样式: 排序: IF: - GO 导出 标记为已读
-
Ethereum Transaction Replay Platform Based on State-wise Account Input Data IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-04-17 Yuan Huang, Rong Wang, Xiangping Chen, Changlin Yang, Zibin Zheng
-
A Monitoring-Free Bitcoin Payment Channel Scheme With Support for Real-Time Settlement IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-04-17 Yankai Xie, Ruian Li, Yan Huang, Chi Zhang, Lingbo Wei, Yani Sun
-
A Deep Recurrent-Reinforcement Learning Method for Intelligent AutoScaling of Serverless Functions IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-04-12 Siddharth Agarwal, Maria A. Rodriguez, Rajkumar Buyya
-
Multi-Attribute Auction-Based Grouped Federated Learning IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-04-12 Renhao Lu, Hongwei Yang, Yan Wang, Hui He, Qiong Li, Xiaoxiong Zhong, Weizhe Zhang
-
RCME: A Reputation Incentive Committee Consensus-Based for Matchmaking Encryption in IoT Healthcare IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-04-11 Ningbin Yang, Chunming Tang, Zehui Xiong, Debiao He
-
Blockchained Dual-Asynchronous Federated Learning Services for Digital Twin Empowered Edge-Cloud Continuum IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-04-08 Youyang Qu, Shui Yu, Longxiang Gao, Keshav Sood, Yong Xiang
-
CouldPin-Fast: Effient and Effective Root Cause Localization for Shared Bandwidth Package Traffic Anomalies in Public Cloud Networks IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-04-08 Shize Zhang, Yunfeng Zhao, Jianyuan Lu, Shuai Yang, Biao Lyu, Shunmin Zhu, Enhuan Dong, Zhiliang Wang, Jiahai Yang
-
C-KHCS: Multi-Objective Workflow Scheduling using Chaotic Krill Herd Optimization and Improved Cuckoo Search in Fog Computing IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-04-01 Shahin Nazemi, Reihaneh Khorsand
-
Data-Submission Control of Web Service-Based Multi-Agent System IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-04-01 Chen Hou
-
Enabling Privacy-Preserving K-hop Reachability Query over Encrypted Graphs IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-03-28 Yunjiao Song, Xinrui Ge, Jia Yu, Rong Hao, Ming Yang
-
Privacy Preserving Based on Seamless Authentication with Provable Key Verification using mIoMT for B5G-enabled Healthcare Systems IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-03-28 B D Deebak, Seong Oun Hwang
-
Blockchain-based Efficient and Trustworthy AIGC Services in Metaverse IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-03-28 Yijing Lin, Zhipeng Gao, Hongyang Du, Dusit Niyato, Jiawen Kang, Zehui Xiong, Zibin Zheng
-
Encoder-Decoder Based Route Generation Model for Flexible Travel Recommendation IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-03-26 Jiale Zhang, Mingqian Ma, Xiaofeng Gao, Guihai Chen
-
Leader Federated Learning Optimization Using Deep Reinforcement Learning for Distributed Satellite Edge Intelligence IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-03-26 Hangyu Zhang, Hongbo Zhao, Rongke Liu, Xiangqiang Gao, Shenzhan Xu
-
Enhancing Disentanglement of Popularity Bias for Recommendation with Triplet Contrastive Learning IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-03-25 Jie Liao, Wei Zhou, Fengji Luo, Junhao Wen
-
A Joint Learning Recommendation Model for E-Commerce Platforms Integrating Long-Term and Short-Term Interests IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-03-21 Yunpeng Xiao, Wanjing Zhao, Yuyang Huang, Tun Li, Qian Li
-
Publicly Verifiable Secure Multi-Party Computation Framework Based on Bulletin Board IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-03-21 Xiaotong Li, Hao Wang, Zhi Li, Lei Wu, Xiaochao Wei, Ye Su, Rongxing Lu
-
Efficient and Privacy-Preserving Federated Learning against Poisoning Adversaries IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-03-20 Jiaqi Zhao, Hui Zhu, Fengwei Wang, Yandong Zheng, Rongxing Lu, Hui Li
-
SCOF: Security-Aware Computation Offloading Using Federated Reinforcement Learning in Industrial Internet of Things with Edge Computing IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-03-19 Kai Peng, Peiyun Xiao, Shangguang Wang, Victor C.M. Leung
-
RT3C: Real-Time Crowd Counting in Multi-Scene Video Streams via Cloud-Edge-Device Collaboration IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-03-18 Rui Wang, Yixue Hao, Yiming Miao, Long Hu, Min Chen
-
EPSet: Efficient and Privacy-Preserving Set Similarity Range Query Over Encrypted Data IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-03-18 Yandong Zheng, Rongxing Lu, Yunguo Guan, Songnian Zhang, Jun Shao, Fengwei Wang, Hui Zhu
Set similarity query is a fundamental query type in various applications, such as clinical diagnosis, online shopping, and mobile crowdsensing. Meanwhile, as the prevalence of outsourced query services, privacy-preserving set similarity query has been considerablely studied. However, to the best of our knowledge, most previously reported solutions suffer from applicability, efficiency, or security
-
Optimizing Resource Allocation for Wireless VR Services IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-03-18 Chih-Hang Wang, Yishuo Shi, De-Nian Yang, Chih-Yen Chen, Wanjiun Liao
-
PBScaler: A Bottleneck-Aware Autoscaling Framework for Microservice-Based Applications IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-03-18 Shuaiyu Xie, Jian Wang, Bing Li, Zekun Zhang, Duantengchuan Li, Patrick C. K. Hung
Autoscaling is critical for ensuring optimal performance and resource utilization in cloud applications with dynamic workloads. However, traditional autoscaling technologies are typically no longer applicable in microservice-based applications due to the diverse workload patterns and complex interactions between microservices. Specifically, the propagation of performance anomalies through interactions
-
PrivRo: A Privacy-Preserving Crowdsourcing Service with Robust Quality Awareness IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-03-18 Rui Lian, Yifeng Zheng, Cong Wang
-
Incentive Mechanism for Uncertain Tasks under Differential Privacy IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-03-18 Xikun Jiang, Chenhao Ying, Lei Li, Boris Düdder, Haiqin Wu, Haiming Jin, Yuan Luo
-
SmartChain: A Dynamic and Self-Adaptive Sharding Framework for IoT Blockchain IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-03-18 Ting Cai, Wuhui Chen, Jianting Zhang, Zibin Zheng
Sharding technologies allow the Internet of Things (IoT) to deploy blockchains in large-scale applications with good scalability. However, conventional sharding strategies in IoT blockchain are highly restricted because most IoT devices are dynamic and heterogeneous. They fail to partition and reconfigure shards with a fine-balanced tradeoff between throughput and security. Therefore, we propose SmartChain
-
Design of Anti-Plagiarism Mechanisms in Decentralized Federated Learning IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-03-18 Yumeng Shao, Jun Li, Ming Ding, Kang Wei, Chuan Ma, Long Shi, Wen Chen, Shi Jin
-
Achieving Privacy-preserving Trajectory Query in Geospatial Information Systems with Outsourced Cloud IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-03-13 Qinglei Kong, Songnian Zhang, Rongxing Lu, Haiyong Bao, Bo Chen, Shiwu Xu
-
FRLN: Federated Residual Ladder Network for Data-Protected QoS Prediction IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-03-13 Guobing Zou, Wenzhuo Yu, Shengxiang Hu, Yanglan Gan, Bofeng Zhang, Yixin Chen
-
Boosting Dynamic Decentralized Federated Learning by Diversifying Model Sources IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-03-13 Dongyuan Su, Yipeng Zhou, Laizhong Cui, Song Guo
-
Incentive-Aware Resource Allocation for Multiple Model Owners in Federated Learning IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-03-12 Feng-Yang Chen, Li-Hsing Yen
A user (model owner) in federated learning builds a learning model by aggregating local learning models trained by independent workers with their private datasets. A fundamental issue of federating learning is allocating resource from workers to the training task. As the allocation causes extra costs and overheads, workers are inherently reluctant to participate. Therefore, it is crucial to design
-
Attribute-hiding fuzzy encryption for privacy-preserving data evaluation IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-03-12 Zhenhua Chen, Luqi Huang, Guomin Yang, Willy Susilo, Xingbing Fu, Xingxing Jia
-
DPFLA: Defending Private Federated Learning Against Poisoning Attacks IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-03-12 Xia Feng, Wenhao Cheng, Chunjie Cao, Liangmin Wang, Victor S. Sheng
-
Fission Spectral Clustering Strategy for UAV Swarm Networks IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-03-12 Gepeng Zhu, Haipeng Yao, Tianle Mai, Zunliang Wang, Di Wu, Song Guo
The flying ad hoc networks (FANETs) have attracted a large amount of attention from both academia and industry. Benefiting from the flexibility, the FANETs have been widely deployed in various scenarios, ranging from agricultural production to emergency rescue. However, in FANETs, the mobility of unmanned aerial vehicles (UAVs) has led to critical challenges for the stability of communications. Especially
-
E2MS: An Efficient and Economical Microservice Migration Strategy for Smart Manufacturing IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-03-12 Yuxiang Liu, Bo Yang, Xiaoyuan Ren, Qi Liu, Sicheng Liu, Xinping Guan
-
Dynamic Task Offloading and Resource Allocation for NOMA-aided Mobile Edge Computing: An Energy Efficient Design IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-03-12 Ying Chen, Jiajie Xu, Yuan Wu, Jie Gao, Lian Zhao
-
POP-FL: Towards Efficient Federated Learning on Edge Using Parallel Over-Parameterization IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-03-12 Xingjian Lu, Haikun Zheng, Wenyan Liu, Yuhui Jiang, Hongyue Wu
Federated Learning (FL) is a promising paradigm for mining massive data while respecting users’ privacy. However, the deployment of FL on resource-constrained edge devices remains elusive due to its high resource demand. In this paper, unlike existing works that use expensive dense models, we propose to utilize dynamic sparse training in FL and design a novel sparse-to-sparse FL framework, named as
-
StraAlgin: automated strategic alignment of services IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-03-12 Ahmed Saeed Alsayed, Hoa Khanh Dam, Aditya Ghose, Chau Nguyen
-
Server-Initiated Federated Unlearning to Eliminate Impacts of Low-Quality Data IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-02-20 Pengfei Wang, Wei Song, Heng Qi, Changjun Zhou, Fuliang Li, Yong Wang, Peng Sun, Qiang Zhang
-
Recommendation-Enabled Edge Caching and D2D Offloading Via Incentive-Driven Deep Reinforcement Learning IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-02-19 Tong Wu, Dongjin Yu, Chengfei Liu, Dongjing Wang, Binbin Huang
-
Web Service Composition in Mobile Environment: A Survey of Techniques IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-02-05 Cheyma Ben Njima, Chirine Ghedira Guegan, Youssef Gamha, Lotfi Ben Romdhane
Today, with the exponential rise in the use of the internet, the trend of the massive use of mobile devices (tablets, laptops, computers, iPads etc...) the user has become inseparable from his smartphone, which facilitates the use of several services in different fields (work, research, commerce, etc.). Besides, with the proliferation of data, the needs of consumers are becoming increasingly complex
-
Autoscaling Solutions for Cloud Applications under Dynamic Workloads IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-02-05 Giovanni Quattrocchi, Emilio Incerto, Riccardo Pinciroli, Catia Trubiani, Luciano Baresi
-
Stable Matching based Revenue Maximization for Federated Learning in UAV-Assisted WBANs IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-01-31 Moirangthem Biken Singh, Himanshu Singh, Ajay Pratap
-
Battery-Aware Energy Optimization for Satellite Edge Computing IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-01-29 Qing Li, Shangguang Wang, Xiao Ma, Ao Zhou, Yue Wang, Gang Huang, Xuanzhe Liu
Satellite edge computing can incur dramatically increased energy demand onboard, which is met by satellite batteries during eclipses. Excessive energy usage during regular operations accelerates battery wear. Therefore, it is important and timely to optimize the energy consumption onboard to extend satellite batteries life. This article investigates battery-aware energy optimization for satellite edge
-
Paramart: Parallel Resource Allocation Based on Blockchain Sharding for Edge-Cloud Services IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-01-29 Xiaoxu Ren, Minrui Xu, Dusit Niyato, Jiawen Kang, Chao Qiu, Xiaofei Wang
-
Incentive-Aware Partitioning and Offloading Scheme for Inference Services in Edge Computing IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-01-26 TaeYoung Kim, Chang Kyung Kim, Seung-seob Lee, SuKyoung Lee
-
DMPSI: Efficient Scalable Delegated Multiparty PSI and PSI-CA With Oblivious PRF IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-01-26 Yihao Yang, Yunbo Yang, Xiang Chen, Xiaolei Dong, Zhenfu Cao, Jiachen Shen
Multiparty private set intersection (PSI) allows several parties, each holding a set of elements, to jointly compute the intersection without leaking any additional information. With the development of cloud computing, delegating the computation to an untrsuted cloud server is becoming a major problem, where the untrusted cloud server may try to get some sensitive information from clients’ private
-
SecDM: A Secure and Lossless Human Mobility Prediction System IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-01-25 Lin Liu, Shaojing Fu, Xuelun Huang, Yuchuan Luo, Xuyun Zhang, Kim-Kwang Raymond Choo
-
QoS Aware Virtual Network Embedding in Space-Air-Ground-Ocean Integrated Network IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-01-24 Yi Zhang, Peiying Zhang, Chunxiao Jiang, Shangguang Wang, Hongxia Zhang, Chunming Rong
-
A Secure Image Outsourcing Using Privacy-Preserved Local Color Layout Descriptor in Cloud Environment IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-01-23 Anju J., Shreelekshmi R.
Secure storage and content-based retrieval of images on third-party servers without compromising privacy and efficiency is a challenging research problem. In this article, we propose novel encryption and indexing schemes for secure storage of sensitive images on the cloud server and secure retrieval of the images by authorized image users. The proposed image encryption preserves the Local Color Layout
-
Accelerating Tip Selection in Burst Message Arrivals for DAG-Based Blockchain Systems IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-01-23 Xun Xiao
Blockchain systems (e.g., IOTA) use Directed Acyclic Graph (DAG) topology to organize its ledger records. A new message is added by attaching to the tips selected from the DAG. For tip selection, a stochastic approach is widely used, where a random walk is simulated until it ends at a tip of the DAG. Prior art intensively focused on the fairness and security issues of this random walk approach. However
-
DCIRM: Dynamic and Controllable Image Retrieval Scheme in Multi-owner Multi-user Settings IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-01-22 Chenyang Mao, Zhonghua Shen, Kefei Chen, Yong Liu, Qian Meng, Fuqun Wang
-
A Privacy-Preserving and Redactable Healthcare Blockchain System IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-01-22 Shengmin Xu, Jianting Ning, Xiaoguo Li, Jiaming Yuan, Xinyi Huang, Robert H. Deng
Blockchain as an open and immutable ledger is being posited as the next frontier in healthcare that will help solve the industry's interoperability challenges. However, immutability in processing personal data is no longer legal since the General Data Protection Regulation (GDPR) requires the “right to be forgotten” as a critical data subject right. To observe such data regulation, it is desirable
-
LSE: Efficient Symmetric Searchable Encryption Based on Labeled PSI IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-01-22 Yunbo Yang, Yiwei Hu, Ruofan Li, Xiaolei Dong, Zhenfu Cao, Jiachen Shen, Shangmin Dou
Searchable encryption (SE) allows a data owner to outsource encrypted documents to an untrusted cloud server while preserving privacy and achieving secure data sharing. However, most existing SE schemes have a trade-off between security and efficiency. Moreover, these SE schemes leak the server's partial database or search information to perform better. Recent attacks show that such leakages can be
-
Hierarchical Deep Reinforcement Learning for Joint Service Caching and Computation Offloading in Mobile Edge-Cloud Computing IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-01-19 Chuan Sun, Xiuhua Li, Chenyang Wang, Qiang He, Xiaofei Wang, Victor C. M. Leung
-
Maximum Entropy Policy for Long-Term Fairness in Interactive Recommender Systems IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-01-18 Xiaoyu Shi, Quanliang Liu, Hong Xie, Yanan Bai, Mingsheng Shang
-
CSTL: Compositional Signal Temporal Logic for Adaptive Edge Service Monitoring IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-01-17 Deng Zhao, Zhangbing Zhou, Wenbo Zhang, Shuiguang Deng, Xiao Xue, Walid Gaaloul
Edge service monitoring is essential to guarantee the healthy of service compositions at runtime. Current techniques focus mostly on the monitoring of atomic edge services, but they are inadequate for that of inter- and composite services. Besides, constraints to be monitored are usually pre-specified, although certain parameters may have to be adapted online according to the execution context. To
-
Cromlech: Semi-Automated Monolith Decomposition Into Microservices IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-01-16 Giovanni Quattrocchi, Davide Cocco, Simone Staffa, Alessandro Margara, Gianpaolo Cugola
Microservices architectures conceive an application as a composition of loosely-coupled sub-systems that are developed, deployed, maintained, updated, and scaled independently. Compared to monoliths, microservices speed up evolution and increase flexibility. For these reasons they are becoming the reference architecture for many practitioners. A key challenge to embrace a microservices architecture
-
Scaling Power Management in Cloud Data Centers: A Multi-Level Continuous-Time MDP Approach IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-01-16 Behzad Chitsaz, Ahmad Khonsari, Masoumeh Moradian, Aresh Dadlani, Mohammad Sadegh Talebi
-
Oasis: Online All-Phase Quality-Aware Incentive Mechanism for MCS IEEE Trans. Serv. Comput. (IF 8.1) Pub Date : 2024-01-16 Man Zhang, Xinghua Li, Yinbin Miao, Bin Luo, Siqi Ma, Kim-Kwang Raymond Choo, Robert H. Deng
To motivate users to submit high quality data for mobile crowdsensing (MCS), some quality-aware incentive mechanisms have been proposed, which recruit and pay users strategically. However, in the existing mechanisms, the recruitment based only on tasks matching degree leads to the ineffective insistent data quality incentive. Meanwhile, the absence of the reasonable payment strategy cannot motivate