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An Integrated Blockchain Framework for Secure Data Sharing in IoT Fog Computing 物联网雾计算中安全数据共享的集成区块链框架
IF 6.6 1区 计算机科学
Tsinghua Science and Technology Pub Date : 2024-12-30 DOI: 10.26599/TST.2024.9010082
Peda Narayana Bathula;M. Sreenivasulu
{"title":"An Integrated Blockchain Framework for Secure Data Sharing in IoT Fog Computing","authors":"Peda Narayana Bathula;M. Sreenivasulu","doi":"10.26599/TST.2024.9010082","DOIUrl":"https://doi.org/10.26599/TST.2024.9010082","url":null,"abstract":"The importance of secure data sharing in fog computing is increasing due to the growing number of Internet of Things (IoT) devices. This article addresses the privacy and security issues brought up by data sharing in the context of IoT fog computing. The suggested framework, called “BlocFogSec”, secures key management and data sharing through blockchain consensus and smart contracts. Unlike existing solutions, BlocFogSec utilizes two types of smart contracts for secure key exchange and data sharing, while employing a consensus protocol to validate transactions and maintain blockchain integrity. To process and store data effectively at the network edge, the framework makes use of fog computing, notably reducing latency and raising throughput. BlocFogSec successfully blocks unauthorized access and data breaches by restricting transactions to authorized nodes. In addition, the framework uses a consensus protocol to validate and add transactions to the blockchain, guaranteeing data accuracy and immutability. To compare BlocFogSec's performance to that of other models, a number of simulations are conducted. The simulation results indicate that BlocFogSec consistently outperforms existing models, such as Security Services for Fog Computing (SSFC) and Blockchain-based Key Management Scheme (BKMS), in terms of throughput (up to 5135 bytes per second), latency (as low as 7 ms), and resource utilization (70% to 92%). The evaluation also takes into account attack defending accuracy (up to 100%), precision (up to 100%), and recall (up to 99.6%), demonstrating BlocFogSec's effectiveness in identifying and preventing potential attacks.","PeriodicalId":48690,"journal":{"name":"Tsinghua Science and Technology","volume":"30 3","pages":"957-977"},"PeriodicalIF":6.6,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10817699","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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
An Efficient Quantum Enabled Machine Algorithm by Universal Features for Predicting Botnet Attacks in Digital Twin Enabled IoT Networks 基于通用特征的高效量子机器算法用于预测数字孪生物联网中僵尸网络攻击
IF 6.6 1区 计算机科学
Tsinghua Science and Technology Pub Date : 2024-12-30 DOI: 10.26599/TST.2024.9010052
Katta Rajesh Babu;Naramula Venkatesh;K. Shashidhar;Yellampalli Dasaratha Rami Reddy;K. Naga Prakash
{"title":"An Efficient Quantum Enabled Machine Algorithm by Universal Features for Predicting Botnet Attacks in Digital Twin Enabled IoT Networks","authors":"Katta Rajesh Babu;Naramula Venkatesh;K. Shashidhar;Yellampalli Dasaratha Rami Reddy;K. Naga Prakash","doi":"10.26599/TST.2024.9010052","DOIUrl":"https://doi.org/10.26599/TST.2024.9010052","url":null,"abstract":"In this manuscript, the authors introduce a quantum enabled Reinforcement Algorithm by Universal Features (REMF) as a lightweight solution designed to identify and assess the impact of botnet attacks on 5G Internet of Things (IoT) networks. REMF's primary objective is the swift detection of botnet assaults and their effects, aiming to prevent the initiation of such attacks. The algorithm introduces a novel adaptive classification boosting through reinforcement learning, training on values derived from universal features extracted from network transactions within a given training corpus. During the prediction phase, REMF assesses the Botnet attack confidence of feature values obtained from unlabeled network transactions. It then compares these botnet attack confidence values with the botnet attack confidence of optimal features derived during the training phase to predict the potential impact of the botnet attack, categorizing it as high, moderate, low, or not-an-attack (normal). The performance evaluation results demonstrate that REMF achieves the highest decision accuracy, displaying maximum sensitivity and specificity in predicting the scope of botnet attacks at an early stage. The experimental study illustrates that REMF outperforms existing detection techniques for predicting botnet attacks.","PeriodicalId":48690,"journal":{"name":"Tsinghua Science and Technology","volume":"30 3","pages":"947-956"},"PeriodicalIF":6.6,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10817765","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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
Few-Shot Object Detection via Dual-Domain Feature Fusion and Patch-Level Attention 基于双域特征融合和补丁级关注的小镜头目标检测
IF 6.6 1区 计算机科学
Tsinghua Science and Technology Pub Date : 2024-12-30 DOI: 10.26599/TST.2024.9010031
Guangli Ren;Jierui Liu;Mengyao Wang;Peiyu Guan;Zhiqiang Cao;Junzhi Yu
{"title":"Few-Shot Object Detection via Dual-Domain Feature Fusion and Patch-Level Attention","authors":"Guangli Ren;Jierui Liu;Mengyao Wang;Peiyu Guan;Zhiqiang Cao;Junzhi Yu","doi":"10.26599/TST.2024.9010031","DOIUrl":"https://doi.org/10.26599/TST.2024.9010031","url":null,"abstract":"Few-shot object detection receives much attention with the ability to detect novel class objects using limited annotated data. The transfer learning-based solution becomes popular due to its simple training with good accuracy, however, it is still challenging to enrich the feature diversity during the training process. And fine-grained features are also insufficient for novel class detection. To deal with the problems, this paper proposes a novel few-shot object detection method based on dual-domain feature fusion and patch-level attention. Upon original base domain, an elementary domain with more category-agnostic features is superposed to construct a two-stream backbone, which benefits to enrich the feature diversity. To better integrate various features, a dual-domain feature fusion is designed, where the feature pairs with the same size are complementarily fused to extract more discriminative features. Moreover, a patch-wise feature refinement termed as patch-level attention is presented to mine internal relations among the patches, which enhances the adaptability to novel classes. In addition, a weighted classification loss is given to assist the fine-tuning of the classifier by combining extra features from FPN of the base training model. In this way, the few-shot detection quality to novel class objects is improved. Experiments on PASCAL VOC and MS COCO datasets verify the effectiveness of the method.","PeriodicalId":48690,"journal":{"name":"Tsinghua Science and Technology","volume":"30 3","pages":"1237-1250"},"PeriodicalIF":6.6,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10817768","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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
Blockchain-Driven Secure Data Sharing Framework for Edge Computing Networks 边缘计算网络中区块链驱动的安全数据共享框架
IF 6.6 1区 计算机科学
Tsinghua Science and Technology Pub Date : 2024-12-30 DOI: 10.26599/TST.2024.9010051
Fuad A. M. Al-Yarimi;Ramzi Salah;Khaled Mohamoud
{"title":"Blockchain-Driven Secure Data Sharing Framework for Edge Computing Networks","authors":"Fuad A. M. Al-Yarimi;Ramzi Salah;Khaled Mohamoud","doi":"10.26599/TST.2024.9010051","DOIUrl":"https://doi.org/10.26599/TST.2024.9010051","url":null,"abstract":"This study examines secure and effective data sharing methods for edge computing networks. Traditional methods of sharing data at the edge have issues with security, speed, and consensus. The goal is to develop a Blockchain-based Secure Data Sharing Framework (BSDSF) capable of improving data integrity, latency, and overall network efficiency for edge-cloud computing applications. BSDSF proposes using blockchain technology with Byzantine Fault Tolerance (BFT) and smart contract-based validation as a new method of secure data sharing. It has a two-tiered consensus protocol to meet the needs of edge computing, which requires instantaneous responses. BSDSF employs Byzantine fault tolerance to deal with errors and protect against attacks. Smart contracts automate validation and consensus operations, while edge computing processes data at the attack site. Node validation and failure detection methods monitor network quality and dependability, while system security ensures secure communication between nodes. BSDSF is an important step toward digital freedom and trust by protecting security and improving transaction reliability. The framework demonstrates a reduction in transaction latency by up to 30% and an increase in throughput by 25% compared to traditional edge computing models, positioning BSDSF as a pivotal solution for fostering digital freedom and trust in edge computing environments.","PeriodicalId":48690,"journal":{"name":"Tsinghua Science and Technology","volume":"30 3","pages":"978-997"},"PeriodicalIF":6.6,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10817767","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 Review on Air-Ground Coordination in Mobile Edge Computing: Key Technologies, Applications and Future Directions 移动边缘计算中地空协同:关键技术、应用及未来发展方向
IF 6.6 1区 计算机科学
Tsinghua Science and Technology Pub Date : 2024-12-30 DOI: 10.26599/TST.2024.9010142
Siqi Li;Guoqiang Liu;Li Li;Zhongyuan Zhang;Wenhao Fei;Haolong Xiang
{"title":"A Review on Air-Ground Coordination in Mobile Edge Computing: Key Technologies, Applications and Future Directions","authors":"Siqi Li;Guoqiang Liu;Li Li;Zhongyuan Zhang;Wenhao Fei;Haolong Xiang","doi":"10.26599/TST.2024.9010142","DOIUrl":"https://doi.org/10.26599/TST.2024.9010142","url":null,"abstract":"In recent years, Mobile Edge Computing (MEC) has received extensive research attention due to its characteristics, such as real-time data processing and flexible application deployment. However, traditional MEC server deployment relies on the terrestrial Base Stations (BSs), resulting in high deployment costs and limited coverage range. In response to these challenges, air-ground coordination has emerged, which effectively combines the advantages of edge computing and Unmanned Aerial Vehicles (UAVs), providing an effective architecture for edge intelligence. By utilizing the flexibility of UAVs and empowering them into edge nodes with computing resources, the coverage range of MEC can be expanded, thereby reducing the reliance of edge devices on terrestrial BSs. Furthermore, leveraging terrestrial BSs as supplements to the computing power compensates for relatively limited computational capabilities of UAVs. Although extensive studies have been conducted on air-ground coordination, there are few related summaries of application technologies and prospects. Thus, the key technologies of air-ground coordination and applications are comprehensively reviewed in this paper. Finally, to provide guidance for interested researchers, the development trends and potential applications of air-ground coordination are explored.","PeriodicalId":48690,"journal":{"name":"Tsinghua Science and Technology","volume":"30 3","pages":"1359-1386"},"PeriodicalIF":6.6,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10817761","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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
MDGCN-Lt: Fair Web API Classification with Sparse and Heterogeneous Data Based on Deep GCN MDGCN-Lt:基于深度GCN的稀疏异构数据公平Web API分类
IF 6.6 1区 计算机科学
Tsinghua Science and Technology Pub Date : 2024-12-30 DOI: 10.26599/TST.2024.9010026
Boyuan Yan;Yankun Zhang;Wenwen Gong;Haoyang Wan;Wenwei Wang;Weiyi Zhong;Caixia Bu
{"title":"MDGCN-Lt: Fair Web API Classification with Sparse and Heterogeneous Data Based on Deep GCN","authors":"Boyuan Yan;Yankun Zhang;Wenwen Gong;Haoyang Wan;Wenwei Wang;Weiyi Zhong;Caixia Bu","doi":"10.26599/TST.2024.9010026","DOIUrl":"https://doi.org/10.26599/TST.2024.9010026","url":null,"abstract":"Developers integrate web Application Programming Interfaces (APIs) into edge applications, enabling data expansion to the edge computing area for comprehensive coverage of devices in that region. To develop edge applications, developers search API categories to select APIs that meet specific functionalities. Therefore, the accurate classification of APIs becomes critically important. However, existing approaches, as evident on platforms like programableweb.com, face significant challenges. Firstly, sparsity in API data reduces classification accuracy in works focusing on single-dimensional API information. Secondly, the multidimensional and heterogeneous structure of web APIs adds complexity to data mining tasks, requiring sophisticated techniques for effective integration and analysis of diverse data aspects. Lastly, the long-tailed distribution of API data introduces biases, compromising the fairness of classification efforts. Addressing these challenges, we propose MDGCN-Lt, an API classification approach offering flexibility in using multi-dimensional heterogeneous data. It tackles data sparsity through deep graph convolutional networks, exploring high-order feature interactions among API nodes. MDGCN-Lt employs a loss function with logit adjustment, enhancing efficiency in handling long-tail data scenarios. Empirical results affirm our approach's superiority over existing methods.","PeriodicalId":48690,"journal":{"name":"Tsinghua Science and Technology","volume":"30 3","pages":"1294-1314"},"PeriodicalIF":6.6,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10817770","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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
DEFOG: Deep Learning with Attention Mechanism Enabled Cross-Age Face Recognition 深度学习与注意机制支持跨年龄人脸识别
IF 6.6 1区 计算机科学
Tsinghua Science and Technology Pub Date : 2024-12-30 DOI: 10.26599/TST.2024.9010107
Biaokai Zhu;Lu Li;Xiaochun Hu;Fulin Wu;Zhaojie Zhang;Shengnan Zhu;Yanxi Wang;Jiali Wu;Jie Song;Feng Li;Sanman Liu;Jumin Zhao
{"title":"DEFOG: Deep Learning with Attention Mechanism Enabled Cross-Age Face Recognition","authors":"Biaokai Zhu;Lu Li;Xiaochun Hu;Fulin Wu;Zhaojie Zhang;Shengnan Zhu;Yanxi Wang;Jiali Wu;Jie Song;Feng Li;Sanman Liu;Jumin Zhao","doi":"10.26599/TST.2024.9010107","DOIUrl":"https://doi.org/10.26599/TST.2024.9010107","url":null,"abstract":"As individuals age, their facial features change, which can hinder the accuracy of face recognition technology. To address this challenge, a new cross-age face recognition algorithm, leveraging deep learning and a loss function (Loss), has been proposed in this article. The Retinaface algorithm detects faces in images, while the Resnet-50 model is enhanced by incorporating an attention mechanism and improved softmax loss (Arcface) to extract facial features. This approach has been tested on publicly available and custom-built datasets, and its performance has been compared to other cross-age face recognition techniques. The results show that the model effectively recognizes faces across different age groups.","PeriodicalId":48690,"journal":{"name":"Tsinghua Science and Technology","volume":"30 3","pages":"1342-1358"},"PeriodicalIF":6.6,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10817764","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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
Physical Layer Security for CR-NOMA Network with Cooperative Jamming 具有合作干扰功能的 CR-NOMA 网络的物理层安全性
IF 6.6 1区 计算机科学
Tsinghua Science and Technology Pub Date : 2024-12-09 DOI: 10.26599/TST.2023.9010128
Meiling Li;Peng Xue;Hu Yuan;Yuxing Han
{"title":"Physical Layer Security for CR-NOMA Network with Cooperative Jamming","authors":"Meiling Li;Peng Xue;Hu Yuan;Yuxing Han","doi":"10.26599/TST.2023.9010128","DOIUrl":"https://doi.org/10.26599/TST.2023.9010128","url":null,"abstract":"Cooperative jamming can effectively combat eavesdropping in physical layer security communication without affecting the legal receiver and improve the security performance of the system. This paper introduces cooperative jamming to cognitive radio (CR) networks with non-orthogonal multiple access (NOMA) technology. The secure performance of the considered CR and NOMA (CR-NOMA) network is evaluated using two modes: non-cooperative jamming and cooperative jamming. In particular, the secrecy outage probabilities (SOPs) of the primary user (PU) in the two modes are derived under Rician fading channels, based on which, the influences of the transmission signal-to-noise ratio (SNR) of secondary users (SUs), the number of SUs, the secrecy rate, and the power allocation coefficient on the SOPs of PU are analyzed thereafter. Both analysis and simulation results show that cooperative jamming effectively prevents eavesdropping behaviour, which reduces the SOP of PU compared to non-cooperative jamming. We also show that the transmission SNR, the number of SUs, the secrecy rate, and the power distribution coefficients greatly influence performance improvement.","PeriodicalId":48690,"journal":{"name":"Tsinghua Science and Technology","volume":"30 2","pages":"708-720"},"PeriodicalIF":6.6,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10786938","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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
Wearable Continuous Blood Pressure Monitoring Based on Pulsatile Cycle Volume Adjustment Method 基于脉动周期量调节法的可穿戴式连续血压监测系统
IF 6.6 1区 计算机科学
Tsinghua Science and Technology Pub Date : 2024-12-09 DOI: 10.26599/TST.2024.9010043
Pang Wu;Zhongrui Bai;Pan Xia;Lirui Xu;Peng Wang;Xianxiang Chen;Lidong Du;Ziqing Hei;Weifeng Yao;Xiaoran Li;Zhan Zhao;Zhen Fang
{"title":"Wearable Continuous Blood Pressure Monitoring Based on Pulsatile Cycle Volume Adjustment Method","authors":"Pang Wu;Zhongrui Bai;Pan Xia;Lirui Xu;Peng Wang;Xianxiang Chen;Lidong Du;Ziqing Hei;Weifeng Yao;Xiaoran Li;Zhan Zhao;Zhen Fang","doi":"10.26599/TST.2024.9010043","DOIUrl":"https://doi.org/10.26599/TST.2024.9010043","url":null,"abstract":"Accurate and portable Blood Pressure (BP) monitoring is vital for managing cardiovascular diseases. However, existing wearable continuous BP monitoring technologies are often inaccurate and rely on external calibration, limiting their practical application in continuous BP monitoring. To address this challenge, we have developed a Wearable continuous non-invasive BP Monitor (WeBPM) equipped with a finger cuff sensor, capable of monitoring BP continuously and accurately within medical-grade precision. WeBPM integrates advanced finger oscillographic BP measurement technology to provide reliable self-calibration functionality. Moreover, Pulsatile Cycle Volume Adjustment Method (PCVAM) we proposed for the closed-loop phase can continuously track changes in vasomotor tone under a controlled frequency based on pulsatile cycles, thereby enabling continuous BP measurement. In comparative experiments with the Nexfin monitor, WeBPM demonstrates excellent performance in induced dynamic BP experiments, with measurement errors of (-1.4 ± 6.24) mmHg for Systolic BP (SBP) and (-0.82 ± 4.83) mmHg for Diastolic BP (DBP). Additionally, compared to clinical invasive reference measurements, WeBPM's SBP and DBP measurement errors are (-1.74 ± 4.9) mmHg and (0.37 ± 3.28) mmHg, respectively, further proving its outstanding performance. These results highlight WeBPM's potential in personalized health management and remote monitoring, offering a new solution for continuous non-invasive BP monitoring.","PeriodicalId":48690,"journal":{"name":"Tsinghua Science and Technology","volume":"30 2","pages":"650-669"},"PeriodicalIF":6.6,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10786939","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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
Efficient Maximum Vertex (k,ℓ)-Biplex Computation on Bipartite Graphs 双向图上的高效最大顶点 (k,ℓ)- 双工计算
IF 6.6 1区 计算机科学
Tsinghua Science and Technology Pub Date : 2024-12-09 DOI: 10.26599/TST.2024.9010009
Hongru Zhou;Shengxin Liu;Ruidi Cao
{"title":"Efficient Maximum Vertex (k,ℓ)-Biplex Computation on Bipartite Graphs","authors":"Hongru Zhou;Shengxin Liu;Ruidi Cao","doi":"10.26599/TST.2024.9010009","DOIUrl":"https://doi.org/10.26599/TST.2024.9010009","url":null,"abstract":"Cohesive subgraph search is a fundamental problem in bipartite graph analysis. Given integers \u0000<tex>$k$</tex>\u0000 and ℓ, a (k,ℓ)-biplex is a cohesive structure which requires each vertex to disconnect at most \u0000<tex>$k$</tex>\u0000 or \u0000<tex>$l$</tex>\u0000 vertices in the other side. Computing (k,ℓ)-biplexes has been a popular research topic in recent years and has various applications. However, most existing studies considered the problem of finding (k, ℓ)-biplex with the largest number of edges. In this paper, we instead consider another variant and focus on the maximum vertex (k, ℓ)-biplex problem which aims to search for a (k, ℓ)-biplex with the maximum cardinality. We first show that this problem is Non-deterministic Polynomial-time hard (NP-hard) for any positive integers \u0000<tex>$k$</tex>\u0000 and ℓ while max{k, ℓ} is at least 3. Guided by this negative result, we design an efficient branch-and-bound algorithm with a novel framework. In particular, we introduce a branching strategy based on whether there is a pivot in the current set, with which our proposed algorithm has the time complexity of γ\u0000<sup>n</sup>\u0000n\u0000<sup>O(1)</sup>\u0000, where γ< 2. In addition, we also apply multiple speed-up techniques and various pruning strategies. Finally, we conduct extensive experiments on various real datasets which demonstrate the efficiency of our proposed algorithm in terms of running time.","PeriodicalId":48690,"journal":{"name":"Tsinghua Science and Technology","volume":"30 2","pages":"569-584"},"PeriodicalIF":6.6,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10786929","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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
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