Concurrency and Computation-Practice & Experience最新文献

{"title":"Customer-Satisfaction and Risk-Aware Pricing Policy for Profit Maximization in Cloud Computing","authors":"Siyi Chen,&nbsp;Haiyang Kuang,&nbsp;Jiaxin Zhou,&nbsp;Jin Liu","doi":"10.1002/cpe.70075","DOIUrl":"https://doi.org/10.1002/cpe.70075","url":null,"abstract":"<div>\u0000 \u0000 <p>Cloud computing has been attracting increasing concern due to its remarkable flexibility and substantial economic returns. As a crucial feature of cloud computing, cloud service providers typically offer customers various resources through on-demand services and charge them accordingly. Considering servers as the service carriers in cloud computing, their availability may sometimes be affected by potential uncertainties, which can lead to temporary server breakdowns. It should be noted that such cases related to the availability of servers have rarely been examined in the profit maximization problem. In this paper, an optimal configuration scheme for addressing the issue of profit maximization in the cloud service system is proposed, taking server breakdowns into account. By introducing the concept of generalized service time, the probability density function of waiting time is initially derived. Owing to the complexity of the designed function, a two-stage fitting method is employed to obtain its approximation, thereby significantly reducing the analysis difficulty. On this basis, considering the average waiting time and server breakdowns, a compensation mechanism is adopted to design the pricing strategy for customers. Then, the revenue, cost, and profit models of cloud service providers are constructed. Since the optimal solution of the profit model is difficult to calculate due to its complexity, a heuristic algorithm is introduced to solve its numerical solution. Finally, the proposed scheme is verified through a series of numerical simulations, and the results indicate that the profits of cloud service providers and customer experience can be satisfied simultaneously.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"37 9-11","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143818766","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":"Variantrank: Business Process Event Log Sampling Based on Importance of Trace Variants","authors":"Jiawei Chen,&nbsp;Jiayi Zhong,&nbsp;Guosheng Kang,&nbsp;Jianxun Liu,&nbsp;Yiping Wen","doi":"10.1002/cpe.70092","DOIUrl":"https://doi.org/10.1002/cpe.70092","url":null,"abstract":"<div>\u0000 \u0000 <p>To address the issues of low sampling quality and efficiency in processing large-scale event logs in existing business process event log sampling methods, a new method, named VariantRank, is proposed, which is based on the importance of trace variants. First, the importance of each trace variant is calculated based on the activity importance and the importance of directly-follow relationships within the trace variants. Then, the trace variants are ranked according to their importance. Finally, based on the given sampling rate and the ranking of trace variants, the final sampling is performed to obtain the sample event logs. The effectiveness of the proposed sampling method is evaluated in terms of both sampling quality and sampling efficiency across 8 public event log datasets. The experimental analysis shows that, compared with the state-of-the-art sampling methods, VariantRank improves the sampling efficiency while ensuring the sampling quality.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"37 9-11","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143818737","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":"High-Precision Indoor Visible Light Positioning Method for Line-Of-Sight Scenes Based on a Spatiotemporal Sequence Attention Mechanism","authors":"Yonghao Yu,&nbsp;Dawei Zhao,&nbsp;Yongwei Tang,&nbsp;WengTak Kuok,&nbsp;Wei Ding","doi":"10.1002/cpe.70058","DOIUrl":"https://doi.org/10.1002/cpe.70058","url":null,"abstract":"<div>\u0000 \u0000 <p>Using deep learning to improve the accuracy of indoor visible light positioning (VLP) systems has gradually become a widely used research strategy in the field. However, current deep learning-based indoor visible light localization algorithms have not been able to effectively mine the deep temporal and spatial sequence features in signals, resulting in complex network construction and low localization accuracy. To address this issue, the text proposes a deep learning framework that utilizes an attention mechanism to train a small number of randomly continuously sampled spatial received signals to predict the coordinates of the received signals and encode the spatiotemporal sequence attributes of the received signals as a feature into the data, constructed a highly reliable spatiotemporal sequence attention mechanism for indoor visible light localization method. Combined with Convolutional Neural Networks (CNN), the localization accuracy is further improved. Through simulation experiments, it has been verified that the neural network structure designed in this paper has better positioning accuracy compared to advanced algorithms, and can still achieve centimeter-level (9.886cm) average positioning error under low signal-to-noise ratio (SNR) conditions. It is proved that the method proposed in this paper is reliable in the indoor VLP system.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"37 9-11","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143818738","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":"HealthEdgeAI: GAI and XAI Based Healthcare System for Sustainable Edge AI and Cloud Computing Environments","authors":"Han Wang,&nbsp;Balaji Muthurathinam Panneer Chelvan,&nbsp;Muhammed Golec,&nbsp;Sukhpal Singh Gill,&nbsp;Steve Uhlig","doi":"10.1002/cpe.70057","DOIUrl":"https://doi.org/10.1002/cpe.70057","url":null,"abstract":"<div>\u0000 \u0000 <p>Coronary heart disease is a leading cause of mortality worldwide. Although no cure exists for this condition, appropriate treatment and timely intervention can effectively manage its symptoms and reduce the risk of complications such as heart attacks. Prior studies have mostly relied on a limited dataset from the UC Irvine Machine Learning Repository, predominantly focusing on Machine Learning (ML) models without incorporating Explainable Artificial Intelligence (XAI) or Generative Artificial Intelligence (GAI) techniques for dataset enhancement. While some research has explored cloud-based deployments, the implementation of edge AI in this domain remains largely under-explored. Therefore, this paper proposes <i>HealthEdgeAI</i>, a sustainable approach to heart disease prediction that enhances XAI through GAI-driven data augmentation. In our research, we assessed multiple AI models by evaluating accuracy, precision, recall, F1-score, and area under the curve (AUC). We also developed a web application using Streamlit to demonstrate our XAI methods and employed FastAPI to serve the optimal model as an API. Additionally, we examined the performance of these models in cloud computing and edge AI settings by comparing key Quality of Service (QoS) parameters, such as average response rate and throughput. To highlight the potential of sustainable edge AI and cloud computing, we tested edge devices with both low- and high-end configurations to illustrate differences in QoS. Ultimately, this study identifies current limitations and outlines prospective directions for future research in AI-based cloud and edge computing environments.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"37 9-11","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143809430","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":"Optimization of Anti-Tampering Method for Financial Data in Edge Intelligent Systems Based on Support Vector Machine","authors":"Shugui Lin,&nbsp;Wei Zhang,&nbsp;Ruchun Jia,&nbsp;Haitao Deng,&nbsp;Linyuan Li,&nbsp;Jianjun Zhou,&nbsp;Ze Li","doi":"10.1002/cpe.70070","DOIUrl":"https://doi.org/10.1002/cpe.70070","url":null,"abstract":"<div>\u0000 \u0000 <p>The proliferation of edge intelligent systems has introduced new challenges in securing financial data across distributed networks. This paper proposes an optimized anti-tampering method for financial data based on SVM, specifically designed for implementation in edge computing environments. Our approach leverages the strengths of SVM in handling non-linear, high-dimensional data, while addressing the unique security and privacy concerns of edge-based financial systems. We introduce a novel feature weighting mechanism that enhances the SVM's ability to detect subtle data tampering attempts in distributed financial datasets, and improve the application of SVM to better handle non-stationary, asymmetric, and non-linear time series financial data in edge computing settings. A comprehensive evaluation using real-world financial data in simulated edge computing scenarios demonstrates significant improvements in yield indicators, maximum drawdown rate, and volatility compared to traditional approaches. Our method not only effectively detects data tampering but also improves the accuracy of financial data prediction in decentralized environments. This research contributes to the development of more secure, efficient, and privacy-preserving financial systems in the increasingly decentralized global economy, paving the way for robust security solutions in edge-based financial infrastructures.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"37 9-11","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143801650","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":"SCGG: Smart City Network Topology Graph Generator","authors":"Nouf A. S. Alsowaygh,&nbsp;Mohammed J. F. Alenazi,&nbsp;Maazen Alsabaan","doi":"10.1002/cpe.70088","DOIUrl":"https://doi.org/10.1002/cpe.70088","url":null,"abstract":"<div>\u0000 \u0000 <p>Smart cities use information and communication technology to promote citizen welfare and economic growth within a sustainable environment. To guarantee that different urban actors, including people, devices, companies, and governments, can communicate efficiently, securely, and reliably, a robust, adaptable network infrastructure is required. However, the increasing complexity of the systems involved poses a challenge to smart city network modeling. Network topology generators produce synthetic networks that can reflect the underlying properties of real-world networks, providing a practical approach to designing, testing, and implementing complex systems such as smart cities, yet the limited number of network topology generators for smart city applications has long prevented the proper development, investigation, and evaluation of various network configurations. In this article, a novel Smart City Network Topology Graph Generator (SCGG) is proposed to create a pseudorandom topology that mimics real smart city networks. The main goal of SCGG is to generate a network topology for smart cities that captures the interconnectivity of several communication technologies, such as wireless sensor networks (WSN), Internet of Things (IoT), and cellular networks. The SCGG system is characterized by the number of clusters, the average number of nodes, the number of layers, and the node density. The general network architecture and path-related variables of the generated topologies are evaluated based on different graph theory measures, focusing on both global graph-level characteristics and local node-level features. The experimental results, demonstrating high natural connectivity and a low spectral radius value, offer a reliable tool for optimizing and strengthening the behavior and performance of smart city networks under different conditions to improve their robustness, minimize the probability of disruptions or failures, and enhance overall efficiency to ensure a resilient network.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"37 9-11","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143809390","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":"Detecting Network Security Bypass Threats Using Machine Learning Methods: Detecting Intruders on the Network","authors":"Seyed Ebrahim Dashti,&nbsp;Wassan Sajit Nasser Al-Jabri,&nbsp;Ali Farzanehmehr","doi":"10.1002/cpe.70062","DOIUrl":"https://doi.org/10.1002/cpe.70062","url":null,"abstract":"<div>\u0000 \u0000 <p>The problem of cybersecurity has grown in importance. Machine learning (ML) systems can detect network penetration. Imbalanced data sets have a detrimental impact on typical network intrusion detection. To be more precise, seven traditional ML algorithms were tested against two versions of a fully connected neural network, one with and one without an autoencoder. Additionally, an electing classifier is suggested as a means to integrate the outcomes of these nine ML algorithms. The majority electing classifier allows for the combination of several weak classifiers into a strong classifier. The number and type of weak classifiers used will have an impact on the final ensemble classifier's performance Three distinct resampling methods oversampling, undersampling, and hybrid sampling are used to evaluate each model. Next, we will go over the specifics of the trials and how we analyzed the data. The comparison results show that the performance of the classifiers on balanced data outperforms those on (\u0000https://www.sciencedirect.com/topics/computer-science/imbalanced-data) imbalanced data, and the electing classifier outperforms the nine algorithms. A weighted <i>F</i>1 score is a good performance metric to evaluate solutions in intrusion detection systems. Due to the importance of the <i>F</i>1 score parameter, the proposed method has reached a predict of 80%, which is a significant improvement compared to related works.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"37 9-11","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143809819","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":"An Alternative Mechanism for Multiresource Fair Allocation in Heterogeneous Cloud Computing Systems","authors":"Bin Deng,&nbsp;Hao Guo,&nbsp;Weidong Li","doi":"10.1002/cpe.70091","DOIUrl":"https://doi.org/10.1002/cpe.70091","url":null,"abstract":"<div>\u0000 \u0000 <p>Finding a fair allocation is an important issue in many application areas. In a heterogeneous cloud computing system, users may have different requirements, and servers may also have different configurations. The first proposed fair allocation mechanism for heterogeneous cloud computing systems, called DRFH, is based on dominant resource fairness. However, the DRFH mechanism does not satisfy the properties of strong shared incentives and independence of dummy servers. In this article, we propose a simple mechanism, called the maximin share-based mechanism in a heterogeneous cloud computing system (MMSH), which maximizes the minimum ratio of the user's utility to the maximin share. Because the MMSH mechanism can be formulated as a linear program, a MMSH allocation can be found in polynomial time. Moreover, we prove that MMSH satisfies all the desirable properties including Pareto efficiency, strong sharing incentives, envy-freeness, group strategy-proofness, and independence of dummy servers. Using the Alibaba trace to conduct data simulations, the experimental results indicate that in most cases, the allocation generated by the MMSH mechanism has a higher resource utilization rate.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"37 9-11","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143809389","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":"Revocable and Privacy-Preserving CP-ABE Scheme for Secure mHealth Data Access in Blockchain","authors":"Anita Thakur,&nbsp;Virender Ranga,&nbsp;Ritu Agarwal","doi":"10.1002/cpe.70064","DOIUrl":"https://doi.org/10.1002/cpe.70064","url":null,"abstract":"<div>\u0000 \u0000 <p>Innovations in technology are revolutionizing healthcare, driving a shift toward patient-centric smart healthcare systems. Mobile health (mHealth) leverages innovations in wearable sensors, telecommunications, and IoT to establish a novel healthcare model that prioritizes the patient, enabling real-time monitoring, personalized interventions, and improved access to care, ultimately fostering a proactive approach to health management and enhancing overall patient outcomes. However, safeguarding patient data transparency, security, and privacy within mHealth systems presents significant challenges, particularly concerning personal health records (PHR). Ciphertext-Policy Attribute-Based Encryption (CP-ABE) offers a competent answer to facilitating one-to-many data sharing in healthcare environments. Nevertheless, several issues must be addressed before CP-ABE can be widely deployed. These include the need for timely and effective attribute revocation when user attributes change, resistance to collusion attacks, and ensuring data integrity. This paper proposes a revocable and secure fine-grained access scheme using blockchain and CP-ABE. We compare four prominent state-of-the-art schemes through comprehensive experimentation with our proposed approach. Our results demonstrate the relative performance of our scheme, showing a significant reduction in computational costs. Specifically, the key generation cost is reduced by <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mo>≈</mo>\u0000 </mrow>\u0000 <annotation>$$ approx $$</annotation>\u0000 </semantics></math>35% to 67%, and the encryption cost is reduced by <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mo>≈</mo>\u0000 </mrow>\u0000 <annotation>$$ approx $$</annotation>\u0000 </semantics></math>26% to 39%. A detailed analysis of communication, computational, and storage overhead reveals that our suggested solution offers a distinct advantage in terms of efficiency. The Scyther tool is employed to verify the security measures and assess the accuracy of proposed methodologies, subsequently conducting experiments to showcase its efficacy.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"37 9-11","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143801888","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":"Intelligent Network Security Optimization Algorithm Based on Cnns","authors":"Meirong Zheng,&nbsp;Ruchun Jia,&nbsp;Jing Zhu,&nbsp;Shaorong Zhang,&nbsp;Wenlong Yao,&nbsp;Yuanbin Li","doi":"10.1002/cpe.70069","DOIUrl":"https://doi.org/10.1002/cpe.70069","url":null,"abstract":"<div>\u0000 \u0000 <p>To enhance the precision of security risk assessment and real-time control in edge-based intelligent networks, this article presents a novel risk assessment and control approach leveraging convolutional neural networks (CNNs). This method significantly improves on traditional intelligent network security risk assessment techniques, integrating CNN-based models to achieve higher accuracy and robustness. By incorporating genetic algorithms and proportional integral derivative control optimization, the proposed approach further ensures stability across intelligent network operations. Using the KDDCup99 network security attack database for evaluation, results demonstrate that this approach achieves a high accuracy rate and low false alarm rate. Additionally, the output signal amplitude closely aligns with the expected amplitude, showing only a 0.02 deviation, while maintaining low evaluation and control times. This ensures comprehensive security across edge intelligent systems, addressing key latency and precision requirements and achieving optimal control effects.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"37 9-11","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143801880","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}