IEEE Transactions on Green Communications and Networking最新文献_第8页

Energy-Spectral Efficiency Trade-Off in IRS-Assisted NOMA Systems: A Weighted Product Method irs辅助NOMA系统的能谱效率权衡：加权乘积法

IF 5.3 2区计算机科学

IEEE Transactions on Green Communications and Networking Pub Date : 2024-07-10 DOI: 10.1109/TGCN.2024.3426311

Haitham Al-Obiedollah;Haythem Bany Salameh;Sharief Abdel-Razeq

{"title":"Energy-Spectral Efficiency Trade-Off in IRS-Assisted NOMA Systems: A Weighted Product Method","authors":"Haitham Al-Obiedollah;Haythem Bany Salameh;Sharief Abdel-Razeq","doi":"10.1109/TGCN.2024.3426311","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3426311","url":null,"abstract":"The deployment of intelligent reflecting surfaces (IRS) in non-orthogonal multiple access (NOMA), known as IRS-assisted NOMA-based systems, has recently been considered a potential solution to address the complicated demands of beyond-fifth-generation communication networks. This paper investigates a multi-objective allocation resource allocation technique for an IR-assisted hybrid time division multiple access (TDMA)-NOMA network. To reflect the requirements of such a system, two conflicting performance metrics, namely energy efficiency (EE) and spectral efficiency (SE), are simultaneously optimized under a set of quality-of-service constraints. The proposed SE-EE trade-off design is formulated as a multi-objective optimization (MOO) framework. However, such an MOO problem cannot be solved by conventional approaches. Therefore, the weighted product method (WPM) is proposed to transform the MOO problem into a conventional single-objective optimization (SOO) problem. Meanwhile, the SOO problem through the WPM approach is non-convex in nature, where the optimization parameters, namely the power allocation and the reflecting coefficients of the IRS elements, are jointly designed. As a result, an iterative technique is designed to address this problem and assess the optimization variables. The simulation results demonstrate that the proposed WPM for the SE-EE trade-off resource allocation technique can balance competing optimization variables alongside meeting the system’s demands.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 2","pages":"635-644"},"PeriodicalIF":5.3,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144117443","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

AoI-Aware Energy Efficiency Resource Allocation for Integrated Satellite-Terrestrial IoT Networks 基于aoi的星地物联网综合网络能源效率资源分配

IF 5.3 2区计算机科学

IEEE Transactions on Green Communications and Networking Pub Date : 2024-07-10 DOI: 10.1109/TGCN.2024.3425848

Qingming Wang;Xiao Liang;Hua Zhang;Linghui Ge

{"title":"AoI-Aware Energy Efficiency Resource Allocation for Integrated Satellite-Terrestrial IoT Networks","authors":"Qingming Wang;Xiao Liang;Hua Zhang;Linghui Ge","doi":"10.1109/TGCN.2024.3425848","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3425848","url":null,"abstract":"Integrated satellite and terrestrial network (ISTN) is a potential technology to achieve ubiquitous and reliable broadband communication for Internet of Things (IoT) devices. Timely delivery of information updates represents a pivotal metric in IoT networks. However, due to the limited satellite transmission resources and the huge propagation delay caused by long distance from satellites to the Earth, ISTN faces great challenges in ensuring such freshness. Moreover, energy efficiency (EE) is also a crucial factor in ISTN with multiple antennas serving multiple users. In this research, we incorporate Age of Information (AoI) as a metric to ensure the information freshness of all IoT devices and design an AoI-aware EE resource allocation scheme. We maximize the system average EE by jointly optimizing the beamforming of Low Earth Orbit (LEO) satellites and base station (BS), and scheduling while maintaining the maximum AoI constraints of all IoT devices. To solve such a difficult problem, a Lyapunov drift-plus-penalty approach is leveraged to transform the original dynamic resource allocation problem into a deterministic problem, which is efficiently solved by an alternating optimization. Compared with existing schemes, our proposed scheme achieves the highest average EE. Our simulations also verify the tradeoff between average EE and information freshness.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 1","pages":"125-139"},"PeriodicalIF":5.3,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Adaptive Routing Mechanism for LEO Satellite Network Based on Control Domain Partition 基于控制域划分的LEO卫星网络自适应路由机制

IF 5.3 2区计算机科学

IEEE Transactions on Green Communications and Networking Pub Date : 2024-07-09 DOI: 10.1109/TGCN.2024.3425458

Puning Zhang;Ziyun Xian;Mingjun Liao;Haiyun Huang;Junyan Yang

{"title":"Adaptive Routing Mechanism for LEO Satellite Network Based on Control Domain Partition","authors":"Puning Zhang;Ziyun Xian;Mingjun Liao;Haiyun Huang;Junyan Yang","doi":"10.1109/TGCN.2024.3425458","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3425458","url":null,"abstract":"Low Earth Orbit (LEO) satellite network has the characteristics of low delay, low propagation loss, high bandwidth, and seamless coverage, which is the cornerstone of space-air-ground integrated network. However, the complex topology and time-varying link state of LEO lead to extremely unstable data routing. Existing routing research faces the challenges of large link information update delay, high routing table storage, and query overhead, which seriously affect satellite data transmission, onboard computing, and storage efficiency. To address the above issues, an adaptive routing mechanism based on control domain partition is proposed, considering the dynamic time-varying characteristics of LEO satellite constellation topology and inter-satellite link. Specifically, a non-dominated sorting-based control domain partition architecture is designed to manage the satellite domain for reducing control delay and improving link information update efficiency. Then a distributed routing method for control domain division is proposed to sense the link status of adjacent control domains rather than the entire satellite network, so as to alleviate the problems of high storage and query complexity and slow update of link information. Furthermore, a link situation aware routing decision-making method is devised to accurately perceive the link situation and achieve optimal path decision-making. The simulation results demonstrate that the proposed mechanism respectively improves the network performance by about 12%, 22%, and 14% in terms of end-to-end average delay, packet loss rate, and throughput.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 1","pages":"70-82"},"PeriodicalIF":5.3,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

An Energy Effective RIS-Assisted Multi-UAV Coverage Scheme for Fairness-Aware Ground Terminals 一种面向公平感知地面终端的高能效ris辅助多无人机覆盖方案

IF 5.3 2区计算机科学

IEEE Transactions on Green Communications and Networking Pub Date : 2024-07-08 DOI: 10.1109/TGCN.2024.3424980

Na Lin;Tianxiong Wu;Liang Zhao;Ammar Hawbani;Shaohua Wan;Mohsen Guizani

{"title":"An Energy Effective RIS-Assisted Multi-UAV Coverage Scheme for Fairness-Aware Ground Terminals","authors":"Na Lin;Tianxiong Wu;Liang Zhao;Ammar Hawbani;Shaohua Wan;Mohsen Guizani","doi":"10.1109/TGCN.2024.3424980","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3424980","url":null,"abstract":"Unmanned aerial vehicle (UAV)-assisted communications are critical in regional wireless networks. Using reconfigurable intelligent surfaces (RISs) can significantly improve UAVs’ throughput and energy efficiency. Due to limited communications resources, the data transfer rate of ground terminals (GTs) could be slower, and the throughput may be low. Using RIS-assisted UAVs can effectively address these limitations. This paper focuses on optimizing the three-dimensional (3D) trajectory of the UAV and the scheduling order of the GTs and designing the phase shift of the RIS to maximize energy efficiency while meeting the limited energy and fair service constraints in the case of fair service GTs. To address the non-convexity of this problem, we propose a triple deep q-network (TDQN) algorithm, which better avoids the overestimation problem during the optimization process. We propose an improved k-density-based spatial clustering of applications with noise (K-DBSCAN) clustering algorithm, which is characterized by the ability to output the initial movement range of the UAV and prune the deep reinforcement learning (DRL) state space by the initial movement range to speed up DRL training based on the completion of the partitioning deployment work. A fair screening mechanism is proposed to satisfy the fairness constraint. The results show that the TDQN algorithm is 2.9% more energy efficient than the baseline. The K-DBSCAN algorithm speeds up the training of the TDQN algorithm by 59.4%. The fair screening mechanism reduces the throughput variance from an average of 114099.9 to an average of 46.9.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 1","pages":"164-176"},"PeriodicalIF":5.3,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Accelerating Federated Learning With Model Segmentation for Edge Networks 边缘网络模型分割加速联邦学习

IF 5.3 2区计算机科学

IEEE Transactions on Green Communications and Networking Pub Date : 2024-07-08 DOI: 10.1109/TGCN.2024.3424552

Mingda Hu;Jingjing Zhang;Xiong Wang;Shengyun Liu;Zheng Lin

{"title":"Accelerating Federated Learning With Model Segmentation for Edge Networks","authors":"Mingda Hu;Jingjing Zhang;Xiong Wang;Shengyun Liu;Zheng Lin","doi":"10.1109/TGCN.2024.3424552","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3424552","url":null,"abstract":"In the rapidly evolving landscape of distributed learning strategies, Federated Learning (FL) stands out for its features such as model training on resource-constrained edge devices and high data security. However, the growing complexity of neural network models produces two challenges such as communication bottleneck and resource under-utilization, especially in edge networks. To overcome these challenges, this paper introduces a novel framework by realizing the Parallel Communication-Computation Federated Learning Mode (P2CFed). Specifically, we design an adaptive layer-wise model segmentation strategy according to the wireless environments and computing capability of edge devices, which enables parallel training and transmission within different sub-models. In this way, parameter delivery takes place throughout the training process, thus considerably alleviating the communication overhead. Meanwhile, we also propose a joint optimization scheme with regard to the subchannel allocation, power control, and segmentation layer selection, which is then transformed into an iteration search process for obtaining optimal results. We have conducted extensive simulations to validate the effectiveness of P2CFed when compared with state-of-the-art benchmarks in terms of communication overhead and resource utilization. It also unveils that P2CFed brings a faster convergence rate and smaller training delay compared to traditional FL approaches.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 1","pages":"242-254"},"PeriodicalIF":5.3,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

An AI-Enhanced Multipath TCP Scheduler for Open Radio Access Networks 面向开放式无线接入网络的人工智能增强型多路径 TCP 调度器

IF 5.3 2区计算机科学

IEEE Transactions on Green Communications and Networking Pub Date : 2024-07-05 DOI: 10.1109/TGCN.2024.3424202

Wenxuan Qiao;Yuyang Zhang;Ping Dong;Xiaojiang Du;Hongke Zhang;Mohsen Guizani

{"title":"An AI-Enhanced Multipath TCP Scheduler for Open Radio Access Networks","authors":"Wenxuan Qiao;Yuyang Zhang;Ping Dong;Xiaojiang Du;Hongke Zhang;Mohsen Guizani","doi":"10.1109/TGCN.2024.3424202","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3424202","url":null,"abstract":"Multipath transmission technology has recently emerged as a crucial solution to address bandwidth resource constraints and uneven load distribution across access points caused by the surge in data-intensive applications. A well-designed multipath scheduler can improve the quality of service and balance the power consumption in evolving Open Radio Access Networks (O-RANs). However, wireless channel instability and RAN heterogeneity challenge the scheduler’s bandwidth aggregation capability. This paper introduces a Neural Aggregation Bandwidth Optimization (NABO) scheduler for O-RAN, combining bandwidth prediction with scheduling policy optimization. NABO employs an innovative approach by first constructing a Transformer-optimized Throughput (ToT) prediction model based on historical path characteristics. To train the model, we design a system to simulate various network conditions and collect datasets. This model is then integrated into a dual-network collaborative learning framework that combines ToT predictions with heterogeneity levels to guide the scheduler’s optimization process. The ToT model achieves a throughput prediction error of less than 2%. In numerous heterogeneous simulation scenarios and real-world wireless environments, NABO significantly outperforms state-of-the-art multipath transmission methods, with bandwidth aggregation improvements of approximately 51% and 30% over existing benchmarks, respectively. These findings demonstrate NABO’s superior efficacy and potential in enhancing the performance and energy efficiency of O-RANs.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"8 3","pages":"910-923"},"PeriodicalIF":5.3,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142090990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

A Reinforcement Learning-Based Stochastic Game for Energy-Efficient UAV Swarm-Assisted MEC With Dynamic Clustering and Scheduling 基于强化学习的节能无人机群辅助MEC随机博弈动态聚类与调度

IF 5.3 2区计算机科学

IEEE Transactions on Green Communications and Networking Pub Date : 2024-07-05 DOI: 10.1109/TGCN.2024.3424449

Jialiuyuan Li;Changyan Yi;Jiayuan Chen;You Shi;Tong Zhang;Xiaolong Li;Ran Wang;Kun Zhu

{"title":"A Reinforcement Learning-Based Stochastic Game for Energy-Efficient UAV Swarm-Assisted MEC With Dynamic Clustering and Scheduling","authors":"Jialiuyuan Li;Changyan Yi;Jiayuan Chen;You Shi;Tong Zhang;Xiaolong Li;Ran Wang;Kun Zhu","doi":"10.1109/TGCN.2024.3424449","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3424449","url":null,"abstract":"In this paper, we study the energy-efficient unmanned aerial vehicle (UAV) swarm assisted mobile edge computing (MEC) with dynamic clustering and scheduling. In the considered system model, UAVs are divided into multiple swarms, with each swarm consisting of a leader UAV and several follower UAVs. These UAVs serve as mobile edge servers, providing computing services to their covered ground end-users. Unlike existing works, we allow UAVs to dynamically cluster into different swarms, in other words, each follower UAV can change its leader based on the time-varying spatial positions, updated application placement, etc. in a dynamic manner. With the objective of maximizing the long-term energy efficiency of the UAV swarm assisted MEC system, a joint optimization problem of UAV swarm dynamic clustering and scheduling is formulated. Considering the inherent cooperation and competition among intelligent UAVs, we further reformulate this problem as a combination of a series of strongly interconnected multi-agent stochastic games, and theoretically prove the existence of the corresponding Nash Equilibrium (NE). Then, we propose a novel reinforcement learning based UAV swarm dynamic coordination (RLDC) algorithm for obtaining such an equilibrium. Furthermore, the convergence and complexity of the RLDC algorithm are analyzed. Simulations are performed to evaluate the performance of RLDC and illustrate its superiority compared to existing approaches.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 1","pages":"255-270"},"PeriodicalIF":5.3,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

A Novel DCSK-Based Linear Frequency Modulation Waveform Design for Joint Radar and Communication Systems 一种基于dcsk的联合雷达与通信系统线性调频波形设计

IF 5.3 2区计算机科学

IEEE Transactions on Green Communications and Networking Pub Date : 2024-07-03 DOI: 10.1109/TGCN.2024.3422262

Yi Fang;Yuchen Pan;Huan Ma;Dingfei Ma;Mohsen Guizani

{"title":"A Novel DCSK-Based Linear Frequency Modulation Waveform Design for Joint Radar and Communication Systems","authors":"Yi Fang;Yuchen Pan;Huan Ma;Dingfei Ma;Mohsen Guizani","doi":"10.1109/TGCN.2024.3422262","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3422262","url":null,"abstract":"The joint radar and communication (JRC) system is an appealing technology that integrates communication and radar sensing functionalities onto a single hardware equipment. The JRC system’s appeal largely stems from its compact form, reduced power demands, and cost-efficiency. Within this context, we present a novel differential chaos shift keying-based linear frequency modulation waveform design (DCSK-LFM) to execute both communication and radar sensing operations in this paper. The scheme employs the LFM waveform as the fundamental radar waveform, while information symbols are embedded by DCSK modulation. Furthermore, the proposed DCSK-LFM scheme offers a controllable trade-off between the data rate and the maximum detection distance, adjustable through the pulse repetition period. The performance of the proposed DCSK-LFM scheme is carefully analyzed using the spectrum characteristic, bit error rate (BER), and ambiguity function. The effectiveness of the proposed DCSK-LFM scheme is validated by simulation results, demonstrating its notable proficiency in spectral characteristics, BER, and detection accuracy. Moreover, the proposed scheme exhibits a smaller leakage ratio compared to alternative approaches. These findings highlight that the proposed transmission scheme has significant potential for JRC systems.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 1","pages":"354-366"},"PeriodicalIF":5.3,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143403823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Federated Learning Assisted Intelligent IoV Mobile Edge Computing 联邦学习辅助智能车联网移动边缘计算

IF 5.3 2区计算机科学

IEEE Transactions on Green Communications and Networking Pub Date : 2024-07-01 DOI: 10.1109/TGCN.2024.3421357

Haoyu Quan;Qingmiao Zhang;Junhui Zhao

引用次数: 0

GAS: DVFS-Driven Energy Efficiency Approach for Latency-Guaranteed Edge Computing Microservices GAS：延迟保证边缘计算微服务的dvfs驱动的能效方法

IF 5.3 2区计算机科学

IEEE Transactions on Green Communications and Networking Pub Date : 2024-07-01 DOI: 10.1109/TGCN.2024.3420957

Zouhir Bellal;Laaziz Lahlou;Nadjia Kara;Ibtissam El Khayat

{"title":"GAS: DVFS-Driven Energy Efficiency Approach for Latency-Guaranteed Edge Computing Microservices","authors":"Zouhir Bellal;Laaziz Lahlou;Nadjia Kara;Ibtissam El Khayat","doi":"10.1109/TGCN.2024.3420957","DOIUrl":"https://doi.org/10.1109/TGCN.2024.3420957","url":null,"abstract":"Edge computing-based microservices (ECM) are pivotal infrastructure components for latency-critical applications such as Virtual Reality/Augmented Reality (VR/AR) and the Internet of Things (IoT). ECM involves strategically deploying microservices at the network’s edge to fulfill the low latency needs of modern applications. However, achieving efficient resource and energy consumption while meeting the latency requirement in the ECM environment remains challenging. Dynamic Voltage and Frequency Scaling (DVFS) is a common technique to address this issue. It adjusts the CPU frequency and voltage to balance energy cost and performance. However, selecting the optimal CPU frequency depends on the nature of the microservice workload (e.g., CPU-bound, memory-bound, or mixed). Moreover, various microservices with different latency requirement can be deployed on the same edge node. This makes the DVFS application extremely challenging, particularly for a chip-wide DVFS implementation for which CPU cores operate at the same frequency and voltage. To this end, we propose GAS, enerGy Aware microServices edge computing framework, which enables CPU frequency scaling to meet diverse microservice latency requirement with the minimum energy cost. Our evaluation indicates that our CPU scaling policy decreases energy consumption by 5% to 23% compared to Linux governors while maintaining latency requirement and significantly contributing to sustainable edge computing.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 1","pages":"108-124"},"PeriodicalIF":5.3,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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