IEEE Transactions on Services Computing最新文献

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Generalizable Pareto-Optimal Offloading with Reinforcement Learning in Mobile Edge Computing 移动边缘计算中基于强化学习的广义pareto最优卸载
IF 8.1 2区 计算机科学
IEEE Transactions on Services Computing Pub Date : 2025-08-29 DOI: 10.1109/tsc.2025.3604371
Ning Yang, Junrui Wen, Meng Zhang, Ming Tang
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引用次数: 0
Towards a Trust Ecosystem for Crowdsourcing IoT Services: A Macro Perspective 面向众包物联网服务的信任生态系统:宏观视角
IF 5.8 2区 计算机科学
IEEE Transactions on Services Computing Pub Date : 2025-08-29 DOI: 10.1109/TSC.2025.3604379
Dianjie Lu;Guijuan Zhang;Yu Guo;Xiaohua Jia
{"title":"Towards a Trust Ecosystem for Crowdsourcing IoT Services: A Macro Perspective","authors":"Dianjie Lu;Guijuan Zhang;Yu Guo;Xiaohua Jia","doi":"10.1109/TSC.2025.3604379","DOIUrl":"10.1109/TSC.2025.3604379","url":null,"abstract":"Trust plays a crucial role in crowdsourcing Internet of Things (IoT), as it can be used to select trustworthy participants to improve the quality of crowdsourced services and strengthen system security. While traditional research has focused on micro-level aspects, including trust computation and propagation, a comprehensive macro-level trust analysis remains underexplored. In this paper, we propose a macroscopic trust ecosystem analysis framework for crowdsourcing IoT services. We first construct a Trust Ecosystem Model (TEM), where trust clusters serve as an abstraction to capture and quantify overall trust characteristics based on their size and structure. To analyze the dynamic evolution of TEM, we propose a Percolation-based Trust Ecosystem Analysis Model (P-TEAM), which maps the formation of trust clusters to a joint site-bond percolation process. Thus, the study of TEM evolution can be reframed into an investigation of how trust clusters evolve as users’ trust attributes change. Through P-TEAM, we identify the critical thresholds associated with trust attributes that trigger trust phase transitions in crowdsourcing IoT services, which act as key metrics for evaluating the ecosystem’s robustness macroscopically. Finally, we further evaluate the trust ecosystem beyond these thresholds by calculating the proportions of trusted giant components. We validate our approach on directed networks, using both synthetic and real-world datasets. The experimental results further substantiate our findings and provide valuable insights into constructing a healthy and sustainable trust ecosystem for crowdsourcing IoT services.","PeriodicalId":13255,"journal":{"name":"IEEE Transactions on Services Computing","volume":"18 5","pages":"3292-3306"},"PeriodicalIF":5.8,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144919271","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
AttResRec: Learning User Credibility for Attack Resistant Matrix Factorization Recommendation 学习用户可信度的抗攻击矩阵分解推荐
IF 8.1 2区 计算机科学
IEEE Transactions on Services Computing Pub Date : 2025-08-29 DOI: 10.1109/tsc.2025.3604375
Jiangpeng Zhao, Wen Zhang, Song Wang, Quan Bai, Kuien Liu
{"title":"AttResRec: Learning User Credibility for Attack Resistant Matrix Factorization Recommendation","authors":"Jiangpeng Zhao, Wen Zhang, Song Wang, Quan Bai, Kuien Liu","doi":"10.1109/tsc.2025.3604375","DOIUrl":"https://doi.org/10.1109/tsc.2025.3604375","url":null,"abstract":"","PeriodicalId":13255,"journal":{"name":"IEEE Transactions on Services Computing","volume":"52 1","pages":""},"PeriodicalIF":8.1,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144919268","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
Trident: A Provider-Oriented Resource Management Framework for Serverless Computing Platforms Trident:面向提供者的无服务器计算平台资源管理框架
IF 5.8 2区 计算机科学
IEEE Transactions on Services Computing Pub Date : 2025-08-28 DOI: 10.1109/TSC.2025.3603867
Botao Zhu;Yifei Zhu;Chen Chen;Linghe Kong
{"title":"Trident: A Provider-Oriented Resource Management Framework for Serverless Computing Platforms","authors":"Botao Zhu;Yifei Zhu;Chen Chen;Linghe Kong","doi":"10.1109/TSC.2025.3603867","DOIUrl":"10.1109/TSC.2025.3603867","url":null,"abstract":"Serverless computing has become increasingly popular due to its flexible and hassle-free service, relieving users from traditional resource management burdens. However, the shift in responsibility has led to unprecedented challenges for serverless providers in managing virtual machines (VMs) and serving heterogeneous function instances. Serverless providers need to purchase, provision and manage VM instances from IaaS providers, aiming to minimize VM provisioning costs while ensuring compliance with Service Level Objectives (SLOs). In this paper, we propose Trident, a provider-oriented resource management framework for serverless computing platforms. Trident optimizes three major serverless computing provisioning problems for serverless providers: workload prediction, VM provisioning, and function placement. Specifically, Trident introduces a novel dynamic model selection algorithm for more accurate workload prediction. With the prediction results, Trident then carefully designs a hierarchical reinforcement learning (HRL)-based approach for VM provisioning with a mix of types and configurations. To further improve resource utilization, Trident employs an effective collocation placement strategy for efficient function container scheduling. Evaluations on the Azure Function dataset demonstrate that Trident maintains the lowest probability of violating SLOs while simultaneously achieving substantial cost savings of up to 71.8% in provisioning expense compared to state-of-the-art methods from industry and academia.","PeriodicalId":13255,"journal":{"name":"IEEE Transactions on Services Computing","volume":"18 5","pages":"3334-3347"},"PeriodicalIF":5.8,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144915645","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
Serving LLM in Distributed GPU Cluster with Fine-Grain Pipeline Constraints 基于细粒度管道约束的分布式GPU集群LLM服务
IF 8.1 2区 计算机科学
IEEE Transactions on Services Computing Pub Date : 2025-08-28 DOI: 10.1109/tsc.2025.3603576
Yanying Lin, Shijie Peng, Shuaipeng Wu, Yanbo Li, Chengzhi Lu, Kejiang Ye, Chengzhong Xu
{"title":"Serving LLM in Distributed GPU Cluster with Fine-Grain Pipeline Constraints","authors":"Yanying Lin, Shijie Peng, Shuaipeng Wu, Yanbo Li, Chengzhi Lu, Kejiang Ye, Chengzhong Xu","doi":"10.1109/tsc.2025.3603576","DOIUrl":"https://doi.org/10.1109/tsc.2025.3603576","url":null,"abstract":"","PeriodicalId":13255,"journal":{"name":"IEEE Transactions on Services Computing","volume":"23 1","pages":""},"PeriodicalIF":8.1,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144915644","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 Game-Theoretic Approach for Microservice Request Dispatching in Mobile Edge Computing Systems 移动边缘计算系统微服务请求调度的博弈论方法
IF 8.1 2区 计算机科学
IEEE Transactions on Services Computing Pub Date : 2025-08-26 DOI: 10.1109/tsc.2025.3602905
Hongyue Wu, Bowen Shi, Qiang He, Guangming Cui, Shizhan Chen, Zhiyong Feng, Albert Y. Zomaya, Shuiguang Deng
{"title":"A Game-Theoretic Approach for Microservice Request Dispatching in Mobile Edge Computing Systems","authors":"Hongyue Wu, Bowen Shi, Qiang He, Guangming Cui, Shizhan Chen, Zhiyong Feng, Albert Y. Zomaya, Shuiguang Deng","doi":"10.1109/tsc.2025.3602905","DOIUrl":"https://doi.org/10.1109/tsc.2025.3602905","url":null,"abstract":"","PeriodicalId":13255,"journal":{"name":"IEEE Transactions on Services Computing","volume":"55 1","pages":""},"PeriodicalIF":8.1,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144905923","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
Secure and Privacy Preserving Scalable GDPR Enforcement System 安全和隐私保护可扩展的GDPR执行系统
IF 8.1 2区 计算机科学
IEEE Transactions on Services Computing Pub Date : 2025-08-26 DOI: 10.1109/tsc.2025.3603041
Mou Dutta, Subhasish Dhal, Hema Gohain
{"title":"Secure and Privacy Preserving Scalable GDPR Enforcement System","authors":"Mou Dutta, Subhasish Dhal, Hema Gohain","doi":"10.1109/tsc.2025.3603041","DOIUrl":"https://doi.org/10.1109/tsc.2025.3603041","url":null,"abstract":"","PeriodicalId":13255,"journal":{"name":"IEEE Transactions on Services Computing","volume":"32 1","pages":""},"PeriodicalIF":8.1,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144905924","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
Comment on “RCME: A Reputation Incentive Committee Consensus-Based for Matchmaking Encryption in IoT Healthcare” 评论“RCME:基于声誉激励委员会共识的物联网医疗撮合加密”
IF 5.8 2区 计算机科学
IEEE Transactions on Services Computing Pub Date : 2025-08-25 DOI: 10.1109/TSC.2025.3601977
Jiseung Kim;Hyung Tae Lee
{"title":"Comment on “RCME: A Reputation Incentive Committee Consensus-Based for Matchmaking Encryption in IoT Healthcare”","authors":"Jiseung Kim;Hyung Tae Lee","doi":"10.1109/TSC.2025.3601977","DOIUrl":"10.1109/TSC.2025.3601977","url":null,"abstract":"Recently, Yang et al. proposed a reputation incentive committee consensus-based matchmaking scheme (IEEE Transactions on Services Computing, 2024), claiming to achieve indistinguishability under adaptive chosen ciphertext attacks (IND-CCA2). In this work, we present a plaintext recovery attack against their scheme under the adaptive chosen ciphertext attack model, analyze the design and proof flaws enabling the attacks, and suggest a countermeasure to achieve the IND-CCA2 security.","PeriodicalId":13255,"journal":{"name":"IEEE Transactions on Services Computing","volume":"18 5","pages":"3362-3363"},"PeriodicalIF":5.8,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144900518","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 Reciprocal Dual-channel Preference Extraction and Refinement Network for Category-aware Service Recommendation 一种新的双向双通道偏好提取和优化网络用于类别感知服务推荐
IF 8.1 2区 计算机科学
IEEE Transactions on Services Computing Pub Date : 2025-08-21 DOI: 10.1109/tsc.2025.3601040
Shuxiang Xu, Qibu Xiang, Yushun Fan, Jia Zhang
{"title":"A Novel Reciprocal Dual-channel Preference Extraction and Refinement Network for Category-aware Service Recommendation","authors":"Shuxiang Xu, Qibu Xiang, Yushun Fan, Jia Zhang","doi":"10.1109/tsc.2025.3601040","DOIUrl":"https://doi.org/10.1109/tsc.2025.3601040","url":null,"abstract":"","PeriodicalId":13255,"journal":{"name":"IEEE Transactions on Services Computing","volume":"46 1","pages":"1-14"},"PeriodicalIF":8.1,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144900522","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
Understanding AWS Provider Dependencies Updates in Infrastructure-as-Code: Empirical Study, Taxonomy, and Insights 了解基础设施即代码中的AWS提供商依赖关系更新:实证研究、分类和见解
IF 8.1 2区 计算机科学
IEEE Transactions on Services Computing Pub Date : 2025-08-20 DOI: 10.1109/tsc.2025.3601051
Mahi Begoug, Ali Ouni, Jasem Khelifi
{"title":"Understanding AWS Provider Dependencies Updates in Infrastructure-as-Code: Empirical Study, Taxonomy, and Insights","authors":"Mahi Begoug, Ali Ouni, Jasem Khelifi","doi":"10.1109/tsc.2025.3601051","DOIUrl":"https://doi.org/10.1109/tsc.2025.3601051","url":null,"abstract":"","PeriodicalId":13255,"journal":{"name":"IEEE Transactions on Services Computing","volume":"23 1","pages":"1-17"},"PeriodicalIF":8.1,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144900525","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
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