKIs) are widely used for managing X.509 Public Key Certificates (PKCs) to allow for secure communications and authentication on the Internet. PKCs are issued by a trusted third-party Certification Authority (CA), which is responsible for verifying the certificate requester’s information. Recent developments in web PKI show a high proliferation of Domain Validated (DV) certificates but a decline in Extended Validated (EV) certificates, indicating poor authentication of the entities behind web services. The ACME protocol facilitates the deployment of Web Certificates by automating their management. However, it is only limited to DV certificates. This paper proposes an enhancement to the ACME protocol for automating all types of Web X.509 PKCs by using W3C Verifiable Credentials (VCs) to assert a requester’s claims. We argue that any CA’s requirements for issuing a PKC can be expressed as a set of VCs returned in a Verifiable Presentation (VP) that could facilitate the issuance of high-profile certificates such as EV certificates. We also propose a generic communication workflow to request and present VPs, which interact with our ACME enhancement. In this regard, we present proof of our approach by using the OpenID for Verifiable Presentation protocol (OID4VP) to request and present VPs. To assess the feasibility of our solution, we conduct a complexity analysis, evaluating both computational and communication overhead compared to the standard ACME protocol. Finally, we present an implementation of our solution as proof-of-concept.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"236 ","pages":"Article 108106"},"PeriodicalIF":4.5,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143579862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multi-layer guided reinforcement learning task offloading based on Softmax policy in smart cities

IF 4.5 3区计算机科学

Computer Communications Pub Date : 2025-02-17 DOI: 10.1016/j.comcom.2025.108105

Bin Wu , Liwen Ma , Yu Ji , Jia Cong , Min Xu , Jie Zhao , Yue Yang

{"title":"Multi-layer guided reinforcement learning task offloading based on Softmax policy in smart cities","authors":"Bin Wu , Liwen Ma , Yu Ji , Jia Cong , Min Xu , Jie Zhao , Yue Yang","doi":"10.1016/j.comcom.2025.108105","DOIUrl":"10.1016/j.comcom.2025.108105","url":null,"abstract":"<div><div>Edge computing is an effective measure for addressing the high demand for computing power on the end-side due to dense task distribution in the mobile Internet. In the case of limited device resources and computing power, how to optimize the task offloading decision has become an important issue for improving computing efficiency. We improve the heuristic algorithm by combining the characteristics of intensive tasks, and optimize the task offloading decision at a lower cost. To overcome the limitation of requiring a large amount of real-time information, we utilize the RL algorithm and design a new reward function to enable the agent to learn from its interactions with the environment. Aiming at the poor performance of the system in the uncertain initial environment, we propose a Q-learning scheme based on the Softmax strategy for the multi-layer agent RL framework. The offloading process is optimized by coordinating agents with different views of the environment between each layer, while balancing the exploration and utilization relationship to improve the performance of the algorithm in a more complex dynamic environment. The experimental results show that in the mobile environment with high device density and diverse tasks, the proposed algorithm achieves significant improvements in key indicators such as task success rate, waiting time, and energy consumption. In particular, it exhibits excellent robustness and efficiency advantages in complex dynamic environments, far exceeding the current benchmark algorithm.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"235 ","pages":"Article 108105"},"PeriodicalIF":4.5,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143453713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

DFFL: A dual fairness framework for federated learning

IF 4.5 3区计算机科学

Computer Communications Pub Date : 2025-02-17 DOI: 10.1016/j.comcom.2025.108104

Kaiyue Qi, Tongjiang Yan, Pengcheng Ren, Jianye Yang, Jialin Li

{"title":"DFFL: A dual fairness framework for federated learning","authors":"Kaiyue Qi, Tongjiang Yan, Pengcheng Ren, Jianye Yang, Jialin Li","doi":"10.1016/j.comcom.2025.108104","DOIUrl":"10.1016/j.comcom.2025.108104","url":null,"abstract":"<div><div>Federated learning (FL) is an emerging paradigm of distributed machine learning that facilitates collaborative training of a global model across multiple clients while preserving client-side data privacy. However, current equality fairness methodologies aim to maintain a more uniform performance distribution across clients, but they fail to consider the varying contributions of different clients. In contrast, collaboration fairness takes into account the contributions of clients but may exclude low-contributing clients in pursuit of the interests of high-contributing clients. To address these concerns, this paper proposes a novel Dual Fair Federated Learning (DFFL) framework. Specifically, we combine the concept of cosine annealing to evaluate each client’s contribution from two perspectives. Then, we utilize client’s contribution as the aggregation weight of the global model to improve the global model accuracy. Additionally, we introduce a personalized design and utilize client’s contribution as a regularization coefficient to achieve dual fairness. Furthermore, we conduct a theoretical analysis of the convergence of the global model. Finally, through comprehensive experiments on benchmark datasets, we demonstrate that our method achieves competitive predictive accuracy and dual fairness.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"235 ","pages":"Article 108104"},"PeriodicalIF":4.5,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143444666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Secrecy performance optimization for UAV-based relay NOMA systems with friendly jamming

IF 4.5 3区计算机科学

Computer Communications Pub Date : 2025-02-17 DOI: 10.1016/j.comcom.2025.108086

Thanh Trung Nguyen , Tran Manh Hoang , Phuong T. Tran

{"title":"Secrecy performance optimization for UAV-based relay NOMA systems with friendly jamming","authors":"Thanh Trung Nguyen , Tran Manh Hoang , Phuong T. Tran","doi":"10.1016/j.comcom.2025.108086","DOIUrl":"10.1016/j.comcom.2025.108086","url":null,"abstract":"<div><div>Friendly jamming and relay are effective schemes in physical layer security (PLS) for enhancing security in wireless communication. By deploying unmanned aerial vehicle (UAV)-assisted Non-Orthogonal Multiple Access (NOMA) transmission can extend coverage and enhancing spectrum efficiency. This paper studies the physical layer security of an UAV-based relay NOMA system, consisting of a source, multiple users, and an eavesdropper. To enhance secrecy performance, an additional UAV is employed to transmit jamming signals to the eavesdropper. Moreover, for a more practical approach, we also consider the imperfect collaboration between the jammer device and the legitimate user. The minimum average secrecy rate (MASR) of the users is maximized, assuming that the eavesdropper is capable of intercepting signals both from the source and from the relay UAV. An efficient iterative algorithm is proposed to solve the MASR maximum problem by optimizing UAV trajectories, transmit power, and power allocation coefficients. Simulation results demonstrate that the proposed system achieves 238% better MASR than the system without friendly jamming signals and 633% better than the non-optimal system. In addition, the ability to decode the received signal using successive interference cancellation also significantly affects the MASR of users in the system.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"235 ","pages":"Article 108086"},"PeriodicalIF":4.5,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Incentive mechanisms for non-proprietary vehicles in vehicular crowdsensing with budget constraints 有预算限制的车辆众包中的非专有车辆激励机制

IF 4.5 3区计算机科学

Computer Communications Pub Date : 2025-02-14 DOI: 10.1016/j.comcom.2025.108083

Zhirui Feng, Yantao Yu, Guojin Liu, Yang Jiang, TianCong Huang

{"title":"Incentive mechanisms for non-proprietary vehicles in vehicular crowdsensing with budget constraints","authors":"Zhirui Feng, Yantao Yu, Guojin Liu, Yang Jiang, TianCong Huang","doi":"10.1016/j.comcom.2025.108083","DOIUrl":"10.1016/j.comcom.2025.108083","url":null,"abstract":"<div><div>Vehicular crowdsensing (VCS) utilizes the onboard sensors and computational capabilities of smart vehicles to collect data across diverse regions. Non-dedicated vehicles, due to their lower cost and broad distribution, have emerged as a central focus in VCS research. However, their trajectories are often concentrated in urban areas, resulting in uneven data coverage. Existing incentive mechanisms primarily rely on platforms to dynamically adjust task allocation based on vehicle trajectory predictions. Yet, they frequently neglect the influence of geographic locations on vehicle routing choices and fail to incentivize proactive route planning. To address this, we propose a novel two-phase incentive mechanism that, for the first time, incorporates a <em><strong>willingness to traverse</strong></em> factor. This mechanism aims to maximize spatial coverage within a limited budget by encouraging vehicles to voluntarily traverse remote areas to complete tasks. In the initial phase, a multi-agent deep reinforcement learning algorithm dynamically adjusts each vehicle’s route and quote price, which is then reported to the platform. In the second phase, the platform allocates tasks and adjusts compensation based on the provided routes and quotes to optimize overall platform benefits. Experimental results show that our mechanism effectively balances platform and vehicle benefits, achieving optimal outcomes even under budget constraints.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"235 ","pages":"Article 108083"},"PeriodicalIF":4.5,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Load-balanced multi-user mobility-aware task offloading in multi-access edge computing

IF 4.5 3区计算机科学

Computer Communications Pub Date : 2025-02-13 DOI: 10.1016/j.comcom.2025.108102

Shanchen Pang, Meng Zhou, Haiyuan Gui, Xiao He, Nuanlai Wang, Luqi Wang

{"title":"Load-balanced multi-user mobility-aware task offloading in multi-access edge computing","authors":"Shanchen Pang, Meng Zhou, Haiyuan Gui, Xiao He, Nuanlai Wang, Luqi Wang","doi":"10.1016/j.comcom.2025.108102","DOIUrl":"10.1016/j.comcom.2025.108102","url":null,"abstract":"<div><div>In scenarios with dense user network service requests, multi-access edge computing demonstrates significant advantages in reducing user device load and decreasing service response time. However, the dynamic changes in user trajectories cause edge server load fluctuations, inevitably impacting the overall service processing performance. To tackle this problem, this paper introduces a load-balanced multi-user mobility-aware service request offloading method, achieving efficient service request offloading in mobile user scenarios. Specifically, this paper divides the service request offloading problem into two stages: dynamic edge server allocation and real-time offloading decision generation. In the first stage, users are allocated edge servers based on their location distribution, implementing an adaptive decreasing variance optimization server load balancing algorithm to achieve edge server load balancing. In the second stage, based on the edge server allocation results from the first stage, a latency performance self-optimizing task offloading decision-making algorithm is employed to minimize the processing latency of user requests, utilizing dueling double deep Q-network to generate real-time decisions on whether to offload service requests to the corresponding edge servers. According to experimental results, the proposed algorithm markedly decreases the processing latency of user network service requests in scenarios of different scales, with an average task completion rate of 99.94%. This effectively addresses the problem of inefficient processing requests caused by load fluctuations due to user movement in multi-access edge computing.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"235 ","pages":"Article 108102"},"PeriodicalIF":4.5,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143420581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cloud-edge-end integrated Artificial intelligence based on ensemble learning

IF 4.5 3区计算机科学

Computer Communications Pub Date : 2025-02-13 DOI: 10.1016/j.comcom.2025.108103

Zhen Gao , Daning Su , Shuang Liu , Yuqi Zhang , Chenyang Wang , Cheng Zhang , Xiaofei Wang , Tarik Taleb

{"title":"Cloud-edge-end integrated Artificial intelligence based on ensemble learning","authors":"Zhen Gao , Daning Su , Shuang Liu , Yuqi Zhang , Chenyang Wang , Cheng Zhang , Xiaofei Wang , Tarik Taleb","doi":"10.1016/j.comcom.2025.108103","DOIUrl":"10.1016/j.comcom.2025.108103","url":null,"abstract":"<div><div>Deep neural networks (DNNs) have been extensively used in the domains of artificial intelligence (AI) applications. Their inherent complexity primarily drives the deployment of DNN models in cloud environments. However, the geographical distance between the cloud and the end-users fails to meet the low-latency requirements of time-sensitive applications. Edge computing has emerged as a viable way to address this issue, nevertheless, the inherent constraints of limited resources on edge servers pose challenges in supporting intricate models. Solutions relying on network compression or model segmentation often fall short in meeting both performance and reliability needs. For the few ensemble-based solutions, the diversity between base models is not fully explored, and the low-latency advantage of edge computing is not fully utilized. In this paper, we propose a cloud–edge-end integrated approach for building an efficient and reliable DNN inference platform based on ensemble learning. In this design, heterogeneous models are trained on the cloud according to the resource constraints of edge servers, and the inference process is performed independently on each edge server, whose outputs are combined at the end-user side to get the final result. Furthermore, a diversity-based deployment scheme is proposed to build a user-centric network for edge AI. The generation of base models is explored, and the effectiveness of the proposed approach is demonstrated through two case studies.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"235 ","pages":"Article 108103"},"PeriodicalIF":4.5,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143420580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0