IEEE Transactions on Mobile Computing最新文献

Corrections to “Learning Domain-Invariant Model for WiFi-Based Indoor Localization” 对“基于wifi的室内定位学习域不变模型”的修正

IF 7.7 2区计算机科学

IEEE Transactions on Mobile Computing Pub Date : 2025-06-05 DOI: 10.1109/TMC.2025.3539443

Guanzhong Wang;Dongheng Zhang;Tianyu Zhang;Shuai Yang;Qibin Sun;Yan Chen

引用次数: 0

Correction to “CV-Cast: Computer Vision–Oriented Linear Coding and Transmission” 更正“CV-Cast：计算机视觉导向的线性编码和传输”

IF 7.7 2区计算机科学

IEEE Transactions on Mobile Computing Pub Date : 2025-06-05 DOI: 10.1109/TMC.2025.3565860

Jakub Žádník;Michel Kieffer;Anthony Trioux;Markku Mäkitalo;Pekka Jääskeläinen

引用次数: 0

Differential Private Data Stream Analytics in the Local and Shuffle Models 本地和Shuffle模型中的差异私有数据流分析

IF 7.7 2区计算机科学

IEEE Transactions on Mobile Computing Pub Date : 2025-04-15 DOI: 10.1109/TMC.2025.3559621

Shaowei Wang;Jin Li;Yun Peng;Kongyang Chen;Wei Yang;Hui Jiang;Jin Li

{"title":"Differential Private Data Stream Analytics in the Local and Shuffle Models","authors":"Shaowei Wang;Jin Li;Yun Peng;Kongyang Chen;Wei Yang;Hui Jiang;Jin Li","doi":"10.1109/TMC.2025.3559621","DOIUrl":"https://doi.org/10.1109/TMC.2025.3559621","url":null,"abstract":"We study online data analytics with differential privacy (DP) in decentralized settings. Specifically, online data analytics with local DP protection is widely adopted in real-world applications. Despite numerous endeavors in this field, significant gaps in utility and functionality remain when compared to its offline counterpart. We present an optimal, streamable mechanism: <monospace>ExSub</monospace>, for local DP sparse vector estimation. The mechanism enables a range of online analytics on streaming binary vectors, including multi-dimensional binary, categorical, or set-valued data. By leveraging the negative correlation of occurrence events in the sparse vector, we attain an optimal error rate under local privacy constraints, only requiring streamable computations. To surpass the error barrier of local privacy, we also study <monospace>ExSub</monospace> randomizer in the newly emerging (single-message) shuffle model of DP, and provide nearly-tight privacy amplification bounds therein. Additionally, we leverage the online shuffle model that independently permutes users’ messages at each timestamp, to design a simplified randomization strategy that can approximately reach Gaussian accuracy in central DP. Through experiments with both synthetic and real-world datasets, <monospace>ExSub</monospace> mechanism in the local model have been shown to reduce error by 40%–60% compared to SOTA approaches. The <monospace>ExSub</monospace> in the shuffle model can further reduce over 85% error, and the online shuffle protocol reduces over 99.7% error.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"24 7","pages":"6701-6717"},"PeriodicalIF":7.7,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144219585","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

CHAR: Composite Head-Body Activities Recognition With a Single Earable Device CHAR：复合头身活动识别与一个单一的可穿戴设备

IF 7.7 2区计算机科学

IEEE Transactions on Mobile Computing Pub Date : 2025-03-06 DOI: 10.1109/TMC.2025.3548647

Peizhao Zhu;Yuzheng Zhu;Wenyuan Li;Yanbo He;Yongpan Zou;Kaishun Wu;Victor C. M. Leung

{"title":"CHAR: Composite Head-Body Activities Recognition With a Single Earable Device","authors":"Peizhao Zhu;Yuzheng Zhu;Wenyuan Li;Yanbo He;Yongpan Zou;Kaishun Wu;Victor C. M. Leung","doi":"10.1109/TMC.2025.3548647","DOIUrl":"https://doi.org/10.1109/TMC.2025.3548647","url":null,"abstract":"The increasing popularity of earable devices stimulates great academic interest to design novel head gesture-based interaction technologies. But existing works simply consider it as a singular activity recognition problem. This is not in line with practice since users may have different body movements such as walking and jogging along with head gestures. It is also beneficial to recognize body movements during human-device interaction since it provides useful context information. As a result, it is significant to recognize such composite activities in which actions of different body parts happen simultaneously. In this paper, we propose a system called CHAR to recognize composite head-body activities with a single IMU sensor. The key idea of our solution is to make use of the inter-correlation of different activities and design a multi-task learning network to extract shared and specific representations. We implement a real-time prototype and conduct extensive experiments to evaluate it. The results show that CHAR can recognize 60 kinds of composite activities (12 head gestures and 5 body movements) with high accuracies of 89.7% and 85.1% in sufficient data and insufficient data cases, respectively.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"24 7","pages":"6532-6549"},"PeriodicalIF":7.7,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144219762","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

Device Power Saving With Time-Frequency Adaptation: Joint BWP-DRX Design With BWP Switching Delay Considered 具有时频自适应的器件节能：考虑BWP切换延迟的BWP- drx联合设计

IF 7.7 2区计算机科学

IEEE Transactions on Mobile Computing Pub Date : 2025-03-04 DOI: 10.1109/TMC.2025.3547978

Cheng-Wei Tsai;Kuang-Hsun Lin;Hung-Yu Wei

{"title":"Device Power Saving With Time-Frequency Adaptation: Joint BWP-DRX Design With BWP Switching Delay Considered","authors":"Cheng-Wei Tsai;Kuang-Hsun Lin;Hung-Yu Wei","doi":"10.1109/TMC.2025.3547978","DOIUrl":"https://doi.org/10.1109/TMC.2025.3547978","url":null,"abstract":"In today's ever-growing data traffic landscape, optimizing network power efficiency and performance has become crucial. Discontinuous Reception (DRX) and Bandwidth Parts (BWP) are two key technologies that fulfill this pursuit. DRX is a time-domain power-saving technology that allows user equipment (UE) to switch off their radio frequency module. BWP switching is a frequency domain operation that allows UE to operate on only partial bandwidth for power saving. Investigating the interaction and trade-off between DRX and BWP is a must to optimize network efficiency and enhance network performance. This work proposed a novel BWP-DRX joint mechanism and its analytical model that leverages the concept of “Detect time” with the consideration of BWP switching delay. The model reduces packet loss rate by 50%, packet delay by 36% and increases the energy efficiency rate by 50% when arrival rate is high with the trade-off of 12% power efficiency reduction when arrival rate is low compared to the model without Detect time. The influence of each parameter is further analyzed to reach the best network efficiency under different traffic conditions.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"24 7","pages":"6613-6627"},"PeriodicalIF":7.7,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144219695","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

Incremental Least-Recently-Used Algorithm: Good, Robust, and Predictable Performance 增量最小最近使用算法：良好、鲁棒和可预测的性能

IF 7.7 2区计算机科学

IEEE Transactions on Mobile Computing Pub Date : 2025-03-03 DOI: 10.1109/TMC.2025.3547066

Jinbei Zhang;Chunpeng Chen;Kechao Cai;John C. S. Lui

{"title":"Incremental Least-Recently-Used Algorithm: Good, Robust, and Predictable Performance","authors":"Jinbei Zhang;Chunpeng Chen;Kechao Cai;John C. S. Lui","doi":"10.1109/TMC.2025.3547066","DOIUrl":"https://doi.org/10.1109/TMC.2025.3547066","url":null,"abstract":"This paper proposes a replacement algorithm for file caching in mobile edge computing (MEC) networks. While there are numerous schemes for file replacement, it remains a challenge to achieve good, robust, and predictable performance simultaneously. To address this challenge, we introduce a general scheme called Incremental Least-Recently-Used (iLRU), which builds on the classic Least-Recently-Used (LRU) algorithm. iLRU initially caches only a “portion” of the file upon the first request and incrementally caches more when there are more requests for the file. In this regard, the request frequency can be inferred from the cached size without incurring additional overhead, where a larger cached size represents a higher request frequency. We derive the theoretical hit ratio of iLRU based on the Time-to-Live (TTL) analysis. With the Time-to-Live (TTL) analysis, we can theoretically derive the hit ratio and properties of iLRU and notably show that iLRU allocates more cache space to popular files, resulting in a higher hit ratio than LRU. Simulation results demonstrate the superior performance of iLRU and validate the accuracy of the theoretical hit ratio. Furthermore, we conduct simulations over various real-world traces to show that iLRU outperforms existing schemes across various real-world traces, defenestrating the robustness of iLRU.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"24 7","pages":"6658-6672"},"PeriodicalIF":7.7,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144219698","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

GIRP: Energy-Efficient QoS-Oriented Microservice Resource Provisioning via Multi-Objective Multi-Task Reinforcement Learning 基于多目标多任务强化学习的节能面向qos的微服务资源配置

IF 7.7 2区计算机科学

IEEE Transactions on Mobile Computing Pub Date : 2025-03-03 DOI: 10.1109/TMC.2025.3547339

Honggang Yuan;Ting Wang;Min Fu;Yuanming Shi

{"title":"GIRP: Energy-Efficient QoS-Oriented Microservice Resource Provisioning via Multi-Objective Multi-Task Reinforcement Learning","authors":"Honggang Yuan;Ting Wang;Min Fu;Yuanming Shi","doi":"10.1109/TMC.2025.3547339","DOIUrl":"https://doi.org/10.1109/TMC.2025.3547339","url":null,"abstract":"Microservice architecture has revolutionized web service development by facilitating loosely coupled and independently developable components distributed as containers or virtual machines. While existing studies emphasize end-to-end latency, this paper investigates energy-efficient quality-of-service (QoS)-oriented microservice provisioning, focusing on both QoS satisfaction and power consumption (PC) conservation. We propose the Green and Intelligent Resource Provision (GIRP) architecture, integrating a data-driven energy-latency-aware resource allocation and scheduling manager to balance latency and PC. To reconcile the trade-offs involved, a dual-objective optimization problem is formulated to minimize latency and energy use by selecting proper servers, allocating CPU cores, and determining service replicas. To address challenges with discrete variables, dual objectives, and implicit mappings, we leverage a model-free deep deterministic policy gradient-based reinforcement learning algorithm. Specifically, we develop a multi-task agent via the Multi-gate Mixture-of-Experts model to simultaneously make two separate actions regarding CPU core numbers and service replica numbers, followed by a single-task agent to determine service scheduling. Extensive experiments on the DeathStarBenchmark testbed validate GIRP’s effectiveness, demonstrating approximately 52% resource savings and a 43% reduction in PC compared to leading methods like Sinan, Firm, and heuristic-based algorithms. These results highlight GIRP’s capability to optimize microservice orchestration by balancing end-to-end latency and power efficiency.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"24 7","pages":"5793-5807"},"PeriodicalIF":7.7,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144255483","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

Partial Offloading Strategy Based on Deep Reinforcement Learning in the Internet of Vehicles 基于深度强化学习的车联网部分卸载策略

IF 7.7 2区计算机科学

IEEE Transactions on Mobile Computing Pub Date : 2025-02-25 DOI: 10.1109/TMC.2025.3543976

Shujuan Tian;Xinjie Zhu;Bochao Feng;Zhirun Zheng;Haolin Liu;Zhetao Li

{"title":"Partial Offloading Strategy Based on Deep Reinforcement Learning in the Internet of Vehicles","authors":"Shujuan Tian;Xinjie Zhu;Bochao Feng;Zhirun Zheng;Haolin Liu;Zhetao Li","doi":"10.1109/TMC.2025.3543976","DOIUrl":"https://doi.org/10.1109/TMC.2025.3543976","url":null,"abstract":"Driven by the increasing demands of vehicular tasks, edge offloading has emerged as a promising paradigm to enhance quality of experience (QoE) in Internet of Vehicles (IoV) networks. This approach enables vehicles to offload computation-intensive tasks to edge servers, resulting in reduced computation delays and lower energy consumption. However, traditional binary offloading limits the efficiency of edge offloading. To address this gap, we propose a partial offloading strategy that jointly optimizes the offloading ratio, computation, and communication resources in IoV. Recognizing the varying priorities of vehicular tasks regarding task delay and energy consumption, we formulate two distinct scenarios: one focused on minimizing delay and the other on minimizing energy consumption. Furthermore, we employ a reinforcement learning approach to establish a multi-dimensional joint optimization function by setting different objectives for each scenario. Based on this framework, we introduce a multi-state iteration deep deterministic policy gradient algorithm (SIDDPG), which effectively determines task partitioning and resource allocation. Simulation results demonstrate that the proposed algorithm outperforms benchmark schemes in terms of task delay and energy consumption.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"24 7","pages":"6517-6531"},"PeriodicalIF":7.7,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144219690","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

Toward Optimal Broadcast Mode in Offline Finding Network 离线查找网络中最优广播模式研究

IF 7.7 2区计算机科学

IEEE Transactions on Mobile Computing Pub Date : 2025-02-25 DOI: 10.1109/TMC.2025.3545561

Tong Li;Yukuan Ding;Jiaxin Liang;Kai Zheng;Xu Zhang;Tian Pan;Dan Wang;Ke Xu

引用次数: 0

Joint Design of Power Allocation and Beamforming for IRS-Assisted Millimeter-Wave Communication System With Imperfect CSI 不完全CSI下红外辅助毫米波通信系统的功率分配与波束形成联合设计

IF 7.7 2区计算机科学

IEEE Transactions on Mobile Computing Pub Date : 2025-02-25 DOI: 10.1109/TMC.2025.3545413

Xiangbin Yu;Chenghong Yang;Jiawei Bai;Kezhi Wang;Yun Rui;Xiaoyu Dang

{"title":"Joint Design of Power Allocation and Beamforming for IRS-Assisted Millimeter-Wave Communication System With Imperfect CSI","authors":"Xiangbin Yu;Chenghong Yang;Jiawei Bai;Kezhi Wang;Yun Rui;Xiaoyu Dang","doi":"10.1109/TMC.2025.3545413","DOIUrl":"https://doi.org/10.1109/TMC.2025.3545413","url":null,"abstract":"In this paper, the joint power allocation (PA), passive beamforming (BF) and hybrid BF (HBF) including digital and analogue BFs are designed for an intelligent reflecting surface (IRS)-assisted millimeter-Wave (mmWave) communication system with imperfect channel state information (CSI) and multiple mobile users to optimize the weighted sum rate (WSR) and energy efficiency (EE). The achievable WSR and EE of the IRS-mmWave system are first derived based on imperfect cascaded CSI for performance optimization. Then, the non-convex constrained problem is formulated to maximize the WSR, where the PA, HBF, phase and amplitude of IRS elements are jointly optimized. Given PA and passive BF (PBF), closed-form suboptimal HBF is obtained for each iteration. Also, given HBF and PBF, using the block coordinate descent (BCD) methods, closed-form PA is derived. Moreover, the phase and amplitude of IRS elements are derived for PBF design during each iteration. With the obtained HBF, the digital and analogue BFs are also derived. Based on this, joint schemes of PA, HBF and PBF are developed. Besides, an efficient iterative algorithm based upon the alternating optimization (AO), weighted minimum mean-square error (WMMSE) and Dinkelbach methods are presented for EE maximization and the suboptimal solution is obtained. Correspondingly, the energy-efficient design for joint PA, HBF and PBF is provided. Simulation results verify the proposed solutions.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"24 7","pages":"6566-6582"},"PeriodicalIF":7.7,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144219707","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